it's too much

two still failing
a little cleanup
2026-07-29 11:35:42 +00:00 · 2025-07-31 22:24:41 -07:00 · 2025-07-31 22:12:25 -07:00 · 2025-07-31 21:35:01 -07:00 · 2025-07-31 21:29:24 -07:00 · 2025-07-31 21:29:24 -07:00
1150 changed files with 33570 additions and 51090 deletions
@@ -1,8 +1,5 @@
 bazel-1.0.0.bazelrc

-# for now: filter out annoying TASTY warnings
-common --ui_event_filters=-INFO
-
 common --enable_bzlmod

 # Don't use toolchains_llvm for the swift app build
@@ -19,9 +16,9 @@ common --worker_sandboxing
 common --local_test_jobs=64
 common --jobs=64

-common --cxxopt="--std=c++23"
+common --cxxopt="--std=c++20"
 common --cxxopt="-Wno-deprecated-non-prototype"
-common --host_cxxopt="--std=c++23"
+common --host_cxxopt="--std=c++20"

 common --javacopt="-Xlint:-options"

@@ -1,3 +0,0 @@
-CompileFlags:
-  Add:
-    - "-std=c++23"
@@ -20,7 +20,7 @@ project/boot/
 project/plugins/project/
 project/target/
 bazel-bin
-bazel-eagle0*
+bazel-eagle0
 bazel-out
 bazel-testlogs
 .ijwb
@@ -32,6 +32,7 @@ buildWin.sh
 __pycache__/
 scripts/refresh_name_layers/vendor/
 scripts/refresh_name_layers/refresh_name_layers.zip
+.pre-commit-config.yaml
 .bazelbsp
 .bsp
 .metals
@@ -1,43 +0,0 @@
-# See https://pre-commit.com for more information
-# See https://pre-commit.com/hooks.html for more hooks
-repos:
-   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
-    hooks:
-    -   id: check-added-large-files
-    -   id: no-commit-to-branch
-        args: [--branch, main]
-   repo: https://github.com/pocc/pre-commit-hooks
-    rev: v1.3.5
-    hooks:
-    -   id: clang-format
-        args: [-i, --no-diff]
-        types_or: ["c++", "c#"]
-        exclude: ^src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins
-   repo: https://github.com/yoheimuta/protolint
-    rev: v0.42.2
-    hooks:
-    -   id: protolint
-        args: [-fix]
-        exclude: ^src/main/protobuf/scalapb/
-   repo: local
-    hooks:
-    -   id: scalafmt
-        name: scalafmt
-        language: system 
-        entry: scalafmt -i -f 
-        types_or: ["scala"]
- repo: local
-  hooks:
-      - id: gazelle
-        name: gazelle
-        language: system
-        entry: bazel run //:gazelle
-        files: '(\.go|\.proto|BUILD\.bazel|BUILD|WORKSPACE|WORKSPACE\.bazel|\.bzl)$'
-   repo: local
-    hooks:
-    -   id: update-action-result-types
-        name: update-action-result-types
-        language: system
-        entry: ./scripts/updateActionResultTypes.sh
-        files: 'src/main/protobuf/net/eagle0/eagle/common/action_result_type.proto'
@@ -1,47 +1,2 @@
-version = "3.9.9"
-runner.dialect = scala3
-rewrite.scala3.convertToNewSyntax = true
-# Keep braces, don't use significant indentation
-# rewrite.scala3.removeOptionalBraces = yes
-rewrite.scala3.insertEndMarkerMinLines = 15
-rewrite.scala3.removeEndMarkerMaxLines = 14
-
-# Strip margin settings
-assumeStandardLibraryStripMargin = false
-align.stripMargin = true
-
-# Code Style & Formatting
-align.preset = more
-align.multiline = true
-align.arrowEnumeratorGenerator = true
-spaces.inImportCurlyBraces = false
-spaces.beforeContextBoundColon = Never
-maxColumn = 120
-docstrings.style = Asterisk
-docstrings.wrap = yes
-
-# Method chaining
-newlines.beforeCurlyLambdaParams = multilineWithCaseOnly
-optIn.breakChainOnFirstMethodDot = true
-includeCurlyBraceInSelectChains = false
-
-# Advanced Scala 3 Features
-rewrite.scala3.countEndMarkerLines = all
-rewrite.redundantBraces.stringInterpolation = true
-rewrite.redundantBraces.parensForOneLineApply = true
-
-# Project-Specific Considerations
-optIn.annotationNewlines = true
-runner.optimizer.forceConfigStyleMinArgCount = 3
-
-# Import sorting configuration
-rewrite.rules = [SortImports, RedundantBraces, RedundantParens]
-rewrite.imports.sort = scalastyle
-rewrite.imports.groups = [
-  ["java\\..*"],
-  ["javax\\..*"],
-  ["scala\\..*"],
-  [".*"]
-]
-rewrite.imports.contiguousGroups = only
-rewrite.trailingCommas.style = never
+version = "3.6.1"
+runner.dialect = scala213
@@ -4,32 +4,26 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co

 ## Project Overview

-Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based
-combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.
+Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.

 ## Architecture

 **Three-Tier Game System:**
-
 - **Unity Client (C#)**: Real-time strategy game client with integrated tactical combat UI
 - **Eagle (Scala)**: Strategic layer managing turn-based gameplay, diplomacy, hero progression, and province control
- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle
-  resolution
+- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle resolution

 **Communication Flow:**
-
 ```
 Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC) 
 ```

 **Key Entry Points:**
-
 - `/src/main/csharp/net/eagle0/clients/unity/eagle0/` - Unity C# game client
 - `/src/main/scala/net/eagle0/eagle/Main.scala` - Eagle strategic game server
 - `/src/main/cpp/net/eagle0/shardok/shardok_server_main.cpp` - Shardok tactical server

 **Protocol Buffer Architecture:**
-
 - Extensive use of protobuf for type-safe communication
 - Separate packages: `api/` (client-facing), `internal/` (server state), `views/` (client projections)
 - Event sourcing pattern with immutable action history
@@ -37,17 +31,13 @@ Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC)
 ## Essential Commands

 ### Building
-
 ```bash
 # Build Eagle server (Scala strategic layer)
 bazel build //src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar

-# Build Shardok server (C++ tactical layer)
+# Build Shardok server (C++ tactical layer) 
 bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server

-# Shardok server includes both AI algorithms
-bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
-
 # Build Unity/C# client
 ./scripts/build_protos.sh         # Protocol buffer generation for Unity
 ./scripts/build_plugins.sh        # Native plugins for all platforms  
@@ -56,7 +46,6 @@ bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
 ```

 ### Running Services
-
 ```bash
 # Eagle server (port 40032)
 bazel run //src/main/scala/net/eagle0/eagle:eagle_server -- --eagle-grpc-port 40032
@@ -68,7 +57,6 @@ bazel run //src/main/cpp/net/eagle0/shardok:shardok-server --compilation_mode=op
 ```

 ### Testing
-
 ```bash
 # Run all tests
 bazel test //src/test/... //src/main/go/...
@@ -79,14 +67,12 @@ bazel test //src/test/cpp/...    # C++ Shardok tests
 ```

 ### Code Generation
-
 ```bash
 bazel run gazelle              # Update Go build files
 ./scripts/updateActionResultTypes.sh   # Update protocol buffer mappings
 ```

 ### Code Formatting
-
 ```bash
 # ALWAYS run clang-format after making any C++ or C# code changes
 clang-format -i <modified_files>
@@ -98,95 +84,26 @@ find . -name "*.cpp" -o -name "*.hpp" | xargs clang-format -i
 find . -name "*.cs" | xargs clang-format -i
 ```

-### Static Analysis
-
-```bash
-# Run clang-tidy static analysis on C++ files
-# Note: This may show some header include errors but will still analyze the main file
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' <file_path> -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
-
-# Example for AI files:
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' /Users/dancrosby/CodingProjects/github/eagle0/src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.cpp -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
-```
-
-## AI Algorithm Selection
-
-Eagle0 supports two AI algorithms for tactical combat decision-making:
-
-### Iterative Deepening AI (Default)
-
-The original minimax-based AI with sophisticated randomness handling:
-
- **Advantages**: Proven, sophisticated randomness evaluation, comprehensive lookahead
- **Use cases**: Production builds, scenarios requiring precise evaluation
- **Performance**: Single-threaded, thorough evaluation
-
-### Monte Carlo Tree Search AI (MCTS)
-
-Modern MCTS-based AI with multithreading support:
-
- **Advantages**: Multithreaded, better performance on modern CPUs, anytime algorithm
- **Use cases**: Performance testing, scenarios requiring fast decisions
- **Performance**: Multithreaded, adaptive depth based on time budget
-
-### Switching Between Algorithms
-
-The algorithm is selected at **runtime** via the ShardokAIClient constructor:
-
-```cpp
-// Using Iterative Deepening AI (default)
-ShardokAIClient client(playerId, isDefender, hexMap, settings);
-// OR explicitly:
-ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::ITERATIVE_DEEPENING);
-
-// Using MCTS AI
-ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::MCTS);
-```
-
-```bash
-# Build the server (includes both AI algorithms)
-bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
-
-# Test both algorithms
-bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_iterative_deepening_test
-bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_mcts_test  # If available
-
-# Performance tests
-./scripts/ai_perf_test.sh  # Uses whatever algorithm the server is configured to use
-```
-
-Both implementations are compatible with all existing interfaces and produce the same `SearchResult` structure.
-
-**Note**: Both implementations are documented in `src/main/cpp/net/eagle0/shardok/ai/AI_SCORING_SYSTEM.md`, including
-recommendations for improving MCTS randomness handling.
-
-The AI algorithm selection is made at runtime when creating ShardokAIClient instances, allowing different AI strategies
-to be used for different players or game situations within the same server process.
-
 ## Language-Specific Patterns

 **Scala (Strategic Layer):**
-
 - Use `EngineImpl.scala` for core game logic modifications
 - Follow event sourcing pattern - all changes through immutable actions
 - gRPC streaming for real-time client updates via `EagleServiceImpl.scala`
 - LLM integration in `/common/llm_integration/` for narrative generation

 **C++ (Tactical Layer):**
-
 - Performance-critical combat in `ShardokEngine.hpp/.cpp`
 - FlatBuffers for efficient serialization in `/flatbuffer/` directory
 - AI systems in `/ai/` subdirectory with pluggable strategy selectors
 - Extensive unit testing with Google Test framework

 **Protocol Buffers:**
-
 - Three-layer structure: `api/` (client), `internal/` (server), `views/` (projections)
 - Use `shardok_internal_interface.proto` for Eagle-Shardok communication
 - Maintain backward compatibility when modifying existing messages

 **C# (Unity Client):**
-
 - Located in `/src/main/csharp/net/eagle0/clients/unity/eagle0/`
 - Uses Unity 6 (6000.0.32f1) with comprehensive protobuf integration (100+ .proto files)
 - Key components: `EagleConnection.cs` (gRPC client), `EagleGameController.cs` (main game logic)
@@ -195,7 +112,6 @@ to be used for different players or game situations within the same server proce
 - Seamless transition between strategic gameplay and hex-based tactical combat

 **Go (Build Tools):**
-
 - Build automation and code generation utilities
 - AWS S3 integration for deployment artifacts

@@ -237,12 +153,10 @@ done
 ```

 **Important notes:**
-
 - Run tests multiple times (3-5) to account for performance variance
 - Focus on commands evaluated at each depth rather than total commands
 - Commands at different depths aren't directly comparable (depth 3 is more valuable than depth 2)
- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or
-  behavior changes.
+- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or behavior changes.

 ## Game Content

@@ -254,6 +168,4 @@ done

 - Bazel handles multi-language builds and dependencies
 - CI/CD via GitHub Actions with platform-specific build scripts in `/ci/github_actions/`
- Docker containerization available via `ci/eagle_run.Dockerfile`
- Always run "bazel run //:gazelle" after editing any BUILD.bazel files
- *ALWAYS ALWAYS* run "bazel run gazelle" after any change that modifies a BUILD.bazel file
+- Docker containerization available via `ci/eagle_run.Dockerfile`
@@ -1,66 +1,35 @@
-module(name = "net_eagle0")
-
-# Version constants
-SCALA_VERSION = "3.7.2"
-
-NETTY_VERSION = "4.1.110.Final"
-
-SCALAPB_VERSION = "1.0.0-alpha.1"
-
-AWS_SDK_VERSION = "2.28.1"
+bazel_dep(name = "apple_support", repo_name = "build_bazel_apple_support", version = "1.21.1")

 #
-# Core Build Tools
+# bazel-toolchain
 #

-bazel_dep(name = "bazel_skylib", version = "1.8.1")
-bazel_dep(name = "rules_pkg", version = "1.1.0")
-
-#
-# Language Support - Scala
-#
-
-bazel_dep(name = "rules_scala", version = "7.1.1")
-
-scala_config = use_extension(
-    "@rules_scala//scala/extensions:config.bzl",
-    "scala_config",
-)
-
-scala_config.settings(scala_version = SCALA_VERSION)
-
-scala_deps = use_extension(
-    "@rules_scala//scala/extensions:deps.bzl",
-    "scala_deps",
-)
-
-scala_deps.scala()
-
-scala_deps.scalatest()
-
-scala_deps.scala_proto()
-
-#
-# Language Support - C++
-#
-
-bazel_dep(name = "toolchains_llvm", version = "1.4.0")
+bazel_dep(name = "toolchains_llvm", version = "1.2.0")

+# Configure and register the toolchain.
 llvm = use_extension("@toolchains_llvm//toolchain/extensions:llvm.bzl", "llvm")

 llvm.toolchain(
    name = "llvm_toolchain",
-    llvm_version = "20.1.2",
+    llvm_version = "19.1.0",
 )

 use_repo(llvm, "llvm_toolchain")

-#
-# Language Support - Go
-#
+# Set dev_dependency so we can turn this off for swift MacOS builds
+register_toolchains(
+    "@llvm_toolchain//:all",
+    dev_dependency = True,
+)

-bazel_dep(name = "rules_go", repo_name = "io_bazel_rules_go", version = "0.56.1")
-bazel_dep(name = "gazelle", repo_name = "bazel_gazelle", version = "0.45.0")
+bazel_dep(name = "rules_pkg", version = "1.0.1")
+bazel_dep(name = "bazel_skylib", version = "1.7.1")
+bazel_dep(name = "protobuf", repo_name = "com_google_protobuf", version = "29.2")
+bazel_dep(name = "grpc", version = "1.71.0")
+bazel_dep(name = "grpc-java", version = "1.71.0")
+bazel_dep(name = "googletest", version = "1.15.2")
+bazel_dep(name = "rules_go", repo_name = "io_bazel_rules_go", version = "0.50.1")
+bazel_dep(name = "gazelle", repo_name = "bazel_gazelle", version = "0.40.0")

 go_sdk = use_extension("@io_bazel_rules_go//go:extensions.bzl", "go_sdk")

@@ -77,93 +46,68 @@ use_repo(
    "com_github_aws_aws_sdk_go_v2_credentials",
    "com_github_aws_aws_sdk_go_v2_service_s3",
    "org_golang_google_protobuf",
+    "org_golang_x_text",
+    "com_github_google_go_cmp",
 )

-#
-# Platform Support - Apple/iOS
-#
-
-bazel_dep(name = "apple_support", repo_name = "build_bazel_apple_support", version = "1.21.1")
-bazel_dep(name = "rules_apple", repo_name = "build_bazel_rules_apple", version = "3.16.1")
-bazel_dep(name = "rules_swift", repo_name = "build_bazel_rules_swift", version = "2.3.1")
+#go_sdk.nogo(
+#    nogo = "//:my_nogo",
+#)

 #
-# Protocol Buffers & RPC
+# rules_jvm_external
 #

-bazel_dep(name = "protobuf", repo_name = "com_google_protobuf", version = "29.2")
-bazel_dep(name = "grpc", version = "1.71.0")
-bazel_dep(name = "grpc-java", version = "1.71.0")
-bazel_dep(name = "flatbuffers", version = "25.2.10")
+scala_version = "2.13.14"

-#
-# Testing
-#
-
-bazel_dep(name = "googletest", version = "1.17.0")
-
-#
-# Java/Scala Dependencies
-#
-
-bazel_dep(name = "rules_jvm_external", version = "6.3")
+bazel_dep(
+    name = "rules_jvm_external",
+    version = "6.3",
+)

 maven = use_extension("@rules_jvm_external//:extensions.bzl", "maven")

 maven.install(
    artifacts = [
-        # Netty
-        "io.netty:netty-codec:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-http:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-socks:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-http2:%s" % NETTY_VERSION,
-        "io.netty:netty-handler:%s" % NETTY_VERSION,
-        "io.netty:netty-buffer:%s" % NETTY_VERSION,
-        "io.netty:netty-transport:%s" % NETTY_VERSION,
-        "io.netty:netty-resolver:%s" % NETTY_VERSION,
-        "io.netty:netty-common:%s" % NETTY_VERSION,
-        "io.netty:netty-handler-proxy:%s" % NETTY_VERSION,
-
-        # ScalaPB
-        "com.thesamet.scalapb:lenses_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-json4s_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-runtime_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-runtime-grpc_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:compilerplugin_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:protoc-bridge_3:0.9.9",
-
-        # JSON
-        "org.json4s:json4s-ast_3:4.1.0-M8",
-        "org.json4s:json4s-core_3:4.1.0-M8",
-        "org.json4s:json4s-native_3:4.1.0-M8",
-
-        # Testing
-        "org.scalamock:scalamock_3:7.4.1",
-
-        # AWS SDK
-        "software.amazon.awssdk:s3-transfer-manager:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:s3:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:regions:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:aws-core:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:sdk-core:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:utils:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:http-client-spi:%s" % AWS_SDK_VERSION,
-
-        # AWS Lambda
-        "com.amazonaws:aws-lambda-java-core:1.2.3",
-        "com.amazonaws:aws-lambda-java-events:3.13.0",
-
-        # Logging
+        "org.scala-lang:scala-library:%s" % scala_version,
+        "io.netty:netty-codec:4.1.110.Final",
+        "io.netty:netty-codec-http:4.1.110.Final",
+        "io.netty:netty-codec-socks:4.1.110.Final",
+        "io.netty:netty-codec-http2:4.1.110.Final",
+        "io.netty:netty-handler:4.1.110.Final",
+        "io.netty:netty-buffer:4.1.110.Final",
+        "io.netty:netty-transport:4.1.110.Final",
+        "io.netty:netty-resolver:4.1.110.Final",
+        "io.netty:netty-common:4.1.110.Final",
+        "io.netty:netty-handler-proxy:4.1.110.Final",
+        "com.thesamet.scalapb:lenses_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-json4s_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-runtime_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-runtime-grpc_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:compilerplugin_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:protoc-bridge_2.13:0.9.8",
+        "org.json4s:json4s-ast_2.13:4.0.7",
+        "org.json4s:json4s-core_2.13:4.0.7",
+        "org.json4s:json4s-native_2.13:4.0.7",
+        "org.scalamock:scalamock_2.13:6.0.0",
+        "software.amazon.awssdk:s3-transfer-manager:2.28.1",
+        "software.amazon.awssdk:s3:2.28.1",
+        "software.amazon.awssdk:regions:2.28.1",
+        "software.amazon.awssdk:aws-core:2.28.1",
+        "software.amazon.awssdk:sdk-core:2.28.1",
        "org.slf4j:slf4j-api:2.0.16",
        "org.slf4j:slf4j-simple:2.0.16",
-
-        # Other
+        #"software.amazon.awssdk:sns:2.28.1",
+        "software.amazon.awssdk:utils:2.28.1",
+        "software.amazon.awssdk:http-client-spi:2.28.1",
        "org.reactivestreams:reactive-streams:1.0.4",
+        "com.amazonaws:aws-lambda-java-core:1.2.3",
+        "com.amazonaws:aws-lambda-java-events:3.13.0",
        "javax.xml.bind:jaxb-api:2.3.1",
    ],
    duplicate_version_warning = "error",
    fail_if_repin_required = True,
-    lock_file = "//:maven_install.json",
+    lock_file = "//:maven_install.json",  #
    repositories = [
        "https://repo1.maven.org/maven2",
    ],
@@ -172,49 +116,58 @@ maven.install(
 use_repo(maven, "maven", "unpinned_maven")

 #
-# External Libraries
+# rules_apple
 #

+bazel_dep(
+    name = "rules_apple",
+    repo_name = "build_bazel_rules_apple",
+    version = "3.16.1",
+)
+bazel_dep(
+    name = "rules_swift",
+    repo_name = "build_bazel_rules_swift",
+    version = "2.3.1",
+)
+
+#
+# Unbazelified imports
+#
 http_archive = use_repo_rule("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

-# GTL (for parallel_hashmap)
-GTL_VERSION = "1.2.0"
+#
+# flatbuffers
+#
+bazel_dep(name = "flatbuffers", version = "25.2.10")

-GTL_SHA = "1969c45dd76eac0dd87e9e2b65cffe358617f4fe1bcd203f72f427742537913a"
+#
+# gtl (for parallel_hashmap)
+#
+
+gtl_version = "1.2.0"
+
+gtl_sha = "1969c45dd76eac0dd87e9e2b65cffe358617f4fe1bcd203f72f427742537913a"

 http_archive(
    name = "gtl",
    build_file = "@//external:BUILD.gtl",
-    sha256 = GTL_SHA,
-    strip_prefix = "gtl-%s" % GTL_VERSION,
-    url = "https://github.com/greg7mdp/gtl/archive/refs/tags/v%s.zip" % GTL_VERSION,
+    sha256 = gtl_sha,
+    strip_prefix = "gtl-%s" % gtl_version,
+    url = "https://github.com/greg7mdp/gtl/archive/refs/tags/v%s.zip" % gtl_version,
 )

-# Unity GoDice Plugin
-UNITY_GODICE_COMMIT = "18d6823991592e4d45fcc0f22692db849dea9063"
+#
+# Plugins for the native code for interacting with GoDice
+#
+unity_godice_commit = "18d6823991592e4d45fcc0f22692db849dea9063"

-UNITY_GODICE_SHA = "04e6ae4155965aab3372592e04061eba1256bb6ea7ccffd0d83f27574e5b3349"
+unity_godice_sha = "04e6ae4155965aab3372592e04061eba1256bb6ea7ccffd0d83f27574e5b3349"

 http_archive(
    name = "net_eagle0_unity_godice",
-    sha256 = UNITY_GODICE_SHA,
-    strip_prefix = "godice-framework-%s" % UNITY_GODICE_COMMIT,
+    sha256 = unity_godice_sha,
+    strip_prefix = "godice-framework-%s" % unity_godice_commit,
    urls = [
-        "https://github.com/nolen777/godice-framework/archive/%s.zip" % UNITY_GODICE_COMMIT,
+        "https://github.com/nolen777/godice-framework/archive/%s.zip" % unity_godice_commit,
    ],
 )
-
-#
-# Toolchain Registration
-#
-
-register_toolchains(
-    "//tools:unused_dependency_checker_error_and_opts_toolchain",
-    "@rules_scala//testing:scalatest_toolchain",
-)
-
-# Set dev_dependency so we can turn this off for swift MacOS builds
-register_toolchains(
-    "@llvm_toolchain//:all",
-    dev_dependency = True,
-)
@@ -1,205 +0,0 @@
-# Scala 3 Modernization Guide
-
-## Overview
-This document outlines opportunities to modernize the Eagle0 codebase to use Scala 3 best practices and features. The migration to Scala 3 is complete, but the code still uses many Scala 2 patterns that can be improved.
-
-## Modernization Opportunities
-
-### 1. **Convert Sealed Traits to Enums** 🎯 HIGH IMPACT
-**Benefits**: Better performance, more concise syntax, improved exhaustiveness checking
-
-**Current pattern** (`ExternalTextGenerationCaller.scala:23-31`):
-```scala
-sealed trait ExternalTextGenerationError extends Error {
-  def message: String
-}
-case class ExternalTextGenerationRateLimitError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationHttpError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationTimeoutError(message: String)
-    extends ExternalTextGenerationError
-```
-
-**Scala 3 improvement**:
-```scala
-enum ExternalTextGenerationError extends Error:
-  case RateLimit(code: Int, message: String)
-  case Http(code: Int, message: String) 
-  case Timeout(message: String)
-  
-  def message: String = this match
-    case RateLimit(_, msg) => msg
-    case Http(_, msg) => msg
-    case Timeout(msg) => msg
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/llm_integration/ExternalTextGenerationCaller.scala`
- `/src/main/scala/net/eagle0/eagle/model/action_result/generated_text_request/GeneratedTextRequestT.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/quest/concrete/QuestC.scala`
-
-### 2. **Convert Implicit Classes to Extension Methods** 🎯 HIGH IMPACT
-**Benefits**: Modern syntax, better IDE support, cleaner imports
-
-**Current pattern** (`MoreSeq.scala:23-26`):
-```scala
-implicit def SeqCollect[A, Repr[_]](coll: Repr[A])(implicit
-    itr: IsIterable[Repr[A]]
-): SeqCollect[A, Repr, itr.type] =
-  new SeqCollect[A, Repr, itr.type](coll, itr)
-```
-
-**Scala 3 improvement**:
-```scala
-extension [A, Repr[_]](coll: Repr[A])(using itr: IsIterable[Repr[A]])
-  def flatCollect[B](pf: PartialFunction[itr.A, Option[B]])(using Factory[B, Repr[B]]): Repr[B] =
-    Factory[B, Repr[B]].fromSpecific(itr(coll).collect(pf).flatten)
-    
-  def flatCollectFirst[B](pf: PartialFunction[itr.A, Option[B]]): Option[B] =
-    itr(coll).collect(pf).flatten.headOption
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/command_choice_helpers/CommandChooser.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/NewGameCreation.scala`
- `/src/main/scala/net/eagle0/eagle/library/actions/applier/ActionResultProtoApplierImpl.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/StartGameActionResultUtils.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/date/Date.scala`
-
-### 3. **Convert Implicit Parameters to Using Clauses** 🎯 MEDIUM IMPACT
-**Benefits**: Cleaner syntax, better tooling support, clearer intent
-
-**Current pattern**:
-```scala
-def method[T](value: T)(implicit ec: ExecutionContext): Future[T]
-def process[A](items: Seq[A])(implicit ord: Ordering[A]): Seq[A]
-```
-
-**Scala 3 improvement**:
-```scala
-def method[T](value: T)(using ExecutionContext): Future[T]
-def process[A](items: Seq[A])(using Ordering[A]): Seq[A]
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/OpenAIChatCompletionsServiceImpl.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/ClaudeServiceImpl.scala`
-
-### 4. **Opaque Types for Type Safety** 🎯 MEDIUM IMPACT
-**Benefits**: Zero runtime cost, compile-time type safety, prevents mixing up similar types
-
-**Pattern to look for**: Type aliases that represent distinct concepts
-```scala
-// Instead of: type UserId = String, type GameId = String
-opaque type UserId = String
-object UserId:
-  def apply(s: String): UserId = s
-  extension (id: UserId) 
-    def value: String = id
-    def isValid: Boolean = id.nonEmpty && id.length > 3
-
-opaque type GameId = Long  
-object GameId:
-  def apply(l: Long): GameId = l
-  extension (id: GameId) def value: Long = id
-```
-
-**Candidates**: Look for simple type aliases and ID types throughout the codebase.
-
-### 5. **Inline Methods for Performance** 🎯 LOW IMPACT
-**Benefits**: Compile-time optimization, better performance for hot paths
-
-**Pattern**: Mark small, frequently-called methods as `inline`
-```scala
-inline def isValidId(id: String): Boolean = 
-  id.nonEmpty && id.length > 3
-
-inline def calculateScore(base: Int, multiplier: Double): Double = 
-  base * multiplier
-```
-
-**Candidates**: Small utility methods in performance-critical paths (AI calculations, game state updates).
-
-### 6. **Union Types Instead of Complex Hierarchies** 🎯 LOW IMPACT  
-**Benefits**: Simpler type definitions for either/or scenarios
-
-**Pattern**: Simple sealed traits with only case classes
-```scala
-// Instead of:
-sealed trait Result
-case class Success(value: String) extends Result  
-case class Error(message: String) extends Result
-
-// Consider:
-type Result = Success | Error
-case class Success(value: String)
-case class Error(message: String)
-```
-
-### 7. **Context Functions for Cleaner APIs** 🎯 LOW IMPACT
-**Benefits**: Cleaner API design, implicit context passing
-
-**Pattern**: Replace implicit function parameters
-```scala
-// Old
-type Handler = GameState => Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = handler(gs)
-
-// New  
-type Handler = GameState ?=> Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = 
-  given GameState = gs
-  handler
-```
-
-## Implementation Priority
-
-### Phase 1: Quick Wins (High Impact, Low Risk)
-1. **Convert Extension Methods** in `MoreSeq.scala` - immediate readability improvement
-2. **Update Using Clauses** - simple find/replace operation  
-3. **Convert Simple Sealed Traits to Enums** - start with error types
-
-### Phase 2: Type Safety Improvements  
-4. **Add Opaque Types** for IDs and measurements - improves type safety
-5. **Inline Performance-Critical Methods** - measure before/after impact
-
-### Phase 3: Advanced Features (Lower Priority)
-6. **Union Types** where appropriate - only for simple either/or cases
-7. **Context Functions** for complex API improvements
-
-## Implementation Guidelines
-
-### Style Consistency
- **Keep curly braces**: Continue using Scala 2 style `{}` instead of indentation-based syntax
- **Gradual adoption**: Modernize files as they're touched for other reasons
- **Test thoroughly**: Each modernization should include verification that behavior is unchanged
-
-### Performance Considerations  
- **Measure enum performance**: Verify that enum conversion actually improves performance in hot paths
- **Benchmark inline methods**: Use profiling to confirm performance gains
- **Consider compilation time**: Some features may increase compile time
-
-### Migration Strategy
- **File-by-file approach**: Complete modernization of one file at a time
- **Separate PRs**: Each modernization type should be its own PR for easier review
- **Documentation**: Update this document as patterns are modernized
-
-## Success Criteria
- [ ] All extension methods converted from implicit classes
- [ ] All implicit parameters converted to using clauses  
- [ ] Key sealed traits converted to enums where appropriate
- [ ] Opaque types introduced for important ID types
- [ ] Performance-critical methods marked as inline (with benchmarks)
- [ ] No regression in functionality or performance
- [ ] Code remains readable and maintainable
-
-## Notes
- Focus on high-impact, low-risk improvements first
- Each change should be driven by clear benefits (performance, readability, type safety)
- Maintain backward compatibility where possible
- Document any breaking changes clearly
@@ -1,2 +1,51 @@
-# This file marks the root of the Bazel workspace.
-# See MODULE.bazel for external dependencies and setup.
+workspace(name = "net_eagle0")
+
+load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
+
+#
+# Scala support
+#
+
+scala_version = "2.13.14"
+
+#rules_scala_version = "6.6.0"
+
+#rules_scala_sha = "e734eef95cf26c0171566bdc24d83bd82bdaf8ca7873bec6ce9b0d524bdaf05d"
+
+#http_archive(
+#    name = "io_bazel_rules_scala",
+#    sha256 = rules_scala_sha,
+#    strip_prefix = "rules_scala-%s" % rules_scala_version,
+#    url = "https://github.com/bazelbuild/rules_scala/releases/download/v%s/rules_scala-v%s.tar.gz" % (rules_scala_version, rules_scala_version),
+#)
+
+# Using a commit from master to get 2.13.14 support. Restore the commented-out lines above with a new
+# release version when one is cut.
+rules_scala_commit = "e53a43bf48f10a5906b3e91c21798281cec1b334"
+
+rules_scala_sha = "b4fd903724d084d9d9f45e17fc22391bda745bf0574f8934d38a9c1c2fc18834"
+
+http_archive(
+    name = "io_bazel_rules_scala",
+    sha256 = rules_scala_sha,
+    strip_prefix = "rules_scala-%s" % rules_scala_commit,
+    url = "https://github.com/bazelbuild/rules_scala/archive/%s.zip" % rules_scala_commit,
+)
+
+load("@io_bazel_rules_scala//:scala_config.bzl", "scala_config")
+
+scala_config(scala_version = scala_version)
+
+load("//tools:toolchains.bzl", "scala_register_toolchains")
+
+scala_register_toolchains()
+
+load("@io_bazel_rules_scala//scala:scala.bzl", "scala_repositories")
+
+scala_repositories()
+
+load("@io_bazel_rules_scala//testing:scalatest.bzl", "scalatest_repositories", "scalatest_toolchain")
+
+scalatest_repositories()
+
+scalatest_toolchain()
@@ -1,305 +0,0 @@
-# Actions and Commands Model Usage Analysis
-
-This document analyzes all actions and commands in `src/main/scala/net/eagle0/eagle/library/actions/impl` to determine which use Scala models vs protobuf models, based on BUILD.bazel dependencies.
-
-**Legend:**
- ✅ **Scala Models Only** - Uses only `//src/main/scala/net/eagle0/eagle/model` dependencies
- ❌ **Uses Protobuf** - Has dependencies on `//src/main/protobuf` targets
- 🔄 **Partial Conversion** - Conversion attempted but blocked by dependencies
-
-## Summary
-
-Based on BUILD.bazel dependency analysis (2025-09-16, updated 2025-09-17):
- **Total Commands Analyzed:** 41
- **Commands Fully Migrated (No Protobuf):** 41 (100%) ✅
- **Commands Still Using Protobuf:** 0 (0%) ✅
- **Total Actions Analyzed:** 48
- **Actions Fully Migrated (No Protobuf):** 5 (10.4%)
- **Actions Partially Migrated:** 19 (39.6%)
- **Actions Still Using Protobuf:** 24 (50%)
- **Base Classes:** 8 protoless variants available, 6 still use protobuf
- **Shared Components:** `ResolvedEagleUnit` migrated to use `Option[BattalionT]` for proper null handling
-
-## Conversion Insights
-
-Based on conversion attempt of `ResolveTruceOfferCommand` (see [PR #4379](https://github.com/nolen777/eagle0/pull/4379)):
-
-### Key Challenges Discovered
-
-1. **LLM Integration Dependencies**: Commands that use `DiplomacyResolutionLlmRequestGenerator` face challenges because the LLM system still expects protobuf enum types, not Scala model enums.
-
-2. **Inconsistent Package Naming**: Some files have inconsistent package declarations vs BUILD file locations (e.g., `generated_text_request_generators` in package vs `llm_request_generators` in BUILD).
-
-3. **Model Constructor Differences**: Scala model constructors (e.g., `TruceOffer`) have different required parameters than their protobuf counterparts, requiring more complex data mapping.
-
-4. **Type System Complexity**: Union types and type constraints become more complex when mixing protobuf and Scala model types during transition.
-
-5. **Cascading Dependency Issues**: Converting to `ActionResultC` requires extensive trait dependencies (`ChangedBattalionT`, `ChangedHeroT`, `GeneratedTextRequestT`, etc.) that create complex BUILD dependency graphs, unlike simple protobuf `ActionResult`.
-
-6. **BUILD Complexity**: Each Scala model conversion requires significantly more BUILD dependencies than protobuf equivalents, making incremental conversion difficult.
-
-7. **Build Verification Critical**: Any conversion must maintain working build state - even simple commands like `DefendCommand` can break main server build due to dependency cascades.
-### Successful Conversion Elements
-
- ✅ Base class conversion (`SimpleAction` → `ProtolessSimpleAction`)
- ✅ Import updates for most Scala model types
- ✅ BUILD.bazel dependency updates for core action result types
- ✅ Basic type conversions for simple cases
-
-### Recommended Conversion Strategy
-
-1. **Architecture-First Approach**: Convert base infrastructure (LLM generators, action result builders) before individual commands
-2. **Wrapper Pattern**: Use existing `Protoless*ActionWrapper` classes as templates for gradual transition
-3. **Dependency Analysis**: Map full dependency trees before attempting conversions to avoid cascading build failures
-4. **Batch Conversions**: Convert related commands together to minimize dependency conflicts
-5. **Build Verification**: **ALWAYS** verify `//src/main/scala/net/eagle0/eagle:eagle_server` and test suite build before creating PRs
-
-### Conversion Requirements
-
-**Before creating any PR:**
- ✅ `bazel build //src/main/scala/net/eagle0/eagle:eagle_server` succeeds
- ✅ `bazel test //src/test/scala/... --keep_going` passes (or doesn't introduce new failures)
- ✅ All BUILD dependencies are correctly specified
- ✅ Scalafmt and other linters pass
-
---
-
-## Common Base Classes
-
-| File | Type | Model Usage | Notes |
-|------|------|-------------|-------|
-| Action.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ActionWithResultingState.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSingleResultAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ProtolessRandomSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessRandomSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| RandomSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| RandomSimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| RandomStateProtoSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| RandomStateTSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| SimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| VigorXPApplier.scala | Utility | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-
---
-
-## Actions
-
-### ✅ Fully Migrated Actions (No Protobuf Dependencies)
-
-These actions have been successfully migrated to use Scala models only:
-
-| File | Base Class | Notes |
-|------|------------|-------|
-| HeroBackstoryUpdateAction.scala | ProtolessSequentialResultsAction | Processes hero backstory updates with LLM integration |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | Uses component-based design (gameId, currentRoundId, currentDate, Scala models) |
-| ProvinceHeldAction.scala | ProtolessSimpleAction | Uses specific components (gameId, currentRoundId, defendingProvince, etc.) instead of full GameState |
-| UnaffiliatedHeroAppearedAction.scala | ProtolessSimpleAction | Handles unaffiliated hero appearance with name generation |
-| WithdrawnArmiesReturnHomeAction.scala | ProtolessSequentialResultsAction | Manages army withdrawal and return mechanics |
-
-### 🔄 Actions Partially Migrated (Using Protoless Base Classes)
-
-These actions use protoless base classes but still have some protobuf dependencies:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| CheckForFactionChangesAction.scala | ProtolessSequentialResultsAction | Still has some protobuf dependencies |
-| CheckForFailedQuestsAction.scala | ProtolessSequentialResultsAction | Depends on `unaffiliated_hero_quest_scala_proto` |
-| CheckForFulfilledQuestsAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndAttackDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndBattleAftermathPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndFreeForAllDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndPlayerCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndUnaffiliatedHeroActionsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndVassalCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| FreeForAllDrawAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| FriendlyMoveAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| PerformUncontestedConquestAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | **CONVERTED** - Uses specific components (gameId, currentRoundId, currentDate, Scala models) |
-| SafePassageArmiesProceedAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ShipmentArrivedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| TruceTurnBackPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| UnaffiliatedHeroRejoinedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| WonFreeForAllAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-
-### ❌ Actions Still Using Protobuf (Not Yet Using Protoless Base Classes)
-
-| File | Notes |
-|------|-------|
-| ChronicleEventGenerator.scala | Depends on multiple protobuf targets |
-| EndBattleRequestPhaseAction.scala | Depends on `diplomacy_offer_status_scala_proto` |
-| EndBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDefenseDecisionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDiplomacyResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleRequestPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndHandleRiotsPhaseAction.scala | Depends on multiple protobuf targets |
-| EndPleaseRecruitMePhaseAction.scala | Depends on multiple protobuf targets |
-| EndProvinceMoveResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| NewRoundAction.scala | Depends on multiple protobuf targets |
-| NewYearAction.scala | Depends on multiple protobuf targets |
-| PerformFoodConsumptionPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformForcedTurnBackAction.scala | Depends on multiple protobuf targets |
-| PerformHeroDeparturesAction.scala | Depends on multiple protobuf targets |
-| PerformHostileArmySetupAction.scala | Depends on multiple protobuf targets |
-| PerformProvinceEventsAction.scala | Depends on `province_event_scala_proto` |
-| PerformProvinceMoveResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformReconResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformUnaffiliatedHeroesAction.scala | Depends on `unaffiliated_hero_quest_scala_proto` |
-| PerformVassalCommandsPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformVassalDefenseDecisionsAction.scala | Depends on multiple protobuf targets |
-| PrisonerEscapeAction.scala | Depends on `game_state_scala_proto` |
-| PrisonerExchangeAction.scala | Depends on multiple protobuf targets |
-| RequestBattlesAction.scala | Depends on multiple protobuf targets |
-| RequestFreeForAllBattlesAction.scala | Depends on multiple protobuf targets |
-| ResolveBattleAction.scala | Depends on `shardok_internal_interface_scala_grpc` |
-| UnaffiliatedHeroMovedAction.scala | Depends on multiple protobuf targets |
-| UnaffiliatedHeroesChangedAction.scala | Depends on multiple protobuf targets |
-
---
-
-## Commands
-
-✅ **ALL COMMANDS FULLY MIGRATED** (100% - 41/41 commands)
-
-All 41 commands in the codebase have been successfully migrated to use Scala models only, with no protobuf dependencies. This includes:
-
- **Simple Actions**: Use `ProtolessSimpleAction` base class
- **Random Actions**: Use `ProtolessRandomSimpleAction` base class
- **Complex Domain Models**: Successfully integrated with LLM systems, diplomacy, quest fulfillment, and state management
- **Complete Type Safety**: All commands now use type-safe Scala domain models
-
-**Key Migration Achievements:**
- ✅ All military commands (ArmTroops, Train, Organize, etc.)
- ✅ All diplomacy commands (Resolve Alliance/Truce/Ransom offers, etc.)
- ✅ All LLM-integrated commands (backstory generation, diplomacy resolution)
- ✅ All quest and event commands
- ✅ Final remaining command (FreeForAllDecisionCommand) migrated
-
---
-
-## Diplomacy Helpers
-
-All diplomacy helpers use **Scala models only**:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| AllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| BreakAllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| InvitationResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| RansomResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| TruceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-
---
-
-## Migration Priority Analysis
-
-Based on the BUILD.bazel dependency analysis, here are the key findings and recommendations:
-
-### 🎯 High Impact Migration Targets
-
-**Core Dependencies Blocking Multiple Commands:**
-
-1. **`action_result_scala_proto`** - Used by 12+ commands
-   - Blocks: `DefendCommand`, `FreeForAllDecisionCommand`, diplomacy resolvers
-   - Impact: Would unlock many command migrations
-
-2. **`available_command_scala_proto` / `selected_command_scala_proto`** - Used by 10+ commands
-   - Blocks: All UI-interactive commands
-   - Impact: Would enable client-server interaction model migration
-
-3. **`game_state_scala_proto`** - Used by 8+ commands
-   - Blocks: Complex state-dependent commands
-   - Impact: Core state representation migration
-
-### 📊 Migration Tiers by Complexity
-
-**Tier 1 - Quick Wins (2 commands):**
- `ArmTroopsCommand` - Only `battalion_type` dependency
- `TrainCommand` - Only `battalion_type` dependency
- **Effort:** Low, **Impact:** Demonstrates battalion model usage
-
-**Tier 2 - API Layer (5 commands):**
- Commands blocked by `available_command`/`selected_command`
- **Effort:** Medium, **Impact:** High (enables UI interaction models)
-
-**Tier 3 - Diplomacy Suite (6 commands):**
- All `Resolve*Command` diplomacy commands
- **Effort:** High, **Impact:** High (complete diplomacy model migration)
- **Strategy:** Migrate as a group after diplomacy models are ready
-
-### 🏆 Success Metrics
-
-**Current Status:**
- ✅ **100% of commands fully migrated** (41/41) 🎉
- ✅ **All diplomacy helpers use Scala models**
- ✅ **All protoless base classes available**
- ✅ **ALL command migration completed**
-
-**Completed Milestones:**
- ✅ **70% target:** Migrate Tier 1 + some Tier 2 commands **COMPLETED**
- ✅ **80% target:** Continue with remaining non-diplomacy commands **COMPLETED**
- ✅ **85% target:** Complete API layer migration **COMPLETED**
- ✅ **95% target:** Complete diplomacy migration **COMPLETED**
- ✅ **100% target:** Migrate final remaining command (FreeForAllDecisionCommand) **COMPLETED**
-
-### 🎯 Action Migration Progress
-
-**Migration Statistics:**
- 5/48 Actions fully migrated (10.4%)
- 20/48 Actions using protoless base classes but with protobuf dependencies (41.7%)
- 24/48 Actions still fully on protobuf (50%)
-
-**Successfully Migrated Actions:**
-1. **HeroBackstoryUpdateAction** - LLM integration for hero backstories
-2. **ProvinceConqueredAction** - Component-based design with prisoner handling and province conquest
-3. **ProvinceHeldAction** - Component-based design pattern (gameId, currentRoundId, specific models)
-4. **UnaffiliatedHeroAppearedAction** - Hero appearance with name generation
-5. **WithdrawnArmiesReturnHomeAction** - Army withdrawal mechanics
-
-**Recent Migration Updates (2025-09-17):**
- **ResolvedEagleUnit** - Changed `battalion: BattalionT` to `battalion: Option[BattalionT]`
-  - Properly handles units without battalions (battalion ID -1)
-  - Updated `ShardokInterfaceGrpcClient` to check for `defaultBattalionId` and use `None`
-  - Updated `ResolveBattleAction`, `ProvinceConqueredAction`, `RequestBattlesAction`
-  - All tests updated to handle optional battalions
-
-**Key Migration Patterns:**
- ✅ Use specific components instead of full GameState (see ProvinceHeldAction, ProvinceConqueredAction)
- ✅ Convert protobuf models to Scala models at Action boundaries
- ✅ Update BUILD.bazel to remove protobuf dependencies
- ✅ Update all call sites and tests
- ✅ Use `Option[T]` for optional fields instead of special sentinel values (e.g., battalion ID -1)
-
-**Next Migration Candidates (Simple Actions with Protoless Base):**
-1. **FreeForAllDrawAction** - Already uses ProtolessSimpleAction
-2. **FriendlyMoveAction** - Already uses ProtolessSimpleAction
-3. **ShipmentArrivedAction** - Already uses ProtolessSimpleAction
-4. **WonFreeForAllAction** - Already uses ProtolessSimpleAction
-5. **ProvinceConqueredAction** - Already uses ProtolessSimpleAction, only needs `common_unit` migration
-
-### 🔄 Conversion Strategy Updates
-
-**Revised Approach Based on Analysis:**
-
-1. **Focus on Core Dependencies First**
-   - Migrate `battalion_type` model (unlocks 2 commands immediately)
-   - Migrate `action_result` model (unlocks 12+ commands)
-   - Migrate `available_command`/`selected_command` (unlocks UI layer)
-
-2. **Leverage Existing Success**
-   - 77.5% of commands already fully migrated
-   - Use migrated commands as reference implementations
-   - Diplomacy helpers prove complex business logic can work with Scala models
-
-3. **Group Related Migrations**
-   - Military commands: `ArmTroopsCommand`, `TrainCommand`, `OrganizeTroopsCommand`
-   - UI commands: All using `available_command`/`selected_command`
-   - Diplomacy commands: All `Resolve*Command` variants
-
---
-
-*Updated on 2025-09-17 - Analysis based on BUILD.bazel dependencies and code review*
-*Latest update: ResolvedEagleUnit migrated to use Option[BattalionT] for proper battalion handling*
@@ -1,2 +1,2 @@

-UNITY_VERSION='6000.2.7f2'
+UNITY_VERSION='6000.1.11f1'
@@ -1,7 +1,7 @@
 {
  "__AUTOGENERATED_FILE_DO_NOT_MODIFY_THIS_FILE_MANUALLY": "THERE_IS_NO_DATA_ONLY_ZUUL",
-  "__INPUT_ARTIFACTS_HASH": 571423113,
-  "__RESOLVED_ARTIFACTS_HASH": 438039003,
+  "__INPUT_ARTIFACTS_HASH": 644967262,
+  "__RESOLVED_ARTIFACTS_HASH": -595552834,
  "conflict_resolution": {
    "com.google.guava:failureaccess:1.0.1": "com.google.guava:failureaccess:1.0.2",
    "io.netty:netty-buffer:4.1.110.Final": "io.netty:netty-buffer:4.1.112.Final",
@@ -14,7 +14,8 @@
    "io.netty:netty-transport-native-unix-common:4.1.110.Final": "io.netty:netty-transport-native-unix-common:4.1.112.Final",
    "io.netty:netty-transport:4.1.110.Final": "io.netty:netty-transport:4.1.112.Final",
    "io.opencensus:opencensus-api:0.31.0": "io.opencensus:opencensus-api:0.31.1",
-    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0"
+    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0",
+    "org.scala-lang:scala-library:2.13.14": "org.scala-lang:scala-library:2.13.15"
  },
  "artifacts": {
    "com.amazonaws:aws-lambda-java-core": {
@@ -167,29 +168,23 @@
      },
      "version": "2.10.0"
    },
-    "com.thesamet.scalapb:compilerplugin_3": {
+    "com.thesamet.scalapb:compilerplugin_2.13": {
      "shasums": {
-        "jar": "e7d7156269fc23cbb539eea60f07c3230aa05a726434fc942b040495567f0a2d"
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      },
      "version": "1.0.0-alpha.1"
    },
-    "com.thesamet.scalapb:lenses_3": {
+    "com.thesamet.scalapb:lenses_2.13": {
      "shasums": {
-        "jar": "63fdffc573947402c526c49cf6ee92990ede88d55eb56af5123dfd247b365185"
+        "jar": "46902feb0fd848fce92e234514254dc43b3cde5f6e10e88ae6eec52f4c016fbc"
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      "shasums": {
-        "jar": "403f0e7223c8fd052cff0fbf977f3696c387a696a3a12d7b031d95660c7552f5"
+        "jar": "0b3827da2cd9bca867d6963c2a821e7eaff41f5ac3babf671c4c00408bd14a9b"
      },
-      "version": "0.9.7"
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-      },
-      "version": "0.9.9"
+      "version": "0.9.8"
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      "shasums": {
@@ -197,24 +192,30 @@
      },
      "version": "0.9.7"
    },
-    "com.thesamet.scalapb:scalapb-json4s_3": {
+    "com.thesamet.scalapb:scalapb-json4s_2.13": {
      "shasums": {
-        "jar": "deed5b6ebf5e9bf676e629036ea60182d68b747c775ca5f0222211fcca697e14"
+        "jar": "16b1983d09091e1227de69a999285c02818b8d0639a0520de511d11a3e6fb1cd"
      },
      "version": "1.0.0-alpha.1"
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-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": {
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": {
      "shasums": {
-        "jar": "0c8574f91693cb08795ed16a601bcf6d5ba46ba8dbd71792910b706cce995c7a"
+        "jar": "75eb71fea9509308070812b8bcf1eec90c065be3e9d8c60b12098f206db6c581"
      },
      "version": "1.0.0-alpha.1"
    },
-    "com.thesamet.scalapb:scalapb-runtime_3": {
+    "com.thesamet.scalapb:scalapb-runtime_2.13": {
      "shasums": {
-        "jar": "37ec7d72d56f58e3adb78e385e39ecb927a5097e290f4e51332bbd55fc534a65"
+        "jar": "0ceaaf48bc3fa41419fcb8830d21685aea8b7a5e403b90b3246124d9f4b6d087"
      },
      "version": "1.0.0-alpha.1"
    },
+    "com.thoughtworks.paranamer:paranamer": {
+      "shasums": {
+        "jar": "688cb118a6021d819138e855208c956031688be4b47a24bb615becc63acedf07"
+      },
+      "version": "2.8"
+    },
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      "shasums": {
        "jar": "f9f6cb103f2ddc3c99a9d80ada2ae7bf0685111fd6bffccb72033d1da4e6ff23"
@@ -460,35 +461,41 @@
      },
      "version": "13.0"
    },
-    "org.json4s:json4s-ast_3": {
+    "org.json4s:json4s-ast_2.13": {
      "shasums": {
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-      },
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-      },
-      "version": "4.1.0-M8"
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-      "shasums": {
-        "jar": "aeb0034d1f7eb854b56a672b7dc97c2a96b8109d8dbc8d3128faeca04274fbd3"
+        "jar": "3135eceb95b679ea228e3543267d12bea5f4bdb68e3e8fc55402824d85885e7e"
      },
      "version": "4.0.7"
    },
-    "org.json4s:json4s-native-core_3": {
+    "org.json4s:json4s-core_2.13": {
      "shasums": {
-        "jar": "f5565d5cefed6fdfcbefcf3e5a8e22b2d0455538446af151ac90bc110442c00c"
+        "jar": "e831e4a676964d3f38a408b464b3ba6d21b76730c01f13d2d0b9995945fa06ce"
      },
-      "version": "4.1.0-M8"
+      "version": "4.0.7"
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-    "org.json4s:json4s-native_3": {
+    "org.json4s:json4s-jackson-core_2.13": {
      "shasums": {
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+        "jar": "c189e11ddb2c8e15544386687d986108584934b06a025c09c334f24b11260528"
      },
-      "version": "4.1.0-M8"
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-native-core_2.13": {
+      "shasums": {
+        "jar": "038ce5b91ba8d6198eb11368f90bf7c8f0e05d8fb6a914d1ccf25aa88a8ff6da"
+      },
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-native_2.13": {
+      "shasums": {
+        "jar": "728c6970ff1f6101ca2d47a32c0f7d55277fab92485eef8a8be3e289a4e445ea"
+      },
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-scalap_2.13": {
+      "shasums": {
+        "jar": "69bdf853f04379970939022247495f30f60a3ef7292d6af77ad7bec4cb83ff4b"
+      },
+      "version": "4.0.7"
    },
    "org.ow2.asm:asm": {
      "shasums": {
@@ -502,29 +509,29 @@
      },
      "version": "1.0.4"
    },
-    "org.scala-lang.modules:scala-collection-compat_3": {
+    "org.scala-lang.modules:scala-collection-compat_2.13": {
      "shasums": {
-        "jar": "af81a8bc7d85d2e02ad4448a83ed5f9fe08f64e3d47ca9c050a8c33e19aa4018"
+        "jar": "befff482233cd7f9a7ca1e1f5a36ede421c018e6ce82358978c475d45532755f"
      },
      "version": "2.12.0"
    },
    "org.scala-lang:scala-library": {
      "shasums": {
-        "jar": "1ebb2b6f9e4eb4022497c19b1e1e825019c08514f962aaac197145f88ed730f1"
+        "jar": "8e4dbc3becf70d59c787118f6ad06fab6790136a0699cd6412bc9da3d336944e"
      },
-      "version": "2.13.16"
+      "version": "2.13.15"
    },
-    "org.scala-lang:scala3-library_3": {
+    "org.scala-lang:scala-reflect": {
      "shasums": {
-        "jar": "cf4ddaf76c0ce71cf68ca5d2dc7bad46c5a921aaf18909317ddc9ba6e67fb12b"
+        "jar": "c648ceb93a9fcbd22603e0be3d6a156723ae661f516c772a550a088bb3cbca7a"
      },
-      "version": "3.3.6"
+      "version": "2.13.12"
    },
-    "org.scalamock:scalamock_3": {
+    "org.scalamock:scalamock_2.13": {
      "shasums": {
-        "jar": "9a421b4eb47cbef8394998ec864eea21c1c3e43b1b80966efd493cd06e7b4516"
+        "jar": "f34aacf41fddcf7341408b932ff3cad836c0fc59a080cb19548a587961b4ec2f"
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-      "version": "7.4.1"
+      "version": "6.0.0"
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      "shasums": {
@@ -786,45 +793,41 @@
      "org.jetbrains.kotlin:kotlin-stdlib",
      "org.jetbrains.kotlin:kotlin-stdlib-common"
    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
      "com.google.protobuf:protobuf-java",
      "com.thesamet.scalapb:protoc-gen_2.13",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:lenses_3": [
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:lenses_2.13": [
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
    "com.thesamet.scalapb:protoc-bridge_2.13": [
      "dev.dirs:directories",
      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:protoc-bridge_3": [
-      "dev.dirs:directories",
-      "org.scala-lang:scala3-library_3"
-    ],
    "com.thesamet.scalapb:protoc-gen_2.13": [
      "com.thesamet.scalapb:protoc-bridge_2.13",
      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-json4s_3": [
-      "com.thesamet.scalapb:scalapb-runtime_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
-      "com.thesamet.scalapb:scalapb-runtime_3",
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
      "io.grpc:grpc-protobuf",
      "io.grpc:grpc-stub",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
+    "com.thesamet.scalapb:scalapb-runtime_2.13": [
      "com.google.protobuf:protobuf-java",
-      "com.thesamet.scalapb:lenses_3",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "com.thesamet.scalapb:lenses_2.13",
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
    "io.grpc:grpc-api": [
      "com.google.code.findbugs:jsr305",
@@ -992,35 +995,41 @@
      "org.jetbrains.kotlin:kotlin-stdlib-common",
      "org.jetbrains:annotations"
    ],
-    "org.json4s:json4s-ast_3": [
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-      "org.scala-lang:scala3-library_3"
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-      "org.json4s:json4s-ast_3",
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-      "org.scala-lang:scala3-library_3"
-    ],
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-      "org.json4s:json4s-native-core_3",
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.scala-lang.modules:scala-collection-compat_3": [
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.scala-lang:scala3-library_3": [
+    "org.json4s:json4s-ast_2.13": [
      "org.scala-lang:scala-library"
    ],
-    "org.scalamock:scalamock_3": [
-      "org.scala-lang:scala3-library_3"
+    "org.json4s:json4s-core_2.13": [
+      "com.thoughtworks.paranamer:paranamer",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-scalap_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-jackson-core_2.13": [
+      "com.fasterxml.jackson.core:jackson-databind",
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native-core_2.13": [
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native_2.13": [
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang:scala-reflect": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scalamock:scalamock_2.13": [
+      "org.scala-lang:scala-library",
+      "org.scala-lang:scala-reflect"
    ],
    "org.slf4j:slf4j-simple": [
      "org.slf4j:slf4j-api"
@@ -1463,14 +1472,14 @@
      "okio",
      "okio.internal"
    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
      "scalapb",
      "scalapb.compiler",
      "scalapb.internal",
      "scalapb.options",
      "scalapb.options.compiler"
    ],
-    "com.thesamet.scalapb:lenses_3": [
+    "com.thesamet.scalapb:lenses_2.13": [
      "scalapb.lenses"
    ],
    "com.thesamet.scalapb:protoc-bridge_2.13": [
@@ -1478,21 +1487,16 @@
      "protocbridge.codegen",
      "protocbridge.frontend"
    ],
-    "com.thesamet.scalapb:protoc-bridge_3": [
-      "protocbridge",
-      "protocbridge.codegen",
-      "protocbridge.frontend"
-    ],
    "com.thesamet.scalapb:protoc-gen_2.13": [
      "protocgen"
    ],
-    "com.thesamet.scalapb:scalapb-json4s_3": [
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
      "scalapb.json4s"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
      "scalapb.grpc"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
+    "com.thesamet.scalapb:scalapb-runtime_2.13": [
      "com.google.protobuf.any",
      "com.google.protobuf.api",
      "com.google.protobuf.compiler.plugin",
@@ -1511,6 +1515,9 @@
      "scalapb.options",
      "scalapb.textformat"
    ],
+    "com.thoughtworks.paranamer:paranamer": [
+      "com.thoughtworks.paranamer"
+    ],
    "commons-codec:commons-codec": [
      "org.apache.commons.codec",
      "org.apache.commons.codec.binary",
@@ -1845,24 +1852,28 @@
      "org.intellij.lang.annotations",
      "org.jetbrains.annotations"
    ],
-    "org.json4s:json4s-ast_3": [
+    "org.json4s:json4s-ast_2.13": [
      "org.json4s",
      "org.json4s.prefs"
    ],
-    "org.json4s:json4s-core_3": [
+    "org.json4s:json4s-core_2.13": [
      "org.json4s",
      "org.json4s.prefs",
      "org.json4s.reflect"
    ],
-    "org.json4s:json4s-jackson-core_3": [
+    "org.json4s:json4s-jackson-core_2.13": [
      "org.json4s.jackson"
    ],
-    "org.json4s:json4s-native-core_3": [
+    "org.json4s:json4s-native-core_2.13": [
      "org.json4s.native"
    ],
-    "org.json4s:json4s-native_3": [
+    "org.json4s:json4s-native_2.13": [
      "org.json4s.native"
    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.json4s.scalap",
+      "org.json4s.scalap.scalasig"
+    ],
    "org.ow2.asm:asm": [
      "org.objectweb.asm",
      "org.objectweb.asm.signature"
@@ -1870,7 +1881,7 @@
    "org.reactivestreams:reactive-streams": [
      "org.reactivestreams"
    ],
-    "org.scala-lang.modules:scala-collection-compat_3": [
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
      "scala.collection.compat",
      "scala.collection.compat.immutable",
      "scala.util.control.compat",
@@ -1909,26 +1920,22 @@
      "scala.util.hashing",
      "scala.util.matching"
    ],
-    "org.scala-lang:scala3-library_3": [
-      "scala",
-      "scala.annotation",
-      "scala.annotation.internal",
-      "scala.annotation.unchecked",
-      "scala.compiletime",
-      "scala.compiletime.ops",
-      "scala.compiletime.testing",
-      "scala.deriving",
-      "scala.quoted",
-      "scala.quoted.runtime",
-      "scala.reflect",
-      "scala.runtime",
-      "scala.runtime.coverage",
-      "scala.runtime.function",
-      "scala.runtime.stdLibPatches",
-      "scala.util",
-      "scala.util.control"
+    "org.scala-lang:scala-reflect": [
+      "scala.reflect.api",
+      "scala.reflect.internal",
+      "scala.reflect.internal.annotations",
+      "scala.reflect.internal.pickling",
+      "scala.reflect.internal.settings",
+      "scala.reflect.internal.tpe",
+      "scala.reflect.internal.transform",
+      "scala.reflect.internal.util",
+      "scala.reflect.io",
+      "scala.reflect.macros",
+      "scala.reflect.macros.blackbox",
+      "scala.reflect.macros.whitebox",
+      "scala.reflect.runtime"
    ],
-    "org.scalamock:scalamock_3": [
+    "org.scalamock:scalamock_2.13": [
      "org.scalamock",
      "org.scalamock.clazz",
      "org.scalamock.context",
@@ -1939,8 +1946,6 @@
      "org.scalamock.scalatest",
      "org.scalamock.scalatest.proxy",
      "org.scalamock.specs2",
-      "org.scalamock.stubs",
-      "org.scalamock.stubs.internal",
      "org.scalamock.util"
    ],
    "org.slf4j:slf4j-api": [
@@ -2272,14 +2277,14 @@
      "com.google.truth:truth",
      "com.squareup.okhttp:okhttp",
      "com.squareup.okio:okio",
-      "com.thesamet.scalapb:compilerplugin_3",
-      "com.thesamet.scalapb:lenses_3",
+      "com.thesamet.scalapb:compilerplugin_2.13",
+      "com.thesamet.scalapb:lenses_2.13",
      "com.thesamet.scalapb:protoc-bridge_2.13",
-      "com.thesamet.scalapb:protoc-bridge_3",
      "com.thesamet.scalapb:protoc-gen_2.13",
-      "com.thesamet.scalapb:scalapb-json4s_3",
-      "com.thesamet.scalapb:scalapb-runtime-grpc_3",
-      "com.thesamet.scalapb:scalapb-runtime_3",
+      "com.thesamet.scalapb:scalapb-json4s_2.13",
+      "com.thesamet.scalapb:scalapb-runtime-grpc_2.13",
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "com.thoughtworks.paranamer:paranamer",
      "commons-codec:commons-codec",
      "commons-logging:commons-logging",
      "dev.dirs:directories",
@@ -2325,17 +2330,18 @@
      "org.jetbrains.kotlin:kotlin-stdlib",
      "org.jetbrains.kotlin:kotlin-stdlib-common",
      "org.jetbrains:annotations",
-      "org.json4s:json4s-ast_3",
-      "org.json4s:json4s-core_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.json4s:json4s-native-core_3",
-      "org.json4s:json4s-native_3",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.json4s:json4s-native_2.13",
+      "org.json4s:json4s-scalap_2.13",
      "org.ow2.asm:asm",
      "org.reactivestreams:reactive-streams",
-      "org.scala-lang.modules:scala-collection-compat_3",
+      "org.scala-lang.modules:scala-collection-compat_2.13",
      "org.scala-lang:scala-library",
-      "org.scala-lang:scala3-library_3",
-      "org.scalamock:scalamock_3",
+      "org.scala-lang:scala-reflect",
+      "org.scalamock:scalamock_2.13",
      "org.slf4j:slf4j-api",
      "org.slf4j:slf4j-simple",
      "software.amazon.awssdk:annotations",
@@ -1,310 +0,0 @@
-# Scala 3 Migration: Reflection Issues Found
-
-This document catalogs all reflection-related problems discovered during the Scala 2.13.16 → Scala 3.7.2 migration of the Eagle0 codebase.
-
-## Summary
-
-The migration revealed several categories of reflection issues that needed to be addressed for Scala 3 compatibility:
-
-1. **Scala 2 Runtime Reflection API** - No longer available in Scala 3
-2. **Settings System Reflection** - Custom reflection for loading settings singletons 
-3. **json4s Automatic Case Class Extraction** - Uses reflection that fails with Scala 3 metaprogramming classes
-4. **ScalaTest Exception Handling** - Syntax changes affecting exception variable binding
-
-## 1. Scala 2 Runtime Reflection (FIXED)
-
-### Issue
-Tests using `scala.reflect.runtime.universe` fail because this reflection API doesn't exist in Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-### Error
-```scala
-import scala.reflect.runtime.universe  // Not available in Scala 3
-```
-
-### Solution Applied
-**Deleted the test entirely** as it was redundant. The test was verifying that auto-generated Scala objects (created by Bazel from proto enum values) matched their source proto values - something already guaranteed by the build system. Since the objects are generated directly from the proto definitions, this test provided no value.
-
-**Files deleted:**
- `src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-## 2. Settings System Reflection (FIXED)
-
-### Issue
-Custom `SettingsLoader` class used reflection to access Scala object singletons, but the reflection pattern changed between Scala 2 and Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/settings/loaders/SettingsLoader.scala`
-
-### Error
-```
-java.lang.NoSuchMethodException: net.eagle0.eagle.library.settings.ApprehendOutlawVigorCost$.MODULE$
-```
-
-### Root Cause
-In Scala 2, singleton objects are accessed via `ClassName$.MODULE$()`, but in Scala 3, they're accessed directly via `ClassName$` field. Additionally, `scala.reflect.runtime.universe` is not available in Scala 3.
-
-### Solution Applied
-**Completely eliminated reflection** by auto-generating the entire `SettingsLoader.scala` file from BUILD.bazel definitions:
-
-1. **Created generator**: `src/main/go/net/eagle0/build/settings_loader_generator/settings_loader_generator.go` - parses BUILD.bazel and generates complete SettingsLoader.scala with pattern matching for all 272 settings
-
-2. **Added genrule**: In `src/main/scala/net/eagle0/eagle/library/settings/loaders/BUILD.bazel`:
-```python
-genrule(
-    name = "settings_loader_src",
-    srcs = ["//src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel"],
-    outs = ["SettingsLoader.scala"],
-    cmd = "$(location //src/main/go/net/eagle0/build/settings_loader_generator) $(location //src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel) > $@",
-    tools = ["//src/main/go/net/eagle0/build/settings_loader_generator"],
-)
-```
-
-3. **Result**: SettingsLoader now uses compile-time pattern matching instead of reflection:
-```scala
-private def settingObjectForKey(key: String): Any = key match {
-  case "ActionVigorCost" => ActionVigorCost
-  case "BaseFoodBuyPrice" => BaseFoodBuyPrice
-  // ... all 272 settings auto-generated
-  case _ => throw NoSuchSettingException(key)
-}
-```
-
-### Benefits
- **No reflection** - Completely Scala 3 compatible
- **Maintainable** - New settings automatically included when added to BUILD.bazel
- **Performance** - Pattern matching is faster than reflection
- **Type-safe** - Compile-time checking of all settings
-
-## 3. json4s Reflection Issues (MULTIPLE LOCATIONS)
-
-### 3.1 EagleServiceImpl JSON Serialization (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/service/EagleServiceImpl.scala`
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-```
-
-#### Root Cause
-json4s automatic case class serialization uses reflection that tries to access Scala 3 metaprogramming classes (`scala.quoted.staging.package$`) which aren't available at runtime.
-
-#### Solution Applied
-Replaced automatic json4s serialization with ScalaPB's built-in JSON support:
-
-```scala
-// Old (reflection-based):
-// implicit val formats: DefaultFormats.type = DefaultFormats
-// write(actionResultView)
-
-// New (ScalaPB JSON support):
-import scalapb.json4s.JsonFormat
-JsonFormat.toJsonString(actionResultView.toProto)
-```
-
-### 3.2 ShardokMapInfo JSON Parsing (FIXED)
-
-#### Files Affected  
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala` (Line 44)
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-at org.json4s.reflect.ScalaSigReader$.readConstructor(ScalaSigReader.scala:42)
-```
-
-#### Root Cause
-The line `val extracted = parsedJson.extract[List[ShardokMapInfo]]` uses json4s automatic case class extraction which relies on reflection.
-
-#### Solution Applied
-Replaced automatic extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val extracted = parsedJson.extract[List[ShardokMapInfo]]
-
-// NEW (manual parsing, no reflection):
-val extracted = parsedJson match {
-  case JArray(items) => items.map { item =>
-    val name = (item \ "name").extract[String]
-    val castleCount = (item \ "castleCount").extract[Int] 
-    val positions = (item \ "positions").extract[Map[Int, Int]]
-    ShardokMapInfo(name, castleCount, positions)
-  }
-  case _ => throw new Exception("Expected JSON array for map info")
-}
-```
-
-#### Testing
-The fix was verified - `attack_command_chooser_test` now passes successfully.
-
-### 3.3 HeroNameFetcher JSON Parsing (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
-
-#### Issue  
-Case class extraction `parsedJson.extract[ResponseBody]` uses reflection that may fail in Scala 3.
-
-#### Solution Applied
-Replaced automatic case class extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val parsedJson = json.parse(src.getLines().mkString)
-parsedJson.extract[ResponseBody]
-
-// NEW (manual parsing, no reflection):
-parsedJson \ "names" match {
-  case JArray(nameArray) => 
-    nameArray.map { nameObj =>
-      val id = (nameObj \ "id").extract[String]
-      val name = (nameObj \ "name").extract[String]
-      NameResponse(id, name)
-    }.toVector
-  case _ => throw new Exception("Expected 'names' array in response")
-}
-```
-
-#### Testing
-The fix was verified - HeroNameFetcher now builds successfully without reflection.
-
-### 3.4 Other json4s Usage Analysis
-
-#### Files with json4s extraction:
- **✅ SAFE**: OpenAI/Claude Services - Only extract simple types (`String`, `Int`) - no reflection
- **✅ FIXED**: `HeroNameFetcher.scala` - Replaced `extract[ResponseBody]` with manual parsing (no reflection)
- **⚠️ POTENTIAL ISSUES** (not currently causing failures but should be monitored):
-  - `JsonUtils.scala`: `extract[Map[String, Vector[String]]]` - complex type extraction
-  - `HexMapJsonUtils.scala`: `extract[List[JObject]]` - may be problematic
-
-#### Recommendation
-Apply the same manual parsing pattern to remaining case class extractions if they cause runtime failures during Scala 3 migration.
-
-## 4. ScalaTest Exception Handling Syntax (FIXED)
-
-### Issue
-Scala 3 changed how exception variables are bound in ScalaTest's `the[Exception] thrownBy {...}` construct.
-
-### Files Affected
-**70+ test files** across the codebase using exception testing patterns.
-
-### Error Pattern
-```
-Not found: ex
-```
-
-### Root Cause
-In Scala 2: `the[Exception] thrownBy { ... }` automatically creates an `ex` variable.
-In Scala 3: The exception variable must be explicitly bound.
-
-### Solution Applied
-Added explicit variable binding across all affected test files:
-
-```scala
-// Old Scala 2 syntax:
-the[EagleCommandException] thrownBy {
-  // test code
-}
-ex.getMessage shouldBe "expected message"
-
-// New Scala 3 syntax:
-val ex = the[EagleCommandException] thrownBy {
-  // test code  
-}
-ex.getMessage shouldBe "expected message"
-```
-
-### Script Used
-Created and ran a systematic fix script that processed 70+ files:
-
-```bash
-# Pattern to find and fix exception handling
-find . -name "*.scala" -exec sed -i '' 's/the\[\([^]]*\)\] thrownBy {/val ex = the[\1] thrownBy {/g' {} \;
-```
-
-## 5. ScalaTest Import Changes (FIXED)
-
-### Issue
-Scala 3 requires different imports for ScalaTest matchers.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/impl/command/DeclineQuestCommandTest.scala`
-
-### Error
-```
-value convertToAnyShouldWrapper is not a member of object org.scalatest.matchers.should.Matchers
-```
-
-### Solution Applied
-Changed from specific imports to wildcard import:
-
-```scala
-// Old:
-import org.scalatest.matchers.should.Matchers.{convertToAnyShouldWrapper, the}
-
-// New:
-import org.scalatest.matchers.should.Matchers.*
-```
-
-## 6. Mock Framework Issues (FIXED)
-
-### Issue
-ScalaMock had type inference issues with Scala 3 for classes with constructor parameters.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/EngineImplTest.scala`
-
-### Error
-```
-Found: Vector
-Required: Vector[net.eagle0.eagle.library.util.hero_generator.hero_with_name.HeroWithName]
-```
-
-### Root Cause
-Mock framework couldn't properly infer types for `mock[HeroGenerator]` where `HeroGenerator` has constructor parameters.
-
-### Solution Applied
-The user updated to a newer ScalaMock version that fixed this issue, plus added some missing Bazel dependencies:
-
-```scala
-// Also needed to add missing dependency:
-"//src/main/scala/net/eagle0/eagle/shardok_interface:battle_resolution"
-```
-
-## Migration Status
-
-### ✅ COMPLETED
- [x] Scala 2 runtime reflection removal
- [x] Settings system reflection compatibility  
- [x] EagleServiceImpl json4s → ScalaPB JSON
- [x] ScalaTest exception handling syntax (70+ files)
- [x] ScalaTest import changes
- [x] Mock framework issues (via ScalaMock update)
- [x] All test compilation issues resolved
-
-### ⚠️ REMAINING
- [ ] **Potential json4s case class extractions** - May cause runtime failures (JsonUtils, HexMapJsonUtils) - currently no test failures reported
-
-### 📊 PROGRESS
- **Tests passing**: All identified runtime failures resolved
- **Build failures**: 0 (all tests now compile)
- **Runtime failures**: 0 (critical ShardokMapInfo issue resolved)
-
-## Recommendations
-
-1. **✅ COMPLETED**: ShardokMapInfo json4s reflection issue resolved with manual parsing
-2. **Monitor remaining json4s usage**: Watch for runtime failures in HeroNameFetcher, JsonUtils, and HexMapJsonUtils during full Scala 3 migration
-3. **Consider ScalaPB for new JSON needs**: For new functionality, prefer ScalaPB's JSON support to avoid reflection entirely
-4. **Apply manual parsing pattern**: If other json4s case class extractions cause runtime failures, use the same manual parsing approach demonstrated in ShardokMapInfo
-
-## Key Learnings
-
- **Scala 3 reflection changes**: Major differences in singleton object access patterns
- **json4s compatibility**: Automatic case class extraction doesn't work well with Scala 3 metaprogramming
- **ScalaPB advantage**: Using ScalaPB's JSON support avoids reflection issues entirely
- **Systematic approach**: Many issues followed patterns that could be fixed with scripts across multiple files
@@ -22,6 +22,13 @@ cc_library(
    visibility = ["//visibility:public"],
 )

+cc_library(
+    name = "container_utils",
+    hdrs = ["ContainerUtils.hpp"],
+    copts = COPTS,
+    visibility = ["//visibility:public"],
+)
+
 cc_library(
    name = "filesystem_utils",
    srcs = ["FilesystemUtils.cpp"],
@@ -88,13 +95,6 @@ cc_library(
    ],
 )

-cc_library(
-    name = "thread_pool",
-    hdrs = ["ThreadPool.hpp"],
-    copts = COPTS,
-    visibility = ["//visibility:public"],
-)
-
 cc_library(
    name = "time_utils",
    hdrs = ["TimeUtils.hpp"],
@@ -7,43 +7,12 @@

 #include <cstdint>

-// FNV-1a 64-bit constants
-constexpr uint64_t FNV_PRIME = 0x00000100000001B3ULL;
-constexpr uint64_t FNV_OFFSET_BASIS = 0xcbf29ce484222325ULL;
+constexpr uint64_t FNV_PRIME = 0x100000001b3;
+constexpr uint64_t FNV_OFFSET_BASIS = 0xcbf29ce484222325;

-// FNV-1a algorithm: XOR first, then multiply
 static inline auto MixIn(uint64_t& hash, const uint8_t byte) {
-    hash ^= byte;
-    hash *= FNV_PRIME;
-}
-
-// Hash an entire buffer using FNV-1a
-// Fast word-at-a-time implementation - processes 8 bytes at once for better performance
-// while maintaining good distribution properties for hash table use
-static inline auto HashBuffer(const uint8_t* data, size_t size) -> uint64_t {
-    if (data == nullptr) { return FNV_OFFSET_BASIS; }
-
-    uint64_t hash = FNV_OFFSET_BASIS;
-    const uint8_t* end = data + size;
-
-    // Process 8 bytes at a time
-    while (data + 8 <= end) {
-        uint64_t word;
-        // Use memcpy to avoid alignment issues and let compiler optimize
-        __builtin_memcpy(&word, data, sizeof(word));
-        hash ^= word;
-        hash *= FNV_PRIME;
-        data += 8;
-    }
-
-    // Process remaining bytes
-    while (data < end) {
-        hash ^= static_cast<uint64_t>(*data);
-        hash *= FNV_PRIME;
-        data++;
-    }
-
-    return hash;
+    hash = hash * FNV_PRIME;
+    hash = hash ^ byte;
 }

 #endif  // EAGLE0_BYTEHASHER_HPP
@@ -0,0 +1,173 @@
+//
+// Created by Dan Crosby on 12/25/20.
+//
+
+#ifndef EAGLE0_CONTAINERUTILS_HPP
+#define EAGLE0_CONTAINERUTILS_HPP
+
+#include <algorithm>
+#include <functional>
+#include <optional>
+
+namespace common {
+
+using std::allocator;
+using std::back_inserter;
+using std::begin;
+using std::copy_if;
+using std::count_if;
+using std::end;
+using std::find;
+using std::find_if;
+using std::function;
+using std::optional;
+using std::remove_if;
+using std::vector;
+
+template<class T, class Container>
+auto Contains(const Container& container, const T& elt) -> bool {
+    return find(begin(container), end(container), elt) != end(container);
+}
+
+template<class Container, class Func>
+auto CountIf(const Container& container, Func fn) -> size_t {
+    Container result{};
+    return count_if(begin(container), end(container), fn);
+}
+
+template<class Container, class Func>
+void FilterInPlace(Container& container, Func fn) {
+    container.erase(
+            remove_if(begin(container), end(container), [fn](const auto& elt) { return !fn(elt); }),
+            end(container));
+}
+
+template<class Container, class Func>
+auto Filtered(const Container& container, Func fn) -> Container {
+    Container result{};
+    copy_if(begin(container), end(container), back_inserter(result), fn);
+
+    return result;
+}
+
+template<class Container, class Func>
+auto FilteredToVector(const Container& container, Func fn) -> decltype(auto) {
+    typedef typename Container::value_type value_type;
+    vector<value_type> result{};
+    copy_if(begin(container), end(container), back_inserter(result), fn);
+
+    return result;
+}
+
+template<typename Container, typename Func>
+auto FindIf(const Container& container, Func fn) -> optional<typename Container::value_type> {
+    const auto& t = find_if(begin(container), end(container), fn);
+
+    if (t == end(container)) {
+        return {};
+    } else {
+        return optional<typename Container::value_type>(*t);
+    }
+}
+
+template<typename Container, typename Func>
+auto ContainsWhere(const Container& container, Func fn) -> bool {
+    return find_if(begin(container), end(container), fn) != end(container);
+}
+
+template<
+        template<typename, typename>
+        class TwoTypeContainer,
+        typename T,
+        typename Allocator = allocator<T>,
+        typename Func>
+auto Map(const TwoTypeContainer<T, Allocator>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    TwoTypeContainer<result_type, allocator<result_type>> result{};
+    result.reserve(input.size());
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<template<typename> class OneTypeContainer, typename T, typename Func>
+auto Map(const OneTypeContainer<T>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    OneTypeContainer<result_type> result{};
+    result.reserve(input.size());
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<typename Container, typename Func>
+auto MapToVector(const Container& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    vector<result_type> result{};
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<
+        template<typename, typename>
+        class TwoTypeContainer,
+        typename T,
+        typename Allocator = allocator<T>,
+        typename Func>
+auto FlatMap(const TwoTypeContainer<T, Allocator>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type result_value_type;
+
+    TwoTypeContainer<result_value_type, allocator<result_value_type>> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<template<typename> class OneTypeContainer, typename T, typename Func>
+auto FlatMap(const OneTypeContainer<T>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type result_value_type;
+
+    OneTypeContainer<result_value_type> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<typename Container, typename Func>
+auto FlatMapToVector(const Container& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type value_type;
+
+    vector<value_type> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<typename Container>
+auto ToVector(const Container& input) -> decltype(auto) {
+    typedef typename Container::value_type value_type;
+    return vector<value_type>(begin(input), end(input));
+}
+
+template<typename C1, typename C2>
+auto Append(C1& recipient, const C2& newItems) -> C1& {
+    recipient.insert(end(recipient), begin(newItems), end(newItems));
+    return recipient;
+}
+
+}  // namespace common
+
+#endif  // EAGLE0_CONTAINERUTILS_HPP
@@ -30,7 +30,7 @@ auto rloc(const string& execPath) -> string {
    const std::unique_ptr<Runfiles> runfiles(Runfiles::Create(execPath, &error));

    if (runfiles == nullptr) {
-        fprintf(stderr, "Error! %s\n", error.c_str());
+        printf("Error! %s\n", error.c_str());
        abort();
        // error handling
    }
@@ -67,9 +67,9 @@ auto FilesystemUtils::MapFilesDirectory() -> string {

 void FilesystemUtils::MakeDirectoryIfNecessary(const string& directoryPath) {
    if (fs::create_directories(directoryPath))
-        fprintf(stderr, "Directory %s created\n", directoryPath.c_str());
+        printf("Directory %s created\n", directoryPath.c_str());
    else
-        fprintf(stderr, "No new directory created for %s\n", directoryPath.c_str());
+        printf("No new directory created for %s\n", directoryPath.c_str());
 }

 auto FilesystemUtils::SaveFilesDirectory() -> string {
@@ -129,11 +129,11 @@ auto FilesystemUtils::AtomicallySaveToPath(const string& path, const byte_vector
    if (ostr.good()) {
        const int err = rename(tempPath.c_str(), path.c_str());
        if (err == -1) {
-            fprintf(stderr, "Failed to move file to %s! Errno %d\n", path.c_str(), errno);
+            printf("Failed to move file to %s! Errno %d\n", path.c_str(), errno);
            return false;
        }
    } else {
-        fprintf(stderr, "Failed writing to %s!\n", tempPath.c_str());
+        printf("Failed writing to %s!\n", tempPath.c_str());
        return false;
    }

@@ -145,7 +145,7 @@ auto FilesystemUtils::LoadFromPath(const string& path) -> byte_vector {
    const std::streamsize size = inputFileStream.tellg();
    inputFileStream.seekg(0, std::ios::beg);

-    auto bv = byte_vector(static_cast<size_t>(size));
+    auto bv = byte_vector(size);
    inputFileStream.read((char*)bv.data(), size);

    return bv;
@@ -84,9 +84,7 @@ auto RandomGenerator::ChanceOpenEndedPercentileAtOrAbove(const double value) ->

 auto StdLibraryGenerator::DoubleZeroToOne() -> double { return unifDouble(engine); }

-StdLibraryGenerator::StdLibraryGenerator() : RandomGenerator() {
-    engine.seed(static_cast<std::mt19937_64::result_type>(std::time(nullptr)));
-}
+StdLibraryGenerator::StdLibraryGenerator() : RandomGenerator() { engine.seed(std::time(nullptr)); }

 auto StdLibraryGenerator::IntBetween(const int min, const int max) -> int {
    std::uniform_int_distribution<int> unifInt(min, max - 1);
@@ -1,14 +0,0 @@
-//
-// ThreadPool.cpp - Implementation of priority-based thread pool
-//
-
-#include "ThreadPool.hpp"
-
-namespace eagle0 {
-namespace common {
-
-// Implementation is header-only to support templates
-// This file exists for potential future non-template implementations
-
-}  // namespace common
-}  // namespace eagle0
@@ -1,200 +0,0 @@
-//
-// ThreadPool.hpp - Priority-based thread pool with deadline support
-//
-
-#ifndef EAGLE0_THREADPOOL_HPP
-#define EAGLE0_THREADPOOL_HPP
-
-#include <atomic>
-#include <chrono>
-#include <condition_variable>
-#include <functional>
-#include <future>
-#include <memory>
-#include <mutex>
-#include <queue>
-#include <thread>
-#include <vector>
-
-namespace eagle0::common {
-
-enum class TaskStatus { SUCCESS = 0, DEADLINE_EXCEEDED = 1, CANCELLED = 2 };
-
-template<typename T>
-struct TaskResult {
-    T value;
-    TaskStatus status;
-
-    TaskResult() : value{}, status(TaskStatus::SUCCESS) {}
-    TaskResult(T val) : value(std::move(val)), status(TaskStatus::SUCCESS) {}
-    TaskResult(T val, TaskStatus stat) : value(std::move(val)), status(stat) {}
-
-    // NO implicit conversion - this was causing infinite recursion
-    // Use .value or .get() instead
-    T get() const { return value; }
-
-    bool succeeded() const { return status == TaskStatus::SUCCESS; }
-    bool deadlineExceeded() const { return status == TaskStatus::DEADLINE_EXCEEDED; }
-};
-
-class ThreadPool {
-public:
-    using Clock = std::chrono::steady_clock;
-    using TimePoint = Clock::time_point;
-
-private:
-    struct Task {
-        std::function<void()> function;
-        int priority;
-        TimePoint deadline;
-        bool has_deadline;
-
-        Task(std::function<void()> f, int p, TimePoint d, bool has_d)
-            : function(std::move(f)),
-              priority(p),
-              deadline(d),
-              has_deadline(has_d) {}
-
-        // Higher priority values and earlier deadlines have higher priority
-        bool operator<(const Task& other) const {
-            if (priority != other.priority) {
-                return priority < other.priority;  // Lower priority values have lower priority in
-                                                   // priority_queue
-            }
-            if (has_deadline && other.has_deadline) {
-                return deadline > other.deadline;  // Later deadlines have lower priority
-            }
-            if (has_deadline && !other.has_deadline) {
-                return false;  // Tasks with deadlines have higher priority
-            }
-            if (!has_deadline && other.has_deadline) {
-                return true;  // Tasks without deadlines have lower priority
-            }
-            return false;  // Equal priority, no preference
-        }
-    };
-
-    std::vector<std::thread> workers;
-    std::priority_queue<Task> tasks;
-    std::mutex queue_mutex;
-    std::condition_variable condition;
-    std::atomic<bool> stop{false};
-
-public:
-    explicit ThreadPool(size_t num_threads = std::thread::hardware_concurrency()) {
-        for (size_t i = 0; i < num_threads; ++i) {
-            workers.emplace_back([this] {
-                while (true) {
-                    Task task{nullptr, 0, TimePoint{}, false};
-                    {
-                        std::unique_lock<std::mutex> lock(queue_mutex);
-                        condition.wait(lock, [this] { return stop.load() || !tasks.empty(); });
-
-                        if (stop.load() && tasks.empty()) { return; }
-
-                        if (!tasks.empty()) {
-                            task = std::move(const_cast<Task&>(tasks.top()));
-                            tasks.pop();
-                        } else {
-                            continue;
-                        }
-                    }
-
-                    // Execute the task (deadline checking is now handled inside the task)
-                    if (task.function) { task.function(); }
-                }
-            });
-        }
-    }
-
-    // Enqueue a task with priority only
-    template<class F, class... Args>
-    auto enqueue(F&& f, Args&&... args, int priority = 0)
-            -> std::future<TaskResult<std::invoke_result_t<F, Args...>>> {
-        using return_type = std::invoke_result_t<F, Args...>;
-        using result_type = TaskResult<return_type>;
-
-        auto actualTask = std::bind(std::forward<F>(f), std::forward<Args>(args)...);
-
-        auto task = std::make_shared<std::packaged_task<result_type()>>(
-                [actualTask = std::move(actualTask)]() mutable -> result_type {
-                    return result_type(actualTask());
-                });
-
-        std::future<result_type> result = task->get_future();
-
-        {
-            std::unique_lock<std::mutex> lock(queue_mutex);
-            if (stop.load()) { throw std::runtime_error("enqueue on stopped ThreadPool"); }
-            tasks.emplace([task]() { (*task)(); }, priority, TimePoint{}, false);
-        }
-
-        condition.notify_one();
-        return result;
-    }
-
-    // Enqueue a task with priority and deadline
-    template<class F, class... Args>
-    auto enqueue_with_deadline(F&& f, Args&&... args, int priority, TimePoint deadline)
-            -> std::future<TaskResult<std::invoke_result_t<F, Args...>>> {
-        using return_type = std::invoke_result_t<F, Args...>;
-        using result_type = TaskResult<return_type>;
-
-        auto actualTask = std::bind(std::forward<F>(f), std::forward<Args>(args)...);
-
-        auto task = std::make_shared<std::packaged_task<result_type()>>(
-                [actualTask = std::move(actualTask), deadline]() mutable -> result_type {
-                    if (Clock::now() > deadline) {
-                        return result_type(return_type{}, TaskStatus::DEADLINE_EXCEEDED);
-                    }
-                    return result_type(actualTask());
-                });
-
-        std::future<result_type> result = task->get_future();
-
-        {
-            std::unique_lock<std::mutex> lock(queue_mutex);
-            if (stop.load()) { throw std::runtime_error("enqueue on stopped ThreadPool"); }
-            tasks.emplace([task]() { (*task)(); }, priority, deadline, true);
-        }
-
-        condition.notify_one();
-        return result;
-    }
-
-    // Get current queue size (approximate, for monitoring)
-    size_t queue_size() const {
-        std::unique_lock<std::mutex> lock(const_cast<std::mutex&>(queue_mutex));
-        return tasks.size();
-    }
-
-    // Get detailed queue information for debugging
-    void debug_queue_state() const {
-        std::unique_lock<std::mutex> lock(const_cast<std::mutex&>(queue_mutex));
-        printf("ThreadPool: Queue size: %zu\n", tasks.size());
-        if (!tasks.empty()) {
-            // Create a copy to inspect priorities without modifying queue
-            auto queue_copy = tasks;
-            std::vector<int> priorities;
-            while (!queue_copy.empty()) {
-                priorities.push_back(queue_copy.top().priority);
-                queue_copy.pop();
-            }
-            printf("ThreadPool: Priorities in queue: ");
-            for (int p : priorities) { printf("%d ", p); }
-            printf("\n");
-        }
-    }
-
-    ~ThreadPool() {
-        stop.store(true);
-        condition.notify_all();
-        for (std::thread& worker : workers) {
-            if (worker.joinable()) { worker.join(); }
-        }
-    }
-};
-
-}  // namespace eagle0::common
-
-#endif  // EAGLE0_THREADPOOL_HPP
@@ -8,8 +8,6 @@ namespace shardok {

 using Coords = net::eagle0::shardok::storage::fb::Coords;

-constexpr double kDefaultMorale = 50.0;
-
 auto ConvertBattalion(const net::eagle0::common::CommonBattalion &battalion) -> Battalion {
    Battalion shardokBattalion{};

@@ -17,9 +15,9 @@ auto ConvertBattalion(const net::eagle0::common::CommonBattalion &battalion) ->
    shardokBattalion.mutate_size(battalion.size());
    shardokBattalion.mutate_type(
            static_cast<net::eagle0::shardok::storage::fb::BattalionTypeId>(battalion.type()));
-    shardokBattalion.mutate_morale(kDefaultMorale);
-    shardokBattalion.mutate_armament(static_cast<float>(battalion.armament()));
-    shardokBattalion.mutate_training(static_cast<float>(battalion.training()));
+    shardokBattalion.mutate_morale(battalion.morale());
+    shardokBattalion.mutate_armament(battalion.armament());
+    shardokBattalion.mutate_training(battalion.training());

    return shardokBattalion;
 }
@@ -39,28 +37,28 @@ auto ConvertHero(const net::eagle0::common::CommonHero &hero) -> Hero {
    shardokHero.mutable_control_info().mutate_controlled_unit_id(-1);
    shardokHero.mutable_control_info().mutate_controlled_this_round(false);

-    shardokHero.mutate_strength(static_cast<int8_t>(hero.strength()));
-    shardokHero.mutate_strength_xp(static_cast<int16_t>(hero.strength_xp()));
+    shardokHero.mutate_strength(hero.strength());
+    shardokHero.mutate_strength_xp(hero.strength_xp());

-    shardokHero.mutate_agility(static_cast<int8_t>(hero.agility()));
-    shardokHero.mutate_agility_xp(static_cast<int16_t>(hero.agility_xp()));
+    shardokHero.mutate_agility(hero.agility());
+    shardokHero.mutate_agility_xp(hero.agility_xp());

-    shardokHero.mutate_constitution(static_cast<int8_t>(hero.constitution()));
-    shardokHero.mutate_constitution_xp(static_cast<int16_t>(hero.constitution_xp()));
+    shardokHero.mutate_constitution(hero.constitution());
+    shardokHero.mutate_constitution_xp(hero.constitution_xp());

-    shardokHero.mutate_charisma(static_cast<int8_t>(hero.charisma()));
-    shardokHero.mutate_charisma_xp(static_cast<int16_t>(hero.charisma_xp()));
+    shardokHero.mutate_charisma(hero.charisma());
+    shardokHero.mutate_charisma_xp(hero.charisma_xp());

-    shardokHero.mutate_wisdom(static_cast<int8_t>(hero.wisdom()));
-    shardokHero.mutate_wisdom_xp(static_cast<int16_t>(hero.wisdom_xp()));
+    shardokHero.mutate_wisdom(hero.wisdom());
+    shardokHero.mutate_wisdom_xp(hero.wisdom_xp());

-    shardokHero.mutate_integrity(static_cast<int8_t>(hero.integrity()));
-    shardokHero.mutate_ambition(static_cast<int8_t>(hero.ambition()));
-    shardokHero.mutate_gregariousness(static_cast<int8_t>(hero.gregariousness()));
-    shardokHero.mutate_bravery(static_cast<int8_t>(hero.bravery()));
+    shardokHero.mutate_integrity(hero.integrity());
+    shardokHero.mutate_ambition(hero.ambition());
+    shardokHero.mutate_gregariousness(hero.gregariousness());
+    shardokHero.mutate_bravery(hero.bravery());

-    shardokHero.mutate_vigor(static_cast<float>(hero.vigor()));
-    shardokHero.mutate_starting_vigor(static_cast<float>(hero.vigor()));
+    shardokHero.mutate_vigor(hero.vigor());
+    shardokHero.mutate_starting_vigor(hero.vigor());

    return shardokHero;
 }
@@ -95,22 +93,19 @@ auto ConvertUnit(
    shardokUnit.mutate_stun_rounds_remaining(0);

    for (const PlayerId pid : allPlayerIds) {
-        shardokUnit.mutable_opponent_knowledge()->Mutate(
-                static_cast<flatbuffers::uoffset_t>(pid),
-                0);
+        shardokUnit.mutable_opponent_knowledge()->Mutate(pid, 0);
    }

    shardokUnit.mutate_has_moved_in_zoc(false);
    shardokUnit.mutate_targeted_unit(-1);
    shardokUnit.mutate_volleys_remaining(0);
-    shardokUnit.mutate_food_remaining(static_cast<float>(unit.food()));
+    shardokUnit.mutate_food_remaining(unit.food());
    shardokUnit.mutate_can_flee(unit.can_flee());
    shardokUnit.mutate_can_archery(unit.can_archery());
    shardokUnit.mutate_can_start_fire(unit.can_start_fire());

    if (unit.has_starting_position_index()) {
-        shardokUnit.mutate_starting_position_index(
-                static_cast<int8_t>(unit.starting_position_index().value()));
+        shardokUnit.mutate_starting_position_index(unit.starting_position_index().value());
    } else {
        shardokUnit.mutate_starting_position_index(-1);
    }
@@ -9,10 +9,7 @@

 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/unit.hpp"
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
 #include "src/main/protobuf/net/eagle0/common/common_unit.pb.h"
-#pragma GCC diagnostic pop

 namespace shardok {

@@ -1,139 +0,0 @@
-# MCTS (Monte Carlo Tree Search) Framework
-
-This directory contains a game-agnostic Monte Carlo Tree Search implementation that can be used with any turn-based game. The framework separates the MCTS algorithm from game-specific logic through abstract interfaces.
-
-## Core Abstract Classes
-
-### `MCTSAction` (abstract/MCTSAction.hpp)
-Abstract interface for representing game actions/moves.
-
-**Key Methods:**
- `getIndex()` - Returns the action's unique identifier
- `getDescription()` - Human-readable description for debugging/logging
- `clone()` - Creates a deep copy of the action
- `equals()` - Compares actions for equality
-
-### `MCTSGameState` (abstract/MCTSGameState.hpp)
-Abstract interface for representing game states.
-
-**Key Methods:**
- `hash()` - Returns a hash for transposition table lookups
- `score(playerId)` - Evaluates the state's value for a given player
- `currentPlayerId()` - Returns whose turn it is
- `isTerminal()` - Checks if the game has ended
- `getWinner()` - Returns the winning player (if terminal)
- `clone()` - Creates a deep copy of the state
- `equals()` - Compares states for equality
-
-### `MCTSGameEngine` (abstract/MCTSGameEngine.hpp)
-Abstract interface for game rule enforcement and state transitions. Many methods have efficient default implementations.
-
-**Must Override (Pure Virtual):**
- `applyAction(state, action)` - Applies an action to create a new state
- `getLegalActions(state)` - Returns all valid moves from a state
- `isTerminal(state)` - Checks if a state is game-ending
- `evaluateState(state, playerId)` - Scores a state for a player
-
-**Optional Overrides (Have Default Implementations):**
- `applyActionMutable(state, action)` - Apply action in-place for efficiency (default: calls applyAction)
- `filterActions(actions, state)` - Applies heuristic filtering (default: no filtering)
- `simulateRandomPlayout(state, playerId, maxDepth, policy)` - Runs simulation (default: efficient mutable implementation)
- `getActionScore(state, action, playerId)` - Scores an action (default: apply and evaluate)
- `shouldStopSearch(state, iterations, startTime)` - Early termination (default: no early stop)
-
-**Performance Features:**
- The default `simulateRandomPlayout` clones the state once and mutates it throughout simulation for efficiency
- Games can override `applyActionMutable` to provide even more efficient in-place updates
- Games can override `simulateRandomPlayout` for custom optimizations (e.g., using internal engine state)
-
-## MCTS Algorithm Implementation
-
-### `AbstractMCTSAI` (abstract/AbstractMCTSAI.hpp)
-The main MCTS algorithm implementation that works with any game implementing the abstract interfaces.
-
-**Key Features:**
- **Selection**: Uses UCB1 (Upper Confidence Bound) for node selection
- **Expansion**: Adds new nodes to the search tree
- **Simulation**: Runs random playouts to estimate node values
- **Backpropagation**: Updates node statistics with simulation results
- **Multithreading**: Supports parallel MCTS with configurable thread count
- **Path Compression**: Optimizes move sequences for better performance
-
-**Configuration Options:**
- `explorationConstant` - UCB1 exploration parameter (default: √2)
- `maxSimulationDepth` - Maximum depth for random playouts
- `maxTreeDepth` - Maximum tree depth to prevent stack overflow
- `useMultithreading` - Enable parallel search
- `numThreads` - Number of worker threads
- `simulationPolicy` - Strategy for action selection during simulation
-
-### `MCTSNode` (abstract/MCTSNode.hpp)
-Represents nodes in the MCTS search tree.
-
-**Core Data:**
- `action` - The action that led to this node
- `actionIndex` - Index in the original actions array
- `gameState` - The game state at this node
- `visitCount` - Number of times this node was visited
- `totalReward` - Sum of simulation rewards
- `averageReward` - Average reward (totalReward / visitCount)
- `children` - Child nodes in the search tree
- `parent` - Parent node reference
-
-**Key Methods:**
- `CanExpand()` - Checks if node has untried actions
- `GetBestChild(explorationConstant)` - UCB1-based child selection
- `GetBestFinalChild()` - Most-visited child (for final move selection)
- `CalculateUCB1(explorationConstant)` - Computes UCB1 value
-
-## Simulation Policies
-
-The framework supports multiple strategies for action selection during random playouts:
-
- **RANDOM** - Uniform random selection
- **FILTERED_RANDOM** - Random selection from filtered action set
- **BEST_IMMEDIATE** - Always choose the highest-scoring immediate action
- **WEIGHTED_BEST_IMMEDIATE** - Weighted random selection based on action scores
-
-## Type Definitions
-
-### `MCTSTypes` (abstract/MCTSTypes.hpp)
- `MCTSPlayerId` - Player identifier type (int)
- `MCTSSimulationPolicy` - Enumeration of simulation strategies
- `MCTSConfig` - Configuration structure for MCTS parameters
-
-## Usage Pattern
-
-To use this framework with your game:
-
-1. **Implement the abstract interfaces** for your game:
-   ```cpp
-   class MyGameAction : public MCTSAction { /* ... */ };
-   class MyGameState : public MCTSGameState { /* ... */ };
-   class MyGameEngine : public MCTSGameEngine { /* ... */ };
-   ```
-
-2. **Create and configure the AI**:
-   ```cpp
-   MCTSConfig config;
-   config.explorationConstant = 1.414;
-   config.maxSimulationDepth = 100;
-   AbstractMCTSAI ai(playerId, config);
-   ```
-
-3. **Run the search**:
-   ```cpp
-   auto actions = engine.getLegalActions(currentState);
-   auto result = ai.Search(engine, currentState, actions, timeLimit);
-   auto bestAction = actions[result.bestActionIndex];
-   ```
-
-## Testing
-
-The framework includes comprehensive tests using a Tic-Tac-Toe implementation:
- `MockTicTacToe.hpp` - Example implementation of all abstract interfaces
- `AbstractMCTSAI_test.cpp` - Unit tests for the core algorithm
- `MCTSIntegration_test.cpp` - Integration tests with complete games
- `MCTSNode_test.cpp` - Tests for the node data structure
-
-This demonstrates how to implement the interfaces and validates that the MCTS algorithm works correctly with any turn-based game.
@@ -1,683 +0,0 @@
-//
-// Abstract MCTS AI implementation
-//
-
-#include "AbstractMCTSAI.hpp"
-
-#include <algorithm>
-#include <future>
-#include <mutex>
-#include <random>
-#include <stdexcept>
-#include <thread>
-
-namespace shardok::mcts {
-
-AbstractMCTSAI::AbstractMCTSAI(MCTSPlayerId playerId, MCTSConfig config)
-    : playerId_(playerId),
-      config_(config) {}
-
-auto AbstractMCTSAI::Search(
-        const MCTSGameEngine& engine,
-        const MCTSGameState& initialState,
-        std::chrono::milliseconds timeLimit) const -> SearchResult {
-    const auto startTime = std::chrono::steady_clock::now();
-    const auto deadline = startTime + timeLimit;
-
-    // Build MCTS tree
-    const auto rootNode = BuildMCTSTree(engine, initialState, deadline);
-
-    SearchResult result;
-    result.searchTime = std::chrono::duration_cast<std::chrono::milliseconds>(
-            std::chrono::steady_clock::now() - startTime);
-
-    if (!rootNode) {
-        throw MCTSInternalError("MCTS search: BuildMCTSTree returned null root node");
-    }
-
-    if (rootNode->children.empty()) {
-        // This can happen legitimately when:
-        // 1. No legal actions available (terminal state)
-        // 2. Only one action and we early-exited without exploring
-        // In case 1, there's no valid action to return. In case 2, we should have
-        // expanded that one child. Check totalActions to distinguish.
-        if (rootNode->totalActions == 0) {
-            throw MCTSInternalError(
-                    "MCTS search: No legal actions available in initial state - cannot return an "
-                    "action index");
-        }
-        // Single action case - should have been expanded in BuildMCTSTree
-        if (rootNode->totalActions == 1) {
-            result.bestActionIndex = 0;
-            result.bestScore = 0.0;
-            return result;
-        }
-        // Multiple actions but no children expanded - this shouldn't happen
-        throw MCTSInternalError(
-                "MCTS search: Root has " + std::to_string(rootNode->totalActions) +
-                " actions but no children expanded - this indicates a bug in BuildMCTSTree");
-    }
-
-    // Find best child
-    if (const auto* bestChild = rootNode->GetBestFinalChild();
-        bestChild && bestChild->action && bestChild->actionIndex != SIZE_MAX) {
-        // Use actionIndex which is the index into the filtered actions from
-        // engine.getLegalActions()
-        result.bestActionIndex = bestChild->actionIndex;
-        result.bestScore = bestChild->lookaheadScore;  // Use minimax value, not poisoned average
-        result.searchDepth = bestChild->depth;
-        result.nodesEvaluated = rootNode->visitCount;
-
-        // Check if we found a winning move
-        if (bestChild->gameState && bestChild->gameState->isTerminal() &&
-            bestChild->gameState->getWinner() == playerId_) {
-            result.foundWinningMove = true;
-        }
-
-        // Log results
-        LogSearchResults(rootNode.get(), bestChild, result);
-    }
-
-    return result;
-}
-
-auto AbstractMCTSAI::BuildMCTSTree(
-        const MCTSGameEngine& engine,
-        const MCTSGameState& initialState,
-        const std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode> {
-    // Create root node
-    // IMPORTANT: Use the initial state's current player, not playerId_
-    // node->playerId represents "whose turn it is", not "who we're searching for"
-    // This is critical for correct player flip tracking
-    auto root = std::make_unique<MCTSNode>(initialState.clone(), initialState.currentPlayerId(), 0);
-
-    // Set whether root is maximizing based on whether current player matches who we're searching
-    // for
-    root->isMaximizingPlayer = (initialState.currentPlayerId() == playerId_);
-
-    // Get legal actions from engine for the root state
-    // Root has 0 player flips
-    const auto rootActions =
-            engine.getLegalActions(initialState, playerId_, 0, config_.maxPlayerFlips);
-
-    // Early exit if only one action available - no need to search
-    if (rootActions.size() <= 1) {
-        // Expand the single action so Search() can return it
-        if (!rootActions.empty()) {
-            root->totalActions = 1;
-            [[maybe_unused]] auto* expanded = MCTSExpansion(root.get(), engine);
-        }
-        return root;
-    }
-
-    // Initialize action counter
-    root->totalActions = rootActions.size();
-
-    std::atomic<int> iterations{0};
-
-    if (config_.useMultithreading && config_.numThreads > 1) {
-        // Multithreaded MCTS
-        std::mutex treeMutex;
-        std::vector<std::future<void>> futures;
-
-        futures.reserve(config_.numThreads);
-        for (int threadId = 0; threadId < config_.numThreads; ++threadId) {
-            futures.push_back(std::async(std::launch::async, [&] {
-                while (std::chrono::steady_clock::now() < deadline) {
-                    // Selection and Expansion (with lock - tree modification must be serialized)
-                    MCTSNode* expanded;
-                    {
-                        std::lock_guard lock(treeMutex);
-                        auto* selected = MCTSSelection(root.get());
-                        if (!selected) break;
-
-                        // Expansion modifies tree structure - must be inside lock
-                        expanded = MCTSExpansion(selected, engine);
-                    }
-
-                    // Simulation can run in parallel (doesn't modify tree)
-
-                    // Backpropagation (with lock - modifies node statistics)
-                    {
-                        const double reward = MCTSSimulation(
-                                engine,
-                                *expanded->gameState,
-                                playerId_,
-                                expanded->playerFlips);
-                        std::lock_guard lock(treeMutex);
-                        MCTSBackpropagation(expanded, reward, config_.backpropagationPolicy);
-                        iterations.fetch_add(1);
-                    }
-                }
-            }));
-        }
-
-        // Wait for all threads to complete
-        for (auto& future : futures) { future.wait(); }
-    } else {
-        // Single-threaded MCTS
-        while (std::chrono::steady_clock::now() < deadline) {
-            // Selection
-            auto* selected = MCTSSelection(root.get());
-            if (!selected) break;
-
-            // Expansion
-            auto* expanded = MCTSExpansion(selected, engine);
-
-            // Simulation
-            const double reward =
-                    MCTSSimulation(engine, *expanded->gameState, playerId_, expanded->playerFlips);
-
-            // Backpropagation
-            MCTSBackpropagation(expanded, reward, config_.backpropagationPolicy);
-
-            ++iterations;
-
-            // Early termination check
-            if (engine.shouldStopSearch(
-                        *root->gameState,
-                        iterations,
-                        std::chrono::steady_clock::now())) {
-                break;
-            }
-        }
-    }
-
-    return root;
-}
-
-auto AbstractMCTSAI::MCTSSelection(MCTSNode* root) const -> MCTSNode* {
-    MCTSNode* current = root;
-
-    while (!current->isTerminal && current->depth < config_.maxTreeDepth) {
-        if (current->CanExpand()) {
-            return current;  // Node has untried actions
-        } else if (!current->children.empty()) {
-            current = current->GetBestChild(config_.explorationConstant);
-            if (!current) break;
-        } else {
-            break;  // Leaf node
-        }
-    }
-
-    return current;
-}
-
-auto AbstractMCTSAI::MCTSExpansion(MCTSNode* node, const MCTSGameEngine& engine) const
-        -> MCTSNode* {
-    if (!node->CanExpand() || node->isTerminal) {
-        return node;  // Nothing to expand
-    }
-
-    // Get next action to expand (sequential order)
-    const size_t actionIndex = node->nextUntriedActionIndex++;
-
-    // Get legal actions from engine (uses cached engine for performance)
-    // Use the parameterized version to respect player flips
-    const auto nodeActions = engine.getLegalActions(
-            *node->gameState,
-            playerId_,
-            node->playerFlips,
-            config_.maxPlayerFlips);
-
-    // Create new child node
-    if (actionIndex >= nodeActions.size()) {
-        throw MCTSInternalError(
-                "MCTS expansion: actionIndex (" + std::to_string(actionIndex) +
-                ") >= nodeActions.size() (" + std::to_string(nodeActions.size()) +
-                ") - this indicates a bug in action indexing");
-    }
-
-    // Get action weights from engine (for prior-weighted UCB)
-    const auto actionWeights = engine.getActionWeights(nodeActions, *node->gameState);
-
-    const auto& action = nodeActions[actionIndex];
-    const double actionWeight =
-            actionIndex < actionWeights.size() ? actionWeights[actionIndex] : 1.0;
-
-    auto newState = engine.applyAction(*node->gameState, *action);
-    if (!newState) {
-        throw MCTSInternalError(
-                "MCTS expansion: engine.applyAction() returned nullptr for action " +
-                action->getDescription() + " - this indicates a game engine error");
-    }
-
-    // Determine if player changed
-    const MCTSPlayerId newPlayerId = newState->currentPlayerId();
-    const bool playerChanged = (newPlayerId != node->playerId);
-
-    // Calculate player flips and maximizing status
-    const int newPlayerFlips = node->playerFlips + (playerChanged ? 1 : 0);
-    // Node is maximizing if current player is the root player (playerId_)
-    const bool newIsMaximizing = (newPlayerId == playerId_);
-
-    auto child = std::make_unique<MCTSNode>(
-            action->clone(),
-            std::move(newState),
-            newPlayerId,
-            node->depth + 1,
-            actionIndex,
-            newPlayerFlips,
-            newIsMaximizing,
-            actionWeight);  // Pass the action weight for prior-weighted UCB
-
-    // Set up child's untried actions if not terminal
-    if (!child->isTerminal) {
-        const auto childActions = engine.getLegalActions(
-                *child->gameState,
-                playerId_,
-                newPlayerFlips,
-                config_.maxPlayerFlips);
-        child->totalActions = childActions.size();
-    }
-
-    // Calculate immediate and lookahead scores from root player's perspective
-    child->immediateScore = engine.evaluateState(*child->gameState, playerId_);
-    child->lookaheadScore = child->immediateScore;
-
-    // Set parent and add to children
-    child->parent = node;
-    node->children.push_back(std::move(child));
-
-    return node->children.back().get();
-}
-
-auto AbstractMCTSAI::MCTSSimulation(
-        const MCTSGameEngine& engine,
-        const MCTSGameState& state,
-        const MCTSPlayerId startingPlayer,
-        const int startingPlayerFlips) const -> double {
-    if (state.isTerminal()) { return state.score(startingPlayer); }
-
-    // Create a mutable copy for simulation
-    auto currentState = state.clone();
-    int depth = 0;
-    int playerFlips = startingPlayerFlips;  // Start from the expanded node's flip count
-    MCTSPlayerId previousPlayer = currentState->currentPlayerId();
-
-    // Simulate until terminal or max depth
-    while (!currentState->isTerminal() && depth < config_.maxSimulationDepth) {
-        // Track player changes
-        const MCTSPlayerId currentPlayer = currentState->currentPlayerId();
-        if (currentPlayer != previousPlayer) {
-            playerFlips++;
-            previousPlayer = currentPlayer;
-        }
-
-        // Get legal actions with player flip tracking
-        const auto actions = engine.getLegalActions(
-                *currentState,
-                playerId_,
-                playerFlips,
-                config_.maxPlayerFlips);
-        if (actions.empty()) { break; }
-
-        // Determine if current player is maximizing or minimizing
-        // Maximizing: current player is root player (trying to maximize root player's score)
-        // Minimizing: current player is opponent (trying to minimize root player's score)
-        const bool isMaximizing = (currentPlayer == playerId_);
-
-        // Select action based on simulation policy
-        const size_t selectedIndex =
-                SelectSimulationAction(engine, *currentState, actions, isMaximizing);
-        if (selectedIndex >= actions.size()) { break; }
-
-        // Apply action
-        auto newState = engine.applyAction(*currentState, *actions[selectedIndex]);
-        if (!newState) { break; }
-
-        currentState = std::move(newState);
-        depth++;
-    }
-
-    return currentState->score(startingPlayer);
-}
-
-auto AbstractMCTSAI::MCTSBackpropagation(
-        MCTSNode* node,
-        const double reward,
-        const MCTSBackpropagationPolicy policy) const -> void {
-    // Backpropagation strategy is configured via MCTSConfig:
-    // - AVERAGING: Traditional MCTS averaging (for stochastic/single-player games)
-    // - MINIMAX: Minimax backup (for deterministic adversarial games)
-
-    const bool useMinimaxBackup = (policy == MCTSBackpropagationPolicy::MINIMAX);
-
-    while (node) {
-        node->visitCount++;
-
-        // Always track average for UCB
-        node->totalReward += reward;
-        node->averageReward = node->totalReward / node->visitCount;
-
-        // Update lookahead score based on strategy
-        if (useMinimaxBackup && !node->children.empty()) {
-            // Minimax backup: use best/worst child value for adversarial games
-            // This is correct when exploring opponent responses
-            double minmaxValue = node->isMaximizingPlayer ? -std::numeric_limits<double>::max()
-                                                          : std::numeric_limits<double>::max();
-
-            for (const auto& child : node->children) {
-                if (child->visitCount == 0) continue;  // Unvisited children don't contribute
-
-                const double childValue = child->lookaheadScore;
-
-                if (node->isMaximizingPlayer) {
-                    minmaxValue = std::max(minmaxValue, childValue);
-                } else {
-                    minmaxValue = std::min(minmaxValue, childValue);
-                }
-            }
-
-            // Use minimax value if we found any visited children, else use average
-            if (minmaxValue != (node->isMaximizingPlayer ? -std::numeric_limits<double>::max()
-                                                         : std::numeric_limits<double>::max())) {
-                node->lookaheadScore = minmaxValue;
-            } else {
-                // No children visited yet, fall back to average
-                if (node->visitCount == 1) {
-                    node->lookaheadScore = reward;
-                } else {
-                    const double alpha = 1.0 / node->visitCount;
-                    node->lookaheadScore = (1.0 - alpha) * node->lookaheadScore + alpha * reward;
-                }
-            }
-        } else {
-            // Standard MCTS averaging (for maxPlayerFlips=0 or leaf nodes)
-            if (node->visitCount == 1) {
-                node->lookaheadScore = reward;
-            } else {
-                const double alpha = 1.0 / node->visitCount;
-                node->lookaheadScore = (1.0 - alpha) * node->lookaheadScore + alpha * reward;
-            }
-        }
-
-        node = node->parent;
-    }
-}
-
-auto AbstractMCTSAI::SelectSimulationAction(
-        const MCTSGameEngine& engine,
-        const MCTSGameState& state,
-        const std::vector<std::unique_ptr<MCTSAction>>& actions,
-        const bool isMaximizing) const -> size_t {
-    if (actions.empty()) {
-        throw MCTSInternalError(
-                "MCTSSimulation called with empty actions list - this indicates a bug in the "
-                "MCTS tree building or game state");
-    }
-
-    thread_local std::mt19937 gen(std::random_device{}());
-
-    switch (config_.simulationPolicy) {
-        case MCTSSimulationPolicy::RANDOM: {
-            std::uniform_int_distribution<size_t> dis(0, actions.size() - 1);
-            return dis(gen);
-        }
-
-        case MCTSSimulationPolicy::FILTERED_RANDOM: {
-            if (const auto filteredIndices = engine.filterActions(actions, state);
-                !filteredIndices.empty()) {
-                std::uniform_int_distribution<size_t> dis(0, filteredIndices.size() - 1);
-                return filteredIndices[dis(gen)];
-            }
-            // Fall back to random
-            std::uniform_int_distribution<size_t> dis(0, actions.size() - 1);
-            return dis(gen);
-        }
-
-        case MCTSSimulationPolicy::BEST_IMMEDIATE: {
-            // For adversarial search:
-            // - Maximizing nodes select action with HIGHEST score (best for root player)
-            // - Minimizing nodes select action with LOWEST score (worst for root player)
-
-            // First, filter out obviously bad moves (e.g., BECOME_OUTLAW)
-            const auto filteredIndices = engine.filterActions(actions, state);
-            if (filteredIndices.empty()) {
-                // If all actions filtered out, fall back to first action
-                return 0;
-            }
-
-            double bestScore = isMaximizing ? -std::numeric_limits<double>::max()
-                                            : std::numeric_limits<double>::max();
-            size_t bestIndex = filteredIndices[0];
-
-            for (const size_t i : filteredIndices) {
-                // CRITICAL: Always get score from ROOT player's perspective for adversarial search
-                // If we use currentPlayerId, opponent actions would be scored from their
-                // perspective, causing them to select moves that help themselves instead of hurt
-                // us!
-                const double score = engine.getActionScore(state, *actions[i], playerId_);
-
-                const bool shouldSelect = isMaximizing ? (score > bestScore) : (score < bestScore);
-
-                if (shouldSelect) {
-                    bestScore = score;
-                    bestIndex = i;
-                }
-            }
-            return bestIndex;
-        }
-
-        case MCTSSimulationPolicy::WEIGHTED_BEST_IMMEDIATE: {
-            // Score all actions and weight by ranking
-            std::vector<std::pair<size_t, double>> scores;
-            scores.reserve(actions.size());
-
-            for (size_t i = 0; i < actions.size(); ++i) {
-                // CRITICAL: Always get score from ROOT player's perspective for adversarial search
-                const double score = engine.getActionScore(state, *actions[i], playerId_);
-                scores.emplace_back(i, score);
-            }
-
-            // Sort by score
-            // - Maximizing: highest scores first (prefer actions that maximize root player's score)
-            // - Minimizing: lowest scores first (prefer actions that minimize root player's score)
-            if (isMaximizing) {
-                std::ranges::sort(scores, [](const auto& a, const auto& b) {
-                    return a.second > b.second;  // Descending
-                });
-            } else {
-                std::ranges::sort(scores, [](const auto& a, const auto& b) {
-                    return a.second < b.second;  // Ascending
-                });
-            }
-
-            // Create weights based on ranking
-            std::vector<double> weights;
-            weights.reserve(scores.size());
-            for (size_t i = 0; i < scores.size(); ++i) {
-                weights.push_back(1.0 / (static_cast<double>(i) + 1.0));
-            }
-
-            // Select based on weights
-            std::discrete_distribution<> dis(weights.begin(), weights.end());
-            return scores[dis(gen)].first;
-        }
-
-        case MCTSSimulationPolicy::WEIGHTED_HEURISTIC: {
-            // Get heuristic weights from engine (fast O(1) per action)
-            const auto weights = engine.getActionWeights(actions, state);
-
-            // Filter out zero-weight actions
-            std::vector<size_t> validIndices;
-            std::vector<double> validWeights;
-            validIndices.reserve(actions.size());
-            validWeights.reserve(actions.size());
-
-            for (size_t i = 0; i < weights.size() && i < actions.size(); ++i) {
-                if (weights[i] > 0.0) {
-                    validIndices.push_back(i);
-                    validWeights.push_back(weights[i]);
-                }
-            }
-
-            // If all actions filtered out, this is a bug in the weighting logic
-            if (validWeights.empty()) {
-                throw MCTSInternalError(
-                        "MCTS simulation: All actions have zero weight in WEIGHTED_HEURISTIC "
-                        "policy (action count: " +
-                        std::to_string(actions.size()) + ") - this indicates incorrect weighting");
-            }
-
-            // Select based on heuristic weights using discrete_distribution
-            std::discrete_distribution<> dis(validWeights.begin(), validWeights.end());
-            return validIndices[dis(gen)];
-        }
-    }
-
-    // Default to random
-    std::uniform_int_distribution<size_t> dis(0, actions.size() - 1);
-    return dis(gen);
-}
-
-auto AbstractMCTSAI::FindNodeAtDepthWithHash(
-        const MCTSNode* root,
-        const int maxDepth,
-        const uint64_t targetHash) -> const MCTSNode* {
-    if (!root || root->depth >= maxDepth || root->stateHash == targetHash) { return root; }
-
-    // Breadth-first search for matching hash at specific depth
-    std::vector<const MCTSNode*> currentLevel = {root};
-    for (int d = 0; d < maxDepth && !currentLevel.empty(); ++d) {
-        std::vector<const MCTSNode*> nextLevel;
-
-        for (const auto* node : currentLevel) {
-            for (const auto& child : node->children) {
-                if (child->stateHash == targetHash && child->depth <= maxDepth) {
-                    return child.get();
-                }
-                if (child->depth < maxDepth) { nextLevel.push_back(child.get()); }
-            }
-        }
-
-        currentLevel = std::move(nextLevel);
-    }
-
-    return nullptr;
-}
-
-auto AbstractMCTSAI::LogSearchResults(
-        const MCTSNode* rootNode,
-        const MCTSNode* bestChild,
-        const SearchResult& result) -> void {
-    // Log selected command
-    const std::string selectedDesc =
-            bestChild->action ? bestChild->action->getDescription() : "Unknown";
-    printf("MCTS: Selected %s (visit:%d, reward:%.2f, lookahead:%.2f) from %zu options\n",
-           selectedDesc.c_str(),
-           bestChild->visitCount,
-           bestChild->averageReward,
-           bestChild->lookaheadScore,
-           rootNode->children.size());
-
-    // Log top 3 actions by visits
-    std::vector<const MCTSNode*> sortedChildren;
-    sortedChildren.reserve(rootNode->children.size());
-    for (const auto& child : rootNode->children) { sortedChildren.push_back(child.get()); }
-    std::ranges::sort(sortedChildren, [](const auto* a, const auto* b) {
-        return a->visitCount > b->visitCount;
-    });
-
-    printf("MCTS: Top actions by visits:\n");
-    for (size_t i = 0; i < std::min(static_cast<size_t>(3), sortedChildren.size()); ++i) {
-        const auto* child = sortedChildren[i];
-        printf("  [%zu] visits:%d immediate:%.2f lookahead:%.2f",
-               i,
-               child->visitCount,
-               child->immediateScore,
-               child->lookaheadScore);
-
-        // Show the action's own description
-        if (child->action) { printf(" %s", child->action->getDescription().c_str()); }
-
-        // Show sequence preview
-        if (!child->children.empty()) {
-            const MCTSNode* bestNext = nullptr;
-            int maxVisits = 0;
-            for (const auto& grandchild : child->children) {
-                if (grandchild->visitCount > maxVisits) {
-                    maxVisits = grandchild->visitCount;
-                    bestNext = grandchild.get();
-                }
-            }
-            if (bestNext && bestNext->action) {
-                printf(" -> %s", bestNext->action->getDescription().c_str());
-            }
-        }
-        printf("\n");
-    }
-
-    printf("MCTS: Tree stats - max depth:%d, total nodes:%d, root visits:%d\n",
-           result.searchDepth,
-           result.nodesEvaluated,
-           rootNode->visitCount);
-
-    // Log best sequence from chosen action (following most-visited path)
-    std::vector<const MCTSNode*> bestSequence;
-    bestSequence.reserve(10);
-    const MCTSNode* current = bestChild;
-    double sequenceScore = bestChild->averageReward;
-
-    while (current && bestSequence.size() < 10) {
-        bestSequence.push_back(current);
-        if (current->children.empty()) break;
-
-        // Find most visited child (standard MCTS principal variation)
-        const MCTSNode* bestChildNode = nullptr;
-        int maxVisits = 0;
-        for (const auto& child : current->children) {
-            if (child->visitCount > maxVisits) {
-                maxVisits = child->visitCount;
-                bestChildNode = child.get();
-            }
-        }
-        current = bestChildNode;
-        if (current) { sequenceScore = current->averageReward; }
-    }
-
-    if (!bestSequence.empty()) {
-        printf("MCTS: Best sequence from chosen action (final: %.2f):\n", sequenceScore);
-        for (size_t i = 0; i < bestSequence.size(); ++i) {
-            const auto* node = bestSequence[i];
-            printf("  %zu.", i + 1);
-            if (node->action) { printf(" %s", node->action->getDescription().c_str()); }
-            printf(" (visits:%d, immediate:%.2f, lookahead:%.2f)\n",
-                   node->visitCount,
-                   node->immediateScore,
-                   node->lookaheadScore);
-
-            // For non-root nodes in the sequence, show what the top alternatives were
-            // This helps diagnose if opponent moves are being properly explored
-            if (i > 0 && node->parent && !node->parent->children.empty()) {
-                // Collect all siblings (including this node) and sort by visit count
-                std::vector<const MCTSNode*> siblings;
-                siblings.reserve(node->parent->children.size());
-                for (const auto& child : node->parent->children) {
-                    if (!child->isRedundant) { siblings.push_back(child.get()); }
-                }
-
-                // Sort by visit count (descending)
-                std::ranges::sort(siblings, [](const MCTSNode* a, const MCTSNode* b) {
-                    return a->visitCount > b->visitCount;
-                });
-
-                // Show top 3 alternatives at this decision point
-                printf("      Alternatives at this node (%zu total):\n", siblings.size());
-                const size_t topN = std::min(siblings.size(), size_t(3));
-                for (size_t j = 0; j < topN; ++j) {
-                    const auto* alt = siblings[j];
-                    printf("        [%zu] visits:%d immediate:%.2f lookahead:%.2f",
-                           j,
-                           alt->visitCount,
-                           alt->immediateScore,
-                           alt->lookaheadScore);
-                    if (alt->action) { printf(" %s", alt->action->getDescription().c_str()); }
-                    printf("\n");
-                }
-            }
-        }
-    }
-}
-
-}  // namespace shardok::mcts
@@ -1,92 +0,0 @@
-//
-// Abstract MCTS AI implementation - game agnostic
-//
-
-#ifndef EAGLE0_ABSTRACT_MCTSAI_HPP
-#define EAGLE0_ABSTRACT_MCTSAI_HPP
-
-#include <chrono>
-#include <memory>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameEngine.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSNode.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-class AbstractMCTSAI {
-public:
-    // Search result structure
-    struct SearchResult {
-        size_t bestActionIndex = 0;
-        double bestScore = 0.0;
-        int searchDepth = 0;
-        int nodesEvaluated = 0;
-        std::chrono::milliseconds searchTime{0};
-        bool foundWinningMove = false;
-    };
-
-    explicit AbstractMCTSAI(MCTSPlayerId playerId, MCTSConfig config = MCTSConfig{});
-
-    // Main search interface
-    [[nodiscard]] auto Search(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& initialState,
-            std::chrono::milliseconds timeLimit) const -> SearchResult;
-
-    // Configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return config_; }
-    void SetConfig(const MCTSConfig& newConfig) { config_ = newConfig; }
-
-    [[nodiscard]] auto FindNodeAtDepthWithHash(
-            const MCTSNode* root,
-            int maxDepth,
-            uint64_t targetHash) -> const MCTSNode*;
-
-private:
-    MCTSPlayerId playerId_;
-    MCTSConfig config_;
-
-    // Core MCTS algorithm
-    [[nodiscard]] auto BuildMCTSTree(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& initialState,
-            std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode>;
-
-    // MCTS phases
-    [[nodiscard]] auto MCTSSelection(MCTSNode* root) const -> MCTSNode*;
-
-    [[nodiscard]] auto MCTSExpansion(MCTSNode* node, const MCTSGameEngine& engine) const
-            -> MCTSNode*;
-
-    [[nodiscard]] auto MCTSSimulation(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& state,
-            MCTSPlayerId startingPlayer,
-            int startingPlayerFlips = 0) const -> double;
-
-    auto MCTSBackpropagation(MCTSNode* node, double reward, MCTSBackpropagationPolicy policy) const
-            -> void;
-
-    // Helper functions
-    [[nodiscard]] auto SelectSimulationAction(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& state,
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            bool isMaximizing) const -> size_t;
-
-    // Logging
-    static auto LogSearchResults(
-            const MCTSNode* rootNode,
-            const MCTSNode* bestChild,
-            const SearchResult& result) -> void;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_ABSTRACT_MCTSAI_HPP
@@ -1,93 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "mcts_types",
-    hdrs = ["MCTSTypes.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-)
-
-cc_library(
-    name = "mcts_action",
-    hdrs = ["MCTSAction.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-)
-
-cc_library(
-    name = "mcts_game_state",
-    hdrs = ["MCTSGameState.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "mcts_game_engine",
-    srcs = ["MCTSGameEngine.cpp"],
-    hdrs = ["MCTSGameEngine.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_state",
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "mcts_node",
-    hdrs = ["MCTSNode.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_state",
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "abstract_mcts_ai",
-    srcs = ["AbstractMCTSAI.cpp"],
-    hdrs = ["AbstractMCTSAI.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_engine",
-        ":mcts_game_state",
-        ":mcts_node",
-        ":mcts_types",
-    ],
-)
-
-# Individual targets are exposed above - no need for a catch-all target
-# Each component should be imported explicitly by its consumers
@@ -1,35 +0,0 @@
-//
-// Abstract action interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_ACTION_HPP
-#define EAGLE0_MCTS_ACTION_HPP
-
-#include <memory>
-#include <string>
-
-namespace shardok {
-namespace mcts {
-
-// Abstract interface for game actions
-class MCTSAction {
-public:
-    virtual ~MCTSAction() = default;
-
-    // Get a unique index for this action (used for command indexing)
-    [[nodiscard]] virtual size_t getIndex() const = 0;
-
-    // Get a human-readable description for debugging/logging
-    [[nodiscard]] virtual std::string getDescription() const = 0;
-
-    // Create a deep copy of this action
-    [[nodiscard]] virtual std::unique_ptr<MCTSAction> clone() const = 0;
-
-    // Check if two actions are equivalent
-    [[nodiscard]] virtual bool equals(const MCTSAction& other) const = 0;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_ACTION_HPP
@@ -1,148 +0,0 @@
-//
-// Default implementations for MCTSGameEngine
-//
-
-#include "MCTSGameEngine.hpp"
-
-#include <algorithm>
-#include <limits>
-#include <random>
-#include <vector>
-
-#include "MCTSTypes.hpp"  // For MCTSInternalError
-
-namespace shardok {
-namespace mcts {
-
-double MCTSGameEngine::simulateRandomPlayout(
-        const MCTSGameState& state,
-        MCTSPlayerId playerId,
-        int maxDepth,
-        MCTSSimulationPolicy policy) const {
-    // Clone state once and mutate it throughout simulation for efficiency
-    auto currentState = state.clone();
-    int depth = 0;
-
-    // Use thread-local random generator for thread safety
-    static thread_local std::mt19937 gen(std::random_device{}());
-
-    // Simulate until terminal or max depth
-    while (!currentState->isTerminal() && depth < maxDepth) {
-        auto actions = getLegalActions(*currentState, playerId, 0, 0);
-        if (actions.empty()) { break; }
-
-        size_t selectedIndex = 0;
-
-        // Select action based on policy
-        switch (policy) {
-            case MCTSSimulationPolicy::RANDOM: {
-                std::uniform_int_distribution<> dis(0, actions.size() - 1);
-                selectedIndex = dis(gen);
-                break;
-            }
-
-            case MCTSSimulationPolicy::FILTERED_RANDOM: {
-                auto filteredIndices = filterActions(actions, *currentState);
-                if (!filteredIndices.empty()) {
-                    std::uniform_int_distribution<> dis(0, filteredIndices.size() - 1);
-                    selectedIndex = filteredIndices[dis(gen)];
-                } else {
-                    // Fall back to random if no actions pass filter
-                    std::uniform_int_distribution<> dis(0, actions.size() - 1);
-                    selectedIndex = dis(gen);
-                }
-                break;
-            }
-
-            case MCTSSimulationPolicy::BEST_IMMEDIATE: {
-                double bestScore = -std::numeric_limits<double>::infinity();
-                for (size_t i = 0; i < actions.size(); ++i) {
-                    double score = getActionScore(
-                            *currentState,
-                            *actions[i],
-                            currentState->currentPlayerId());
-                    if (score > bestScore) {
-                        bestScore = score;
-                        selectedIndex = i;
-                    }
-                }
-                break;
-            }
-
-            case MCTSSimulationPolicy::WEIGHTED_BEST_IMMEDIATE: {
-                // Score all actions and weight by ranking
-                std::vector<std::pair<size_t, double>> scores;
-                scores.reserve(actions.size());
-
-                for (size_t i = 0; i < actions.size(); ++i) {
-                    double score = getActionScore(
-                            *currentState,
-                            *actions[i],
-                            currentState->currentPlayerId());
-                    scores.emplace_back(i, score);
-                }
-
-                // Sort by score (descending)
-                std::sort(scores.begin(), scores.end(), [](const auto& a, const auto& b) {
-                    return a.second > b.second;
-                });
-
-                // Create weights based on ranking (1/rank)
-                std::vector<double> weights;
-                weights.reserve(scores.size());
-                for (size_t i = 0; i < scores.size(); ++i) { weights.push_back(1.0 / (i + 1.0)); }
-
-                // Select based on weights
-                std::discrete_distribution<> dis(weights.begin(), weights.end());
-                selectedIndex = scores[dis(gen)].first;
-                break;
-            }
-
-            case MCTSSimulationPolicy::WEIGHTED_HEURISTIC: {
-                // Get heuristic weights (fast O(1) per action)
-                const auto weights = getActionWeights(actions, *currentState);
-
-                // Filter out zero-weight actions
-                std::vector<size_t> validIndices;
-                std::vector<double> validWeights;
-                validIndices.reserve(actions.size());
-                validWeights.reserve(actions.size());
-
-                for (size_t i = 0; i < weights.size() && i < actions.size(); ++i) {
-                    if (weights[i] > 0.0) {
-                        validIndices.push_back(i);
-                        validWeights.push_back(weights[i]);
-                    }
-                }
-
-                // If all actions filtered out, this is a bug in the weighting logic
-                if (validWeights.empty()) {
-                    throw MCTSInternalError(
-                            "MCTS simulation (playout): All actions have zero weight in "
-                            "WEIGHTED_HEURISTIC policy (action count: " +
-                            std::to_string(actions.size()) +
-                            ") - this indicates incorrect weighting");
-                }
-
-                // Select based on heuristic weights
-                std::discrete_distribution<> dis(validWeights.begin(), validWeights.end());
-                selectedIndex = validIndices[dis(gen)];
-                break;
-            }
-        }
-
-        // Apply selected action using mutable version for efficiency
-        applyActionMutable(currentState, *actions[selectedIndex]);
-        if (!currentState) {
-            break;  // Failed to apply action
-        }
-
-        depth++;
-    }
-
-    // Return evaluation from original player's perspective
-    return evaluateState(*currentState, playerId);
-}
-
-}  // namespace mcts
-}  // namespace shardok
@@ -1,119 +0,0 @@
-//
-// Abstract game engine interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_GAME_ENGINE_HPP
-#define EAGLE0_MCTS_GAME_ENGINE_HPP
-
-#include <chrono>
-#include <memory>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Abstract interface for game engines
-class MCTSGameEngine {
-public:
-    virtual ~MCTSGameEngine() = default;
-
-    // Apply an action to a state and return the resulting state
-    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> applyAction(
-            const MCTSGameState& state,
-            const MCTSAction& action) const = 0;
-
-    // Apply an action to a mutable state in-place (for efficient simulation)
-    // Default: clone, apply, and move the result back
-    // Override this for better performance
-    virtual void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
-            const {
-        state = applyAction(*state, action);
-    }
-
-    // Get all legal actions for the current state with player flip tracking
-    // Default implementation ignores flip tracking and calls base version
-    [[nodiscard]] virtual std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
-            const MCTSGameState& state,
-            MCTSPlayerId /*rootPlayerId*/,
-            int /*currentPlayerFlips*/,
-            int /*maxPlayerFlips*/) const = 0;
-
-    // Check if a state is terminal
-    [[nodiscard]] virtual bool isTerminal(const MCTSGameState& state) const = 0;
-
-    // Evaluate a state from the perspective of a player
-    [[nodiscard]] virtual double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
-            const = 0;
-
-    // Filter actions based on game-specific heuristics
-    // Returns indices of actions to keep
-    // Default: no filtering (return all indices)
-    [[nodiscard]] virtual std::vector<size_t> filterActions(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& /*state*/) const {
-        std::vector<size_t> indices;
-        indices.reserve(actions.size());
-        for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
-        return indices;
-    }
-
-    // Get heuristic weights for actions (used by WEIGHTED_HEURISTIC simulation policy)
-    // Returns weights corresponding to each action (same size as actions vector)
-    // Weight of 0.0 = never select, higher = more likely to select
-    // Default: uniform weights (all actions equally likely)
-    [[nodiscard]] virtual std::vector<double> getActionWeights(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& /*state*/) const {
-        // Default: uniform weights
-        return std::vector<double>(actions.size(), 1.0);
-    }
-
-    // Simulate a random playout from the given state
-    // Default implementation uses policy to select actions
-    [[nodiscard]] virtual double simulateRandomPlayout(
-            const MCTSGameState& state,
-            MCTSPlayerId playerId,
-            int maxDepth,
-            MCTSSimulationPolicy policy) const;
-
-    // Get the immediate score of applying an action
-    // Default: apply the action and evaluate the resulting state
-    [[nodiscard]] virtual double getActionScore(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            MCTSPlayerId playerId) const {
-        auto newState = applyAction(state, action);
-        if (!newState) { return 0.0; }
-        return evaluateState(*newState, playerId);
-    }
-
-    // Check if we should stop searching (e.g., time limit, found winning move)
-    [[nodiscard]] virtual bool shouldStopSearch(
-            const MCTSGameState& /*state*/,
-            int /*iterations*/,
-            std::chrono::steady_clock::time_point /*startTime*/) const {
-        // Default: no early stopping
-        return false;
-    }
-
-    // Map a filtered action index back to the original unfiltered index
-    // This is needed when getLegalActions() applies filtering - the returned actions
-    // may be a subset of all available actions, and this maps back to the original index.
-    // Default implementation: no filtering, so filtered index = original index
-    [[nodiscard]] virtual size_t mapFilteredIndexToOriginal(
-            size_t filteredIndex,
-            const MCTSGameState& state) const {
-        // Default: no filtering, index stays the same
-        (void)state;  // Suppress unused parameter warning
-        return filteredIndex;
-    }
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_GAME_ENGINE_HPP
@@ -1,50 +0,0 @@
-//
-// Abstract game state interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_GAME_STATE_HPP
-#define EAGLE0_MCTS_GAME_STATE_HPP
-
-#include <cstdint>
-#include <memory>
-#include <string>
-
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Abstract interface for game states
-class MCTSGameState {
-public:
-    virtual ~MCTSGameState() = default;
-
-    // Compute hash for transposition table
-    [[nodiscard]] virtual uint64_t hash() const = 0;
-
-    // Evaluate the state from the perspective of the given player
-    [[nodiscard]] virtual double score(MCTSPlayerId playerId) const = 0;
-
-    // Get the player whose turn it is
-    [[nodiscard]] virtual MCTSPlayerId currentPlayerId() const = 0;
-
-    // Check if the game has ended
-    [[nodiscard]] virtual bool isTerminal() const = 0;
-
-    // Create a deep copy of the state
-    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> clone() const = 0;
-
-    // Check if two states are equivalent
-    [[nodiscard]] virtual bool equals(const MCTSGameState& other) const = 0;
-
-    // Get winner if terminal, or -1 if not terminal or draw
-    [[nodiscard]] virtual MCTSPlayerId getWinner() const = 0;
-
-    // Optional: Get a string representation for debugging
-    [[nodiscard]] virtual std::string toString() const { return "MCTSGameState"; }
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_GAME_STATE_HPP
@@ -1,231 +0,0 @@
-//
-// Abstract MCTS Node structure for game-agnostic implementation
-//
-
-#ifndef EAGLE0_ABSTRACT_MCTSNODE_HPP
-#define EAGLE0_ABSTRACT_MCTSNODE_HPP
-
-#include <cmath>
-#include <limits>
-#include <memory>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Abstract MCTS Node structure
-struct MCTSNode {
-    // Action information
-    std::unique_ptr<MCTSAction> action;  // The action that led to this node (null for root)
-    size_t actionIndex = SIZE_MAX;       // Index in the original actions array (SIZE_MAX for root)
-
-    // Score information
-    double immediateScore = 0.0;
-    double lookaheadScore = 0.0;
-
-    // Game state after this action
-    std::unique_ptr<MCTSGameState> gameState;
-
-    // MCTS statistics
-    int visitCount = 0;
-    double totalReward = 0.0;
-    double averageReward = 0.0;
-    mutable double ucb1Value = 0.0;
-    double actionWeight = 1.0;  // Prior probability/weight for this action (from heuristics)
-
-    // Tree structure
-    std::vector<std::unique_ptr<MCTSNode>> children;
-    size_t nextUntriedActionIndex = 0;  // Next action to expand
-    size_t totalActions = 0;            // Total number of available actions
-    MCTSNode* parent = nullptr;
-
-    // Game context
-    MCTSPlayerId playerId;
-    int depth = 0;
-    bool isTerminal = false;
-    int playerFlips = 0;  // Number of times the active player has changed from root player
-    bool isMaximizingPlayer = true;  // True if this node is maximizing for root player
-
-    // Transposition detection
-    uint64_t stateHash = 0;
-    bool isRedundant = false;  // True if this node represents a duplicate state
-
-    // Constructor for root node
-    MCTSNode(std::unique_ptr<MCTSGameState> state, MCTSPlayerId pid, int d)
-        : gameState(std::move(state)),
-          playerId(pid),
-          depth(d),
-          playerFlips(0),
-          isMaximizingPlayer(true) {
-        if (gameState) {
-            stateHash = gameState->hash();
-            isTerminal = gameState->isTerminal();
-        }
-    }
-
-    // Constructor for child node
-    MCTSNode(
-            std::unique_ptr<MCTSAction> act,
-            std::unique_ptr<MCTSGameState> state,
-            MCTSPlayerId pid,
-            int d,
-            size_t actIdx = SIZE_MAX,
-            int flips = 0,
-            bool isMaximizing = true,
-            double weight = 1.0)
-        : action(std::move(act)),
-          actionIndex(actIdx),
-          gameState(std::move(state)),
-          actionWeight(weight),
-          playerId(pid),
-          depth(d),
-          playerFlips(flips),
-          isMaximizingPlayer(isMaximizing) {
-        if (gameState) {
-            stateHash = gameState->hash();
-            isTerminal = gameState->isTerminal();
-        }
-    }
-
-    // Iterative destructor to avoid stack overflow with deep trees
-    ~MCTSNode() {
-        std::vector<std::unique_ptr<MCTSNode>> nodesToDestroy;
-        nodesToDestroy.swap(children);
-
-        while (!nodesToDestroy.empty()) {
-            std::vector<std::unique_ptr<MCTSNode>> currentBatch;
-            currentBatch.swap(nodesToDestroy);
-
-            for (const auto& node : currentBatch) {
-                if (node && !node->children.empty()) {
-                    for (auto& child : node->children) {
-                        nodesToDestroy.push_back(std::move(child));
-                    }
-                    node->children.clear();
-                }
-            }
-        }
-    }
-
-    // Calculate UCB1 value for this node from parent's perspective
-    // Uses prior-weighted formula similar to AlphaGo:
-    //   UCB = Q + c * P * sqrt(N_parent) / (1 + N_child)
-    // Where P is the action weight (prior probability from heuristics)
-    [[nodiscard]] double CalculateUCB1(
-            const double explorationConstant,
-            const int parentVisitCount,
-            const bool parentIsMaximizing) const {
-        // Exploitation: use lookahead score (minimax value)
-        // For minimizing nodes, negate the score to prefer low child values
-        const double exploitationValue = parentIsMaximizing ? lookaheadScore : -lookaheadScore;
-
-        // Exploration: prior-weighted formula (AlphaGo-style)
-        // Actions with weight 0.0 (like FLEE_COMMAND) get no exploration bonus
-        // Unvisited nodes get: c * weight * sqrt(N_parent)
-        // This prevents bad actions from dominating exploration due to infinite UCB
-        const double explorationValue = explorationConstant * actionWeight *
-                                        std::sqrt(parentVisitCount) / (1.0 + visitCount);
-
-        return exploitationValue + explorationValue;
-    }
-
-    // Check if this node can be expanded
-    [[nodiscard]] bool CanExpand() const { return nextUntriedActionIndex < totalActions; }
-
-    // Get best child based on UCB1
-    [[nodiscard]] MCTSNode* GetBestChild(const double explorationConstant) const {
-        if (children.empty()) return nullptr;
-
-        MCTSNode* bestChild = nullptr;
-        double bestValue = -std::numeric_limits<double>::max();
-
-        for (auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            // Calculate UCB1 value using the helper function
-            const double value =
-                    child->CalculateUCB1(explorationConstant, visitCount, isMaximizingPlayer);
-
-            // Debug logging for UCB selection
-            static bool enableUCBDebug = false;
-            if (enableUCBDebug && child->visitCount > 0) {
-                const double exploitationValue =
-                        isMaximizingPlayer ? child->lookaheadScore : -child->lookaheadScore;
-                const double explorationValue =
-                        explorationConstant * std::sqrt(std::log(visitCount) / child->visitCount);
-                printf("    UCB: %s lookahead=%.2f expl=%.2f (+%.2f) = %.2f [%s]\n",
-                       isMaximizingPlayer ? "MAX" : "MIN",
-                       child->lookaheadScore,
-                       exploitationValue,
-                       explorationValue,
-                       value,
-                       child->action ? child->action->getDescription().c_str() : "root");
-            }
-
-            if (value > bestValue) {
-                bestValue = value;
-                bestChild = child.get();
-            }
-        }
-
-        return bestChild;
-    }
-
-    // Get best child based on visit count (for final selection)
-    [[nodiscard]] MCTSNode* GetBestFinalChild() const {
-        if (children.empty()) return nullptr;
-
-        MCTSNode* bestChild = nullptr;
-        int bestVisits = 0;
-        double bestScore = isMaximizingPlayer ? -std::numeric_limits<double>::max()
-                                              : std::numeric_limits<double>::max();
-
-        for (const auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            // Prefer most-visited node (robust child selection)
-            if (child->visitCount > bestVisits) {
-                bestVisits = child->visitCount;
-                bestScore = child->lookaheadScore;
-                bestChild = child.get();
-            } else if (child->visitCount == bestVisits) {
-                // Tie-break on lookahead score (minimax value, not poisoned average)
-                // Maximizing: prefer higher score (better for root player)
-                // Minimizing: prefer lower score (worse for root player)
-                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
-                                                              : (child->lookaheadScore < bestScore);
-                if (shouldReplace) {
-                    bestScore = child->lookaheadScore;
-                    bestChild = child.get();
-                }
-            }
-        }
-
-        // If no child was visited, fall back to lookahead score
-        if (!bestChild && !children.empty()) {
-            for (const auto& child : children) {
-                if (child->isRedundant) continue;
-
-                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
-                                                              : (child->lookaheadScore < bestScore);
-                if (shouldReplace) {
-                    bestScore = child->lookaheadScore;
-                    bestChild = child.get();
-                }
-            }
-        }
-
-        return bestChild;
-    }
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_ABSTRACT_MCTSNODE_HPP
@@ -1,54 +0,0 @@
-//
-// Core types for abstract MCTS implementation
-//
-
-#ifndef EAGLE0_MCTS_TYPES_HPP
-#define EAGLE0_MCTS_TYPES_HPP
-
-#include <stdexcept>
-#include <string>
-
-namespace shardok {
-namespace mcts {
-
-// Exception thrown when MCTS encounters an internal error that indicates a bug
-class MCTSInternalError : public std::logic_error {
-public:
-    explicit MCTSInternalError(const std::string& message) : std::logic_error(message) {}
-};
-
-// Abstract player identifier type
-using MCTSPlayerId = int;
-
-// Simulation policy for MCTS rollouts
-enum class MCTSSimulationPolicy {
-    RANDOM,                   // Pure random selection
-    FILTERED_RANDOM,          // Random from filtered actions
-    BEST_IMMEDIATE,           // Choose best immediate score
-    WEIGHTED_BEST_IMMEDIATE,  // Random weighted by score ranking
-    WEIGHTED_HEURISTIC        // Random weighted by fast heuristics (no score evaluation)
-};
-
-// Backpropagation policy for MCTS tree updates
-enum class MCTSBackpropagationPolicy {
-    AVERAGING,  // Traditional MCTS averaging (for stochastic/single-player games)
-    MINIMAX     // Minimax backup (for deterministic adversarial games)
-};
-
-// Configuration for MCTS algorithm
-struct MCTSConfig {
-    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
-    int maxSimulationDepth = 1000;       // Maximum depth for rollout
-    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
-    bool useMultithreading = true;       // Enable parallel MCTS
-    int numThreads = 16;                 // Number of threads for parallel MCTS
-    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
-    MCTSBackpropagationPolicy backpropagationPolicy = MCTSBackpropagationPolicy::AVERAGING;
-    int maxPlayerFlips = 0;  // Maximum number of player changes to explore (0 = stop at first
-                             // flip, 1 = explore through opponent's response, etc.)
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_TYPES_HPP
@@ -36,7 +36,7 @@ auto CalculateMap(
            .name = mapName,
            .positionsRequiringCrossing = {}};

-    for (unsigned int i = 0; i < hexMap->attacker_starting_positions()->size(); i++) {
+    for (int i = 0; i < hexMap->attacker_starting_positions()->size(); i++) {
        const auto* positionList = hexMap->attacker_starting_positions()->Get(i);
        if (positionList->positions()->size() < 1) continue;
        if (positionList->positions()->size() != 10) {
@@ -5,9 +5,7 @@
 #ifndef EAGLE0_MAPINFOCALCULATOR_HPP
 #define EAGLE0_MAPINFOCALCULATOR_HPP

-#include <cstdint>
 #include <map>
-#include <memory>
 #include <string>

 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
@@ -3,7 +3,6 @@
 //

 #include <iostream>
-#include <memory>

 #include "MapInfoCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -53,7 +52,7 @@ auto main(const int argc, char** argv) -> int {
        outputStream << "    \"positions\": {";

        bool firstPosition = true;
-        for (const auto& [position, count] : mapInfo.positionsRequiringCrossing) {
+        for (const auto& kv : mapInfo.positionsRequiringCrossing) {
            if (firstPosition) {
                outputStream << endl;
                firstPosition = false;
@@ -61,7 +60,7 @@ auto main(const int argc, char** argv) -> int {
                outputStream << "," << endl;
            }

-            outputStream << "      \"" << position << "\": " << count;
+            outputStream << "      \"" << kv.first << "\": " << kv.second;
        }
        outputStream << endl << "    }" << endl << "  }";
    }
@@ -4,11 +4,9 @@

 #include "AIAttackGroups.hpp"

-#include <cstdlib>
-#include <iterator>
-#include <ranges>
 #include <unordered_map>

+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

 namespace shardok {
@@ -75,28 +73,30 @@ auto MinDistanceIncludingBraving(
 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const AttackLocations& attackLocations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T {
+        const AttackLocations& attackLocations,
+        const SettingsGetter& settings,
+        const int braveWaterCost) -> DIST_T {
    return EffectiveDistance(
            unit,
            map,
-            attackLocations.LocationsWithEnemyInRange(unit),
+            mapId,
            apdCache,
-            battalionTypeGetter,
+            attackLocations.LocationsWithEnemyInRange(unit),
+            settings,
            braveWaterCost);
 }

 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const CoordsSet& locations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T {
-    const auto mapId = ActionPointDistancesCache::GetMapId(map);
-    const auto& battType = battalionTypeGetter(unit->battalion().type());
+        const CoordsSet& locations,
+        const SettingsGetter& settings,
+        const int braveWaterCost) -> DIST_T {
+    const auto& battType = settings.GetBattalionType(unit->battalion().type());
    const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
    const ActionPointDistances* bravingApd = nullptr;
    if (battType->allowsBraveWater) {
@@ -129,12 +129,12 @@ auto GenerateTargetPriorities(
        const vector<const Unit*>& remainingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const MapId& mapId,
+        const SettingsGetter& settings,
        const bool isLateGame) -> vector<TargetPriorityList> {
    auto cc = map->column_count();

-    const auto mapId = ActionPointDistancesCache::GetMapId(map);
+    const auto braveWaterCost = settings.Backing().brave_water_action_point_cost();

    vector<TargetPriorityList> allTargetsUnitsAndDistances{};
    allTargetsUnitsAndDistances.reserve(remainingUnits.size());
@@ -158,7 +158,7 @@ auto GenerateTargetPriorities(
        vector<TargetAndDistance> targetsWithDistance;

        // Get APDs directly from cache (now with built-in thread-local optimization)
-        const auto& battType = battalionTypeGetter(unit->battalion().type());
+        const auto& battType = settings.GetBattalionType(unit->battalion().type());
        const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
        const ActionPointDistances* bravingApd = nullptr;
        if (battType->allowsBraveWater) {
@@ -221,15 +221,11 @@ auto GenerateTargetPriorities(
                    Power(unit);
        }

-        tpl.priorityOrder.reserve(targetsWithDistance.size());
-        std::ranges::transform(
-                targetsWithDistance,
-                std::back_inserter(tpl.priorityOrder),
-                [](const TargetAndDistance& tad) {
-                    return TargetAndAttackLocations{
-                            .target = tad.target,
-                            .attackLocations = tad.attackLocations};
-                });
+        tpl.priorityOrder = common::Map(targetsWithDistance, [](const TargetAndDistance& tad) {
+            return TargetAndAttackLocations{
+                    .target = tad.target,
+                    .attackLocations = tad.attackLocations};
+        });
    }

    return allTargetsUnitsAndDistances;
@@ -5,12 +5,12 @@
 #ifndef EAGLE0_AIATTACKGROUPS_HPP
 #define EAGLE0_AIATTACKGROUPS_HPP

-#include <functional>
 #include <vector>

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/player_info.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/unit.hpp"
@@ -22,8 +22,6 @@ using Unit = net::eagle0::shardok::storage::fb::Unit;
 using net::eagle0::shardok::storage::fb::PlayerInfo;
 using std::vector;

-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
 struct TargetAndAttackLocations {
    Coords target;
    CoordsSet attackLocations;
@@ -43,18 +41,20 @@ struct TargetPriorityList {
 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const AttackLocations& attackLocations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T;
+        const AttackLocations& attackLocations,
+        const SettingsGetter& settings,
+        int braveWaterCost) -> DIST_T;

 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const CoordsSet& locations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T;
+        const CoordsSet& locations,
+        const SettingsGetter& settings,
+        int braveWaterCost) -> DIST_T;

 auto EffectiveDistance(
        const Unit* unit,
@@ -71,8 +71,8 @@ auto GenerateTargetPriorities(
        const vector<const Unit*>& remainingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const MapId& mapId,
+        const SettingsGetter& settings,
        bool isLateGame = false) -> vector<TargetPriorityList>;

 }  // namespace shardok
@@ -4,8 +4,6 @@

 #include "AIAttackerStrategySelector.hpp"

-#include "AIAttackGroups.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIFleeDecisionCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

@@ -13,23 +11,21 @@ namespace shardok {

 using Unit = net::eagle0::shardok::storage::fb::Unit;

-// Combat success threshold below which we should consider fleeing
-// This replaces the simple troop ratio check with sophisticated probability estimation
-constexpr double FLEE_CONSIDERATION_THRESHOLD = 0.25;
+constexpr double MAXIMUM_RATIO_FOR_ATTACKER_TO_FLEE = 0.50;

 auto AIAttackerStrategySelector::BestAttackerStrategy(
        const PlayerId attackerPid,
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileCoords,
-        int maxRounds,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
        const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-        const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
+        const vector<CommandProto>& availableCommands) -> AIStrategy {
    uint32_t attackerUnitCount = 0;
    int defenderOccupiedCriticalTileCount = 0;
+    int attackerTroops = 0;
+    int defenderTroops = 0;
    bool canFlee = false;

    vector<const Unit*> attackerUnits{};
@@ -44,6 +40,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
        if (pi != nullptr) {
            if (pi->is_defender()) {
                if (unit->location().row() >= 0) {
+                    defenderTroops += unit->battalion().size();
+
                    if (criticalTileCoords.Contains(unit->location())) {
                        ++defenderOccupiedCriticalTileCount;
                    }
@@ -52,6 +50,7 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                }
            } else if (unit->player_id() == attackerPid) {
                ++attackerUnitCount;
+                attackerTroops += unit->battalion().size();
                if (unit->can_flee()) canFlee = true;
                attackerUnits.push_back(unit);
            } else {
@@ -61,19 +60,11 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
    }

    AIStrategy chosenStrategy;
-
-    // Use sophisticated combat success estimation instead of simple troop ratio
-    if (canFlee && AIFleeDecisionCalculator::ShouldConsiderFleeing(
-                           attackerPid,
-                           gameState,
-                           maxRounds,
-                           FLEE_CONSIDERATION_THRESHOLD)) {
+    if (canFlee && attackerTroops < MAXIMUM_RATIO_FOR_ATTACKER_TO_FLEE * defenderTroops) {
        chosenStrategy = FleeStrategy;
    } else if (const CoordsSet startCrossingLocations =
-                       waterCrossingCommandChooser.StartCrossingFrom(
-                               battalionTypeGetter,
-                               gameState,
-                               criticalTileCoords);
+                       waterCrossingCommandChooser
+                               .StartCrossingFrom(settings, gameState, criticalTileCoords);
               !startCrossingLocations.empty()) {
        chosenStrategy = CrossRiversStrategy(startCrossingLocations);
    } else if (attackerUnitCount < criticalTileCoords.size()) {
@@ -88,8 +79,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                attackerUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost));
+                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
+                settings));
    }
    // If any critical tile is occupied by the defender, attack the castles.
    // Otherwise, try to hold the castles.
@@ -105,8 +96,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                attackerUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost));
+                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
+                settings));
    } else {
        chosenStrategy = HoldCastlesStrategy;
    }
@@ -6,26 +6,24 @@
 #define EAGLE0_AIATTACKERSTRATEGYSELECTOR_HPP

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"

 namespace shardok {

+using GameState = net::eagle0::shardok::storage::fb::GameState;
+
 class AIAttackerStrategySelector {
 public:
    static auto BestAttackerStrategy(
            PlayerId attackerPid,
-            const GameStateW& gameState,
+            const GameState* gameState,
            const CoordsSet& criticalTileCoords,
-            int maxRounds,
            const APDCache& apdCache,
            const ALCache& alCache,
-            const BattalionTypeGetter& battalionTypeGetter,
-            ActionPoints braveWaterCost,
+            const SettingsGetter& settings,
            const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
            const vector<CommandProto>& availableCommands) -> AIStrategy;
 };
@@ -1,560 +0,0 @@
-//
-// Command evaluator for AI lookahead search.
-// Extracted from AIScoreCalculator to separate concerns.
-//
-
-#include "AICommandEvaluator.hpp"
-
-#include <chrono>
-#include <cmath>
-#include <future>
-#include <limits>
-
-#include "AICommandFilter.hpp"
-#include "TranspositionTable.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexCubeUtils.hpp"
-
-namespace shardok {
-
-// No need to forward declare internal functions - use the public interface instead
-
-// Helper constants and static variables
-static const std::vector<double> _averageSequence = {0.5};
-static const auto _averageGenerator = std::make_shared<SequenceRandomGenerator>(_averageSequence);
-
-#define MULTITHREAD true
-#define LOGGING_ 0
-
-// Helper function to determine if a command type is deterministic
-static auto IsDeterministic(const CommandType type) -> bool {
-    switch (type) {
-        case net::eagle0::shardok::common::MOVE_COMMAND:
-        case net::eagle0::shardok::common::CONTROL_COMMAND:
-        case net::eagle0::shardok::common::METEOR_START_COMMAND:
-        case net::eagle0::shardok::common::METEOR_TARGET_COMMAND:
-        case net::eagle0::shardok::common::METEOR_CANCEL_COMMAND:
-        case net::eagle0::shardok::common::END_TURN_COMMAND:
-        case net::eagle0::shardok::common::PLACE_UNIT_COMMAND:
-        case net::eagle0::shardok::common::PLACE_HIDDEN_UNIT_COMMAND:
-        case net::eagle0::shardok::common::UNIT_STOP_COMMAND:
-        case net::eagle0::shardok::common::UNIT_REST_COMMAND:
-        case net::eagle0::shardok::common::FLEE_COMMAND:
-        case net::eagle0::shardok::common::REINFORCE_COMMAND:
-        case net::eagle0::shardok::common::RETREAT_COMMAND:
-        case net::eagle0::shardok::common::END_PLAYER_SETUP_COMMAND:
-        case net::eagle0::shardok::common::HIDE_COMMAND:
-        case net::eagle0::shardok::common::FORTIFY_COMMAND:
-        case net::eagle0::shardok::common::BECOME_OUTLAW_COMMAND:
-        case net::eagle0::shardok::common::HOLY_WAVE_COMMAND:
-        case net::eagle0::shardok::common::REPAIR_COMMAND: return true;
-        default: return false;
-    }
-}
-
-// Helper function to sort commands by score
-static auto CommandSorter(
-        const AICommandEvaluator::IndexAndScore& l,
-        const AICommandEvaluator::IndexAndScore& r) -> bool {
-    if (l.lookaheadScore < r.lookaheadScore) return true;
-    if (l.lookaheadScore > r.lookaheadScore) return false;
-
-    // At this point the scores are tied
-    if (l.immediateScore < r.immediateScore) return true;
-    if (l.immediateScore > r.immediateScore) return false;
-
-    return false;
-}
-
-AICommandEvaluator::AICommandEvaluator(
-        const AIScoreCalculator& scorer,
-        const APDCache& apdCache,
-        BattalionTypeGetter battalionTypeGetter)
-    : scorer_(scorer),
-      apdCache_(apdCache),
-      battalionTypeGetter_(std::move(battalionTypeGetter)) {}  // Move the function object
-
-auto AICommandEvaluator::PerformLookahead(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const std::shared_ptr<ShardokEngine>& innerEngine,
-        const ScoreValue currentUtility,
-        const AIStrategy& attackerStrategy,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue> {
-    // Check transposition table before expensive computation
-    auto cachedScore =
-            g_transpositionTable.probe(innerEngine->GetCurrentGameState(), remainingLookahead, pid);
-
-    if (cachedScore.has_value()) {
-        // Return cached result immediately
-        std::promise<ScoreValue> p;
-        p.set_value(*cachedScore);
-        return p.get_future();
-    }
-    const auto nextUtility = currentUtility;
-
-    // Check if we've reached the depth limit before making recursive calls
-    if (remainingLookahead <= 0) {
-        // Store the current utility in the transposition table and return it
-        // Note: Store with depth 1 since depth 0 indicates an empty entry in the transposition
-        // table
-        g_transpositionTable.store(innerEngine->GetCurrentGameState(), 1, pid, nextUtility);
-
-        std::promise<ScoreValue> p;
-        p.set_value(nextUtility);
-        return p.get_future();
-    }
-
-    if (const CommandListSPtr nextCommands = innerEngine->GetAvailableCommandsForAIPlayer(pid);
-        nextCommands && !nextCommands->empty()) {
-        // Get the future from FindBestCommand without calling .get()
-        auto bestCommandFuture = FindBestCommand(
-                pid,
-                isDefender,
-                remainingLookahead - 1,
-                maxRepeatCount,
-                *innerEngine,
-                attackerStrategy,
-                nextUtility,
-                allCastleCoords,
-                deadline);
-
-        // Return a future that chains the best command evaluation
-        return std::async(
-                std::launch::deferred,
-                [bestCommandFuture = std::move(bestCommandFuture),
-                 innerEngine,
-                 pid,
-                 nextUtility,
-                 remainingLookahead]() mutable -> ScoreValue {
-                    const auto [index, type, lookaheadScore, immediateScore] =
-                            bestCommandFuture.get();
-
-                    ScoreValue resultScore;
-                    if (auto& nextCommand =
-                                innerEngine->GetAvailableCommandsForAIPlayer(pid)->at(index);
-                        nextCommand->GetCommandType() !=
-                        net::eagle0::shardok::common::END_TURN_COMMAND) {
-                        resultScore = immediateScore;
-                    } else {
-                        resultScore = nextUtility;
-                    }
-
-                    // Store in transposition table before returning
-                    g_transpositionTable.store(
-                            innerEngine->GetCurrentGameState(),
-                            remainingLookahead,
-                            pid,
-                            resultScore);
-
-                    return resultScore;
-                });
-    }
-
-    // No commands available, store and return the current utility as a future
-    g_transpositionTable
-            .store(innerEngine->GetCurrentGameState(), remainingLookahead, pid, nextUtility);
-
-    std::promise<ScoreValue> p;
-    p.set_value(nextUtility);
-    return p.get_future();
-}
-
-auto AICommandEvaluator::EvaluateWithRandomness(
-        const PlayerId pid,
-        const bool isDefender,
-        const uint32_t commandIndex,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const std::shared_ptr<RandomGenerator>& randomGenerator,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> ImmediateAndLookaheadScore {
-    ImmediateAndLookaheadScore returnValue{};
-
-    // Check if we've exceeded the deadline
-    if (std::chrono::steady_clock::now() > deadline) {
-        // Return with a default score and an empty future that resolves immediately
-        std::promise<ScoreValue> p;
-        p.set_value(0.0);  // Default timeout score
-        returnValue.immediateScore = 0.0;
-        returnValue.lookaheadScore = p.get_future();
-        return returnValue;
-    }
-
-    auto innerEngine = std::make_shared<ShardokEngine>(guessedEngine, false);
-    innerEngine->PostCommand(pid, commandIndex, randomGenerator);
-
-    auto innerUtility = scorer_.GuessedStateScore(
-            isDefender,
-            innerEngine->GetCurrentGameState(),
-            attackerStrategy,
-            allCastleCoords);
-
-    returnValue.immediateScore = innerUtility;
-
-    if (remainingLookahead <= 0) {
-        std::promise<ScoreValue> p;
-        returnValue.lookaheadScore = p.get_future();
-        p.set_value(innerUtility);
-    } else {
-        auto lookaheadLambda = [this,
-                                pid,
-                                isDefender,
-                                remainingLookahead,
-                                maxRepeatCount,
-                                innerEngine,
-                                attackerStrategy,
-                                innerUtility,
-                                &allCastleCoords,
-                                deadline]() -> ScoreValue {
-            auto lookaheadFuture = PerformLookahead(
-                    pid,
-                    isDefender,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    innerEngine,
-                    innerUtility,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-            return lookaheadFuture.get();
-        };
-
-#if MULTITHREAD
-        auto launchPolicy = remainingLookahead == 1 ? std::launch::async : std::launch::deferred;
-        returnValue.lookaheadScore = std::async(launchPolicy, lookaheadLambda);
-#else
-        std::promise<ScoreValue> p;
-        returnValue.lookaheadScore = p.get_future();
-        auto lambdaResult = lookaheadLambda();
-        p.set_value(lambdaResult);
-#endif
-    }
-
-    return returnValue;
-}
-
-auto AICommandEvaluator::FindBestCommand(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const ScoreValue currentUtility,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<IndexAndScore> {
-    const CommandListSPtr guessedDescriptors = guessedEngine.GetAvailableCommandsForAIPlayer(pid);
-
-    // Filter out obviously bad commands to reduce search space
-    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
-            guessedDescriptors,
-            pid,
-            isDefender,
-            guessedEngine.GetCurrentGameState(),
-            apdCache_,
-            battalionTypeGetter_);
-
-    const auto& gameState = guessedEngine.GetCurrentGameState();
-    // Calculate minimum hex distance to enemies for this player
-    double minDistToEnemies = std::numeric_limits<double>::max();
-    const auto* units = gameState->units();
-
-    for (size_t i = 0; i < units->size(); ++i) {
-        if (const auto* playerUnit = units->Get(static_cast<unsigned int>(i));
-            playerUnit->player_id() == pid) {
-            const auto& playerCoords = playerUnit->location();
-
-            for (size_t j = 0; j < units->size(); ++j) {
-                if (const auto* enemyUnit = units->Get(static_cast<unsigned int>(j));
-                    enemyUnit->player_id() != pid) {
-                    const auto& enemyCoords = enemyUnit->location();
-
-                    // Proper hex distance calculation using cube coordinates
-                    const Cube playerCube = OffsetToCube(playerCoords);
-                    const Cube enemyCube = OffsetToCube(enemyCoords);
-                    const int hexDistance = CubeDistance(playerCube, enemyCube);
-
-                    minDistToEnemies = std::min(minDistToEnemies, static_cast<double>(hexDistance));
-                }
-            }
-        }
-    }
-
-    if (minDistToEnemies == std::numeric_limits<double>::max()) {
-        minDistToEnemies = 0.0;  // No enemies found
-    }
-
-#if LOGGING_
-    // Log command count and distance metrics for performance analysis
-    const auto allCommandCount = guessedDescriptors->size();
-    const auto filteredCommandCount = filteredIndices.size();
-    const int currentRound = gameState->current_round();
-
-    printf("AI_COMMAND_COUNT: Round %d, Player %d, Defender %d, MinDist %.1f, Commands %zu -> %zu "
-           "(%.1f%% filtered)\n",
-           currentRound,
-           static_cast<int>(pid),
-           isDefender ? 1 : 0,
-           minDistToEnemies,
-           allCommandCount,
-           filteredCommandCount,
-           100.0 * (allCommandCount - filteredCommandCount) / allCommandCount);
-#endif
-
-    const auto commandCount = filteredIndices.size();
-
-    // Structure to hold all command evaluation data
-    struct CommandEvaluation {
-        size_t index;
-        CommandType type;
-        ScoreValue immediateScore;
-        std::vector<std::future<ScoreValue>> lookaheadFutures;
-    };
-
-    std::vector<CommandEvaluation> commandEvaluations(commandCount);
-
-    for (uint32_t index = 0; index < commandCount; index++) {
-        const auto originalIndex = filteredIndices[index];
-        const auto& guessedDescriptor = guessedDescriptors->at(originalIndex);
-        const auto guessedCommandType = guessedDescriptor->GetCommandType();
-
-        commandEvaluations[index].index = originalIndex;
-        commandEvaluations[index].type = guessedCommandType;
-
-        if (guessedCommandType == net::eagle0::shardok::common::END_TURN_COMMAND) {
-            std::promise<ScoreValue> p;
-            commandEvaluations[index].lookaheadFutures.push_back(p.get_future());
-            p.set_value(currentUtility);
-            commandEvaluations[index].immediateScore = currentUtility;
-        } else if (IsDeterministic(guessedCommandType)) {
-            auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    _averageGenerator,
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            commandEvaluations[index].immediateScore = immediateScore;
-            commandEvaluations[index].lookaheadFutures.push_back(std::move(lookaheadScore));
-        } else if (guessedDescriptor->HasOdds()) {
-            const auto successChancePercentile = guessedDescriptor->GetOddsPercentile();
-            const double successChance = static_cast<double>(successChancePercentile) / 100.0;
-
-            // Success attempt uses 1.0 - (successChance / 2) as the roll
-            auto [successImmediateScore, successLookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(
-                            std::vector{1.0 - successChance / 2.0}),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            // Failure attempt uses the average of (1 - successChance) and 0 as the roll
-            auto [failureImmediateScore, failureLookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(
-                            std::vector{(1.0 - successChance) / 2.0}),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            commandEvaluations[index].immediateScore =
-                    std::lerp(failureImmediateScore, successImmediateScore, successChance);
-
-            auto successSF = successLookaheadScore.share();
-            auto failureSF = failureLookaheadScore.share();
-            commandEvaluations[index].lookaheadFutures.push_back(std::async(
-                    std::launch::deferred,
-                    [successSF, failureSF, successChance]() -> double {
-                        return std::lerp(failureSF.get(), successSF.get(), successChance);
-                    }));
-        } else {
-            ScoreValue sum = 0.0;
-            for (int repeatIteration = 0; repeatIteration < maxRepeatCount; repeatIteration++) {
-                // In each iteration, use a double from [0, 1] as the random roll
-                auto sequence = std::vector{
-                        static_cast<double>(repeatIteration) /
-                        static_cast<double>(maxRepeatCount - 1)};
-                auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                        pid,
-                        isDefender,
-                        originalIndex,
-                        remainingLookahead,
-                        maxRepeatCount,
-                        std::make_shared<SequenceRandomGenerator>(sequence),
-                        guessedEngine,
-                        attackerStrategy,
-                        allCastleCoords,
-                        deadline);
-
-                sum += immediateScore;
-                commandEvaluations[index].lookaheadFutures.push_back(std::move(lookaheadScore));
-            }
-            commandEvaluations[index].immediateScore = sum / maxRepeatCount;
-        }
-    }
-
-    // Return a future that will wait for all evaluations and find the best one
-    return std::async(
-            std::launch::deferred,
-            [evals = std::move(commandEvaluations)]() mutable -> IndexAndScore {
-                std::vector<IndexAndScore> allResults;
-                allResults.reserve(evals.size());
-
-                // Wait for all futures and compute final scores
-                for (auto& eval : evals) {
-                    ScoreValue totalLookaheadScore = 0.0;
-                    for (auto& future : eval.lookaheadFutures) {
-                        totalLookaheadScore += future.get();
-                    }
-                    ScoreValue avgLookaheadScore =
-                            eval.lookaheadFutures.empty()
-                                    ? eval.immediateScore
-                                    : totalLookaheadScore / eval.lookaheadFutures.size();
-
-                    allResults.push_back(IndexAndScore{
-                            .index = eval.index,
-                            .type = eval.type,
-                            .lookaheadScore = avgLookaheadScore,
-                            .immediateScore = eval.immediateScore});
-                }
-                // Find the best command using the existing sorter
-                auto bestIt = std::ranges::max_element(allResults, CommandSorter);
-                return *bestIt;
-            });
-}
-
-auto AICommandEvaluator::EvaluateCommand(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const ScoreValue currentUtility,
-        const CoordsSet& allCastleCoords,
-        const size_t commandIndex,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue> {
-    const CommandListSPtr guessedDescriptors = guessedEngine.GetAvailableCommandsForAIPlayer(pid);
-
-    if (commandIndex >= guessedDescriptors->size()) {
-        std::promise<ScoreValue> p;
-        p.set_value(currentUtility);
-        return p.get_future();
-    }
-
-    const auto& guessedDescriptor = guessedDescriptors->at(commandIndex);
-
-    if (const auto guessedCommandType = guessedDescriptor->GetCommandType();
-        guessedCommandType == net::eagle0::shardok::common::END_TURN_COMMAND) {
-        std::promise<ScoreValue> p;
-        p.set_value(currentUtility);
-        return p.get_future();
-    } else if (IsDeterministic(guessedCommandType)) {
-        auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                _averageGenerator,
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-        return std::move(lookaheadScore);
-    } else if (guessedDescriptor->HasOdds()) {
-        const auto successChancePercentile = guessedDescriptor->GetOddsPercentile();
-        const double successChance = static_cast<double>(successChancePercentile) / 100.0;
-
-        // Success attempt
-        auto [successImmediateScore, successLookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                std::make_shared<SequenceRandomGenerator>(std::vector{1.0 - successChance / 2.0}),
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-
-        // Failure attempt
-        auto [failureImmediateScore, failureLookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                std::make_shared<SequenceRandomGenerator>(std::vector{(1.0 - successChance) / 2.0}),
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-
-        // Return weighted average of success and failure
-        auto successSF = successLookaheadScore.share();
-        auto failureSF = failureLookaheadScore.share();
-        return std::async(std::launch::deferred, [successSF, failureSF, successChance]() -> double {
-            return std::lerp(failureSF.get(), successSF.get(), successChance);
-        });
-    } else {
-        // For non-deterministic commands without odds, use multiple attempts
-        std::vector<std::future<ScoreValue>> lookaheadFutures;
-        lookaheadFutures.reserve(maxRepeatCount);
-
-        for (int repeatIteration = 0; repeatIteration < maxRepeatCount; repeatIteration++) {
-            auto sequence = std::vector{
-                    static_cast<double>(repeatIteration) / static_cast<double>(maxRepeatCount - 1)};
-            auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    commandIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(sequence),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            lookaheadFutures.push_back(std::move(lookaheadScore));
-        }
-
-        // Return a future that computes the average when needed
-        return std::async(
-                std::launch::deferred,
-                [lookaheadFutures = std::move(lookaheadFutures),
-                 maxRepeatCount]() mutable -> double {
-                    ScoreValue total = 0.0;
-                    for (auto& future : lookaheadFutures) { total += future.get(); }
-                    return total / maxRepeatCount;
-                });
-    }
-}
-
-}  // namespace shardok
@@ -1,112 +0,0 @@
-//
-// Command evaluator for AI lookahead search.
-// Separated from AIScoreCalculator to isolate pure state scoring from lookahead logic.
-//
-
-#ifndef EAGLE0_AICOMMANDEVALUATOR_HPP
-#define EAGLE0_AICOMMANDEVALUATOR_HPP
-
-#include <chrono>
-#include <future>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-class ShardokEngine;
-
-using ScoreValue = double;
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-using CommandType = net::eagle0::shardok::common::CommandType;
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
-/// Evaluates commands with lookahead using minimax-style search.
-/// Uses AIScoreCalculator for pure state evaluation, adds recursive lookahead logic.
-class AICommandEvaluator {
-public:
-    /// Construct evaluator with a scorer for state evaluation and dependencies for command
-    /// filtering
-    AICommandEvaluator(
-            const AIScoreCalculator& scorer,
-            const APDCache& apdCache,
-            BattalionTypeGetter battalionTypeGetter);  // Pass by value
-
-    /// Evaluates the score for a particular command index with lookahead.
-    [[nodiscard]] auto EvaluateCommand(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            ScoreValue currentUtility,
-            const CoordsSet& allCastleCoords,
-            size_t commandIndex,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
-
-    /// Find the best command among all available commands at the given depth.
-    struct IndexAndScore {
-        size_t index;
-        CommandType type;
-        ScoreValue lookaheadScore;
-        ScoreValue immediateScore;
-    };
-
-    [[nodiscard]] auto FindBestCommand(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            ScoreValue currentUtility,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<IndexAndScore>;
-
-private:
-    const AIScoreCalculator& scorer_;
-    const APDCache& apdCache_;
-    BattalionTypeGetter battalionTypeGetter_;  // Store by value
-
-    struct ImmediateAndLookaheadScore {
-        ScoreValue immediateScore;
-        std::future<ScoreValue> lookaheadScore;
-    };
-
-    /// Recursive lookahead calculator
-    [[nodiscard]] auto PerformLookahead(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const std::shared_ptr<ShardokEngine>& innerEngine,
-            ScoreValue currentUtility,
-            const AIStrategy& attackerStrategy,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
-
-    /// Evaluate single command execution with randomness handling
-    [[nodiscard]] auto EvaluateWithRandomness(
-            PlayerId pid,
-            bool isDefender,
-            uint32_t commandIndex,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const std::shared_ptr<class RandomGenerator>& randomGenerator,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> ImmediateAndLookaheadScore;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AICOMMANDEVALUATOR_HPP
@@ -20,8 +20,8 @@ CoordsSet AICommandFilter::BuildEnemyLocations(const GameStateW& gameState, Play
    CoordsSet enemyLocations(gameState->hex_map());
    const auto* units = gameState->units();

-    for (size_t i = 0; i < units->size(); ++i) {
-        const auto* unit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size(); ++i) {
+        const auto* unit = units->Get(i);
        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            unit->player_id() != pid && !unit->hidden() && unit->location().column() != -1) {
            enemyLocations.Add(unit->location());
@@ -36,8 +36,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
-        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) {
+        const SettingsGetter& settings,
+        const APDCache& apdCache) {
    std::vector<size_t> filteredIndices;
    filteredIndices.reserve(commands->size());

@@ -66,8 +66,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                    pid,
                    isDefender,
                    gameState,
+                    settings,
                    apdCache,
-                    battalionTypeGetter,
                    enemyLocations,
                    castleLocations,
                    minDistToEnemies)) {
@@ -80,22 +80,16 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                                     pid,
                                     isDefender,
                                     gameState,
+                                     settings,
                                     apdCache,
-                                     battalionTypeGetter,
                                     enemyLocations,
                                     minDistToEnemies)) {
            shouldFilter = true;
        }

        // Check strategic blunders
-        if (!shouldFilter && IsStrategicBlunder(
-                                     *cmd,
-                                     pid,
-                                     isDefender,
-                                     gameState,
-                                     apdCache,
-                                     battalionTypeGetter,
-                                     minDistToEnemies)) {
+        if (!shouldFilter &&
+            IsStrategicBlunder(*cmd, pid, isDefender, gameState, settings, minDistToEnemies)) {
            shouldFilter = true;
        }

@@ -110,8 +104,8 @@ bool AICommandFilter::IsWastefulAction(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
+        const SettingsGetter& settings,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
        const CoordsSet& enemyLocations,
        const CoordsSet& castleLocations,
        double minDistToEnemies) {
@@ -275,7 +269,7 @@ bool AICommandFilter::IsWastefulAction(
            }

            // Get action point distances for this unit's battalion type
-            const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
+            const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
            const auto* apd = apdCache->GetRaw(
                    gameState->hex_map(),
                    ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -413,8 +407,8 @@ bool AICommandFilter::IsWastefulMovement(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
+        const SettingsGetter& settings,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
        const CoordsSet& enemyLocations,
        double minDistToEnemies) {
    if (cmd.GetCommandType() != CommandType::MOVE_COMMAND) { return false; }
@@ -455,7 +449,7 @@ bool AICommandFilter::IsWastefulMovement(
            static_cast<int8_t>(targetCoords.column())};

    // Get action point distances for this unit's battalion type
-    const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
+    const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
    const auto* apd = apdCache->GetRaw(
            gameState->hex_map(),
            ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -492,13 +486,12 @@ bool AICommandFilter::IsWastefulMovement(
 }

 bool AICommandFilter::IsStrategicBlunder(
-        const ShardokCommand& /*cmd*/,
-        PlayerId /*pid*/,
-        bool /*isDefender*/,
-        const GameStateW& /*gameState*/,
-        const APDCache& /*apdCache*/,
-        const BattalionTypeGetter& /*battalionTypeGetter*/,
-        double /*minDistToEnemies*/) {
+        const ShardokCommand& cmd,
+        PlayerId pid,
+        bool isDefender,
+        const GameStateW& gameState,
+        const SettingsGetter& settings,
+        double minDistToEnemies) {
    // Simplified strategic blunder detection for now
    // TODO: Implement proper castle abandonment detection
    // TODO: Use minDistToEnemies for strategic blunder logic
@@ -513,8 +506,8 @@ double AICommandFilter::MinDistanceToEnemyUnits(
    double minDistance = std::numeric_limits<double>::max();
    const auto* units = gameState->units();

-    for (size_t i = 0; i < units->size(); ++i) {
-        const auto* playerUnit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size(); ++i) {
+        const auto* playerUnit = units->Get(i);
        if (playerUnit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            playerUnit->player_id() == pid) {
            const auto& playerCoords = playerUnit->location();
@@ -544,8 +537,8 @@ double AICommandFilter::MinDistanceToCastles(
    }

    // Find minimum hex distance from any player unit to any castle
-    for (size_t i = 0; i < units->size(); ++i) {
-        const auto* unit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size(); ++i) {
+        const auto* unit = units->Get(i);
        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            unit->player_id() == pid) {
            const auto& unitCoords = unit->location();
@@ -579,8 +572,8 @@ int AICommandFilter::CountPlayerUnits(const GameStateW& gameState, PlayerId pid)
    int count = 0;
    const auto* units = gameState->units();

-    for (size_t i = 0; i < units->size(); ++i) {
-        const auto* unit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size(); ++i) {
+        const auto* unit = units->Get(i);
        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            unit->player_id() == pid) {
            count++;
@@ -591,9 +584,9 @@ int AICommandFilter::CountPlayerUnits(const GameStateW& gameState, PlayerId pid)
 }

 bool AICommandFilter::WouldAbandonCriticalCastle(
-        const ShardokCommand& /*cmd*/,
-        PlayerId /*pid*/,
-        const GameStateW& /*gameState*/) {
+        const ShardokCommand& cmd,
+        PlayerId pid,
+        const GameStateW& gameState) {
    // Simplified implementation - return false for now
    // TODO: Implement proper castle abandonment detection when API is available
    return false;
@@ -8,7 +8,6 @@
 #include <memory>
 #include <vector>

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
@@ -33,8 +32,8 @@ public:
     * @param pid Player ID making the move
     * @param isDefender True if this player is the defender
     * @param gameState Current game state
+     * @param settings Game settings for parameter lookup
     * @param apdCache Action point distance cache for distance calculations
-     * @param battalionTypeLookup Function to look up battalion types by ID
     * @return Filtered list of commands worth evaluating
     */
    static std::vector<size_t> FilterCommands(
@@ -42,8 +41,8 @@ public:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
-            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup);
+            const SettingsGetter& settings,
+            const APDCache& apdCache);

 private:
    // Helper to build enemy locations once for efficiency
@@ -55,8 +54,8 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
+            const SettingsGetter& settings,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
            const CoordsSet& enemyLocations,
            const CoordsSet& castleLocations,
            double minDistToEnemies);
@@ -67,8 +66,8 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
+            const SettingsGetter& settings,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
            const CoordsSet& enemyLocations,
            double minDistToEnemies);

@@ -78,8 +77,7 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
-            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
+            const SettingsGetter& settings,
            double minDistToEnemies);

    // Helper functions for distance and position analysis
@@ -1,23 +0,0 @@
-//
-// AICommonTypes.hpp
-// Common type definitions used across AI utility functions
-//
-
-#ifndef EAGLE0_AICOMMONTYPES_HPP
-#define EAGLE0_AICOMMONTYPES_HPP
-
-#include <functional>
-
-#include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-namespace shardok {
-
-// Function type for looking up battalion types by ID
-// Used across AI utilities to get battalion type information without
-// needing to pass the entire scorer object
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AICOMMONTYPES_HPP
@@ -1,25 +0,0 @@
-//
-// AI System Types and Configuration
-//
-
-#ifndef EAGLE0_AI_CONFIG_HPP
-#define EAGLE0_AI_CONFIG_HPP
-
-namespace shardok {
-
-// Enum for AI algorithm selection
-enum class AIAlgorithmType {
-    ITERATIVE_DEEPENING,  // Default: Minimax with sophisticated randomness
-    MCTS                  // Monte Carlo Tree Search with multithreading
-};
-
-// Enum for scoring calculator selection
-enum class ScoringCalculatorType {
-    STANDARD,       // Default: Unbounded raw scores
-    NORMALIZED,     // Normalized scores in [0, 1] range for ML training
-    MCTS_OPTIMIZED  // Bounded linear scores tuned for MCTS
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_CONFIG_HPP
@@ -4,13 +4,8 @@

 #include "AIDefenderStrategySelector.hpp"

-#include <algorithm>
-#include <ranges>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

 namespace shardok {
@@ -19,11 +14,10 @@ constexpr double MAXIMUM_RATIO_FOR_DEFENDER_TO_FLEE = 0.15;
 constexpr double MINIMUM_RATIO_FOR_DEFENDER_TO_HOLD = 0.60;

 auto AIDefenderStrategySelector::BestDefenderStrategy(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const CoordsSet& criticalTileCoords,
-        int maxRounds,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy {
+        const SettingsGetter& settings) -> AIStrategy {
    uint32_t attackerNonUndeadUnitCount = 0;
    uint32_t attackerNonUndeadUnitNotRequiringWaterCrossingCount = 0;
    int attackerTroops = 0;
@@ -39,7 +33,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                    player->player_id(),
                    criticalTileCoords,
                    apdCache,
-                    battalionTypeGetter);
+                    settings);
            attackerUnitIdsRequiringWaterCrossing.insert(
                    attackerUnitIdsRequiringWaterCrossing.end(),
                    unitIdsRequiringWaterCrossing.begin(),
@@ -63,9 +57,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                    net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD) {
                    ++attackerNonUndeadUnitCount;

-                    if (!std::ranges::contains(
-                                attackerUnitIdsRequiringWaterCrossing,
-                                unit->unit_id())) {
+                    if (!common::Contains(attackerUnitIdsRequiringWaterCrossing, unit->unit_id())) {
                        ++attackerNonUndeadUnitNotRequiringWaterCrossingCount;
                    }
                }
@@ -74,7 +66,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
        }
    }

-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining = 32 - gameState->current_round();
    AIStrategy chosenStrategy;

    // Defender will flee if
@@ -6,23 +6,20 @@
 #define EAGLE0_AIDEFENDERSTRATEGYSELECTOR_HPP

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"

 namespace shardok {
-
 class AIDefenderStrategySelector {
+    using GameState = net::eagle0::shardok::storage::fb::GameState;
+
 public:
    static auto BestDefenderStrategy(
-            const GameStateW& gameState,
+            const GameState* gameState,
            const CoordsSet& criticalTileCoords,
-            int maxRounds,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy;
+            const SettingsGetter& settings) -> AIStrategy;
 };
 }  // namespace shardok

@@ -49,8 +49,8 @@ auto DefenderDistanceBuf(
        const vector<const Unit *> &attackerUnits,
        const APDCache &apdCache,
        const ALCache &alCache,
-        const BattalionTypeGetter &battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter &settings,
+        const int braveWaterActionPointCost,
        const bool lateGame,
        const bool includeUndead) -> double {
    const auto &locationsToAttackMe = alCache->CachedLocations(defenderLocation, lateGame);
@@ -73,14 +73,14 @@ auto DefenderDistanceBuf(
            notBravingDistances[typeInt] = apdCache->GetRaw(
                    hexMap,
                    mapId,
-                    battalionTypeGetter(attacker->battalion().type()),
+                    settings.GetBattalionType(attacker->battalion().type()),
                    false);
            bravingDistances[typeInt] = apdCache->GetRaw(
                    hexMap,
                    mapId,
-                    battalionTypeGetter(attacker->battalion().type()),
+                    settings.GetBattalionType(attacker->battalion().type()),
                    true,
-                    braveWaterCost);
+                    braveWaterActionPointCost);
        }
    }

@@ -6,10 +6,10 @@
 #define EAGLE0_AIDISTANCEDEBUF_HPP

 #include "AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"

 namespace shardok {

@@ -23,8 +23,8 @@ auto DefenderDistanceBuf(
        const vector<const Unit *> &attackerUnits,
        const APDCache &apdCache,
        const ALCache &alCache,
-        const BattalionTypeGetter &battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter &settings,
+        int braveWaterActionPointCost,
        bool lateGame,
        bool includeUndead) -> double;

@@ -9,7 +9,6 @@
 #include "AIFleeDecisionCalculator.hpp"

 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

 namespace shardok {
@@ -22,18 +21,11 @@ auto AIFleeDecisionCalculator::GetFleeCommandIndex(

 auto AIFleeDecisionCalculator::EstimateCombatSuccess(
        PlayerId attackerPlayerId,
-        const GameStateW& gameState,
-        int maxRounds) -> double {
-    if (gameState->status() == nullptr ||
-        gameState->status()->state() !=
-                net::eagle0::shardok::storage::fb::GameStatus_::State_GAME_RUNNING) {
-        return 1.0;  // we're still in set_up so we can't really evaluate
-    }
+        const GameStateW& guessedState,
+        const GameSettingsSPtr& settings) -> double {
+    // Combat success estimation based on troops, heroes, and capture dynamics

-    // Combat success estimation based on unit power, heroes, and capture dynamics
-    double attackerPower = 0.0;
-    double defenderPower = 0.0;
-    int attackerTroops = 0;  // Still track raw troops for special cases
+    int attackerTroops = 0;
    int defenderTroops = 0;
    int attackerUnits = 0;
    int defenderUnits = 0;
@@ -41,19 +33,17 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(
    int defenderHeroes = 0;
    bool defenderHasVips = false;

-    // Calculate total power and count units/heroes for each side
-    for (const auto* unit : *gameState->units()) {
+    // Count troops, units, and heroes for each side
+    for (const auto* unit : *guessedState->units()) {
        if (unit->status() != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;

-        const auto* pi = PlayerInfoForPid(gameState, unit->player_id());
+        const auto* pi = PlayerInfoForPid(guessedState, unit->player_id());
        if (pi == nullptr) continue;

        const int unitTroops = unit->battalion().size();
        const bool hasHero = unit->has_attached_hero();
-        const double unitPower = ContextFreeUnitValue(unit);

        if (pi->is_defender()) {
-            defenderPower += unitPower;
            defenderTroops += unitTroops;
            defenderUnits++;
            if (hasHero) {
@@ -61,50 +51,46 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(
                if (unit->attached_hero().is_vip()) { defenderHasVips = true; }
            }
        } else if (unit->player_id() == attackerPlayerId) {
-            attackerPower += unitPower;
            attackerTroops += unitTroops;
            attackerUnits++;
            if (hasHero) { attackerHeroes++; }
        }
    }

-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining =
+            settings->GetGetter().Backing().max_rounds() - guessedState->current_round();

-    // Special case: Attacker has no heroes - automatic loss
-    if (attackerHeroes == 0) {
-        return 0.0;  // Cannot win without heroes
-    }
-
-    // Special case: Defender has no heroes - automatic win for attacker
-    if (defenderHeroes == 0) {
-        return 1.0;  // Guaranteed win
-    }
-
-    // Special case: Attacker has no troops (but has heroes)
+    // Special case: Attacker has no troops
    if (attackerTroops == 0) {
-        // Very difficult to win with heroes alone
-        return 0.05;  // Extremely low chance
+        // Even with heroes, attacker is extremely unlikely to win without troops
+        return 0.01;  // Near zero, but not absolute zero
    }

    // Special case: Defender has no troops but has heroes
-    if (defenderTroops == 0) {
-        // Defenders with only heroes are vulnerable to capture
-        // Only truly difficult if time is extremely limited
-        if (roundsRemaining <= 1) {
-            // Last round - very hard to capture all heroes
-            return 0.3;  // Low but not impossible
-        } else if (roundsRemaining <= 2) {
-            return 0.6;  // Still achievable
+    if (defenderTroops == 0 && defenderHeroes > 0) {
+        // Defender can win by running out the clock if attacker can't capture heroes
+        // Success depends heavily on remaining time and attacker's ability to capture
+        if (roundsRemaining <= 3) {
+            // Very hard for attacker to capture all heroes in time
+            return 0.15;  // Low chance
+        } else if (roundsRemaining <= 5) {
+            return 0.25;  // Still difficult
        } else {
-            // With 3+ rounds, capturing defenseless heroes is quite feasible
-            return 0.85;  // High probability of success
+            // More time available, but still challenging
+            return 0.35;
        }
    }

+    // Special case: Defender has neither troops nor heroes
+    if (defenderTroops == 0 && defenderHeroes == 0) {
+        return 0.95;  // Nearly guaranteed win
+    }
+
    // Normal case: Both sides have troops
-    // Base probability from power ratio (accounts for unit quality, not just quantity)
-    const double powerRatio = attackerPower / std::max(1.0, defenderPower);
-    double baseProbability = std::min(0.95, std::max(0.05, powerRatio * 0.5));
+    // Base probability from troop ratio
+    const double troopRatio =
+            static_cast<double>(attackerTroops) / static_cast<double>(defenderTroops);
+    double baseProbability = std::min(0.95, std::max(0.05, troopRatio * 0.5));

    // Adjust for time pressure - attackers need to win before time runs out
    if (roundsRemaining <= 1) {
@@ -133,16 +119,19 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(

 auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
        PlayerId playerId,
+        const GameSettingsSPtr& settings,
        const GameStateW& guessedState,
        const vector<CommandProto>& availableCommands,
        const vector<CommandProto>::const_iterator& fleeCommand,
-        int maxRounds,
-        int minimumFleeOddsThreshold,
-        int desperateFleeThreshold,
        bool enableDebugLogging) -> FleeDecision {
    // Get flee success odds
    const int fleeSuccessChance = fleeCommand->odds().success_chance();

+    // Get thresholds from settings
+    const auto settingsGetter = settings->GetGetter();
+    const int minimumFleeOddsThreshold = settingsGetter.Backing().ai_minimum_flee_odds_threshold();
+    const int desperateFleeThreshold = settingsGetter.Backing().ai_desperate_flee_threshold();
+
    if (enableDebugLogging) {
        printf("AI FinalRound: Evaluating flee (odds=%d%%)...\n", fleeSuccessChance);
    }
@@ -161,10 +150,10 @@ auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
    }

    // Low flee odds - evaluate if fighting might be better
-    const double combatWinChance = EstimateCombatSuccess(playerId, guessedState, maxRounds);
+    const double combatWinChance = EstimateCombatSuccess(playerId, guessedState, settings);

    // If combat situation is hopeless, even bad flee odds are better than certain death
-    if (combatWinChance <= 0.05 && fleeSuccessChance >= desperateFleeThreshold) {
+    if (combatWinChance < 0.05 && fleeSuccessChance >= desperateFleeThreshold) {
        if (enableDebugLogging) {
            printf("AI FinalRound: Combat hopeless (%.1f%%), desperate flee attempt (%d%%)\n",
                   combatWinChance * 100,
@@ -210,17 +199,4 @@ auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
    }
 }

-auto AIFleeDecisionCalculator::ShouldConsiderFleeing(
-        PlayerId attackerPlayerId,
-        const GameStateW& guessedState,
-        int maxRounds,
-        double fleeConsiderationThreshold) -> bool {
-    // Get combat success probability
-    const double combatSuccessChance =
-            EstimateCombatSuccess(attackerPlayerId, guessedState, maxRounds);
-
-    // Consider fleeing if combat success chance is below threshold
-    return combatSuccessChance < fleeConsiderationThreshold;
-}
-
 }  // namespace shardok
@@ -10,6 +10,7 @@
 #define AIFleeDecisionCalculator_hpp

 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"

 namespace shardok {
@@ -34,27 +35,17 @@ public:
    // Evaluate whether to flee or fight in the final round
    [[nodiscard]] static auto EvaluateFleeVsFight(
            PlayerId playerId,
+            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
            const vector<CommandProto>& availableCommands,
            const vector<CommandProto>::const_iterator& fleeCommand,
-            int maxRounds,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
            bool enableDebugLogging = false) -> FleeDecision;

    // Estimate probability of combat success for the attacker
    [[nodiscard]] static auto EstimateCombatSuccess(
            PlayerId attackerPlayerId,
            const GameStateW& guessedState,
-            int maxRounds) -> double;
-
-    // Determine if the attacker should consider fleeing based on combat odds
-    // Returns true if fleeing should be considered as an option
-    [[nodiscard]] static auto ShouldConsiderFleeing(
-            PlayerId attackerPlayerId,
-            const GameStateW& guessedState,
-            int maxRounds,
-            double fleeConsiderationThreshold = 0.5) -> bool;
+            const GameSettingsSPtr& settings) -> double;

 private:
    // Helper to get flee command index
@@ -1,230 +0,0 @@
-//
-// Fast heuristic weighting implementation with context-aware logic
-//
-
-#include "AIHeuristicWeighting.hpp"
-
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-
-namespace shardok {
-
-using CommandType = net::eagle0::shardok::common::CommandType;
-using Coords = net::eagle0::shardok::storage::fb::Coords;
-using ProtoCoords = net::eagle0::shardok::common::Coords;
-
-double AIHeuristicWeighting::GetCommandWeight(
-        const net::eagle0::shardok::api::CommandDescriptor& command,
-        const GameStateW& state,
-        const CoordsSet& castleCoords,
-        const APDCache* apdCache,
-        bool isDefender,
-        std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType) {
-    // Fast O(1) heuristic weights based on command type and game context
-    // Higher weight = more likely to select in simulation
-    // 0.0 = never select (filtered out)
-
-    const auto* hexMap = state->hex_map();
-    const auto* units = state->units();
-    const auto actorPlayerId = command.player();
-
-    switch (command.type()) {
-        // === HIGH VALUE OFFENSIVE (10.0) ===
-        // Ranged attacks - very valuable, typically available when in range
-        case CommandType::ARCHERY_COMMAND: return 20.0;
-        case CommandType::LIGHTNING_BOLT_COMMAND: return 10.0;
-        case CommandType::FEAR_COMMAND: return 10.0;
-
-        // Area/tactical spells - high impact
-        case CommandType::METEOR_START_COMMAND: {
-            // High weight per enemy unit at or adjacent to target
-            if (!command.has_target()) return 0.0;  // Default if no target info
-
-            const Coords targetCoords(command.target().row(), command.target().column());
-            int enemyCount = 0;
-
-            // Count enemies at target
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) { enemyCount++; }
-            }
-
-            // Count enemies adjacent to target
-            for (const auto& neighbor : HexMapUtils::GetAdjacentTiles(hexMap, targetCoords)) {
-                if (const auto* unit = Occupant(units, neighbor.coords)) {
-                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
-                }
-            }
-
-            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
-        }
-
-        case CommandType::METEOR_TARGET_COMMAND: {
-            // High weight per enemy unit at or adjacent to target
-            if (!command.has_target()) return 6.0;  // Default if no target info
-
-            const Coords targetCoords(command.target().row(), command.target().column());
-            int enemyCount = 0;
-
-            // Count enemies at target
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) { enemyCount++; }
-            }
-
-            // Count enemies adjacent to target
-            for (const auto& neighbor : HexMapUtils::GetAdjacentTiles(hexMap, targetCoords)) {
-                if (const auto* unit = Occupant(units, neighbor.coords)) {
-                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
-                }
-            }
-
-            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
-        }
-
-        case CommandType::RAISE_DEAD_COMMAND: return 10.0;
-        case CommandType::HOLY_WAVE_COMMAND: return 8.0;
-
-        // Fire on enemy (context-dependent)
-        case CommandType::START_FIRE_COMMAND: {
-            // High if enemy at target, low otherwise
-            if (!command.has_target()) return 3.0;  // Default
-
-            const Coords targetCoords(command.target().row(), command.target().column());
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) {
-                    return 10.0;  // Enemy at target - high value
-                }
-            }
-            return 1.0;  // No enemy - low value
-        }
-
-        // === MEDIUM-HIGH OFFENSIVE (5.0-7.0) ===
-        // Direct damage melee
-        case CommandType::MELEE_COMMAND: return 7.0;
-        case CommandType::CHARGE_COMMAND: return 7.0;  // Damage + movement
-        case CommandType::CHALLENGE_DUEL_COMMAND: return 5.0;
-
-        // Control and tactical magic
-        case CommandType::CONTROL_COMMAND: return 6.0;
-        case CommandType::METEOR_CAST_COMMAND: return 6.0;  // Finish meteor
-
-        case CommandType::REDUCE_COMMAND: {
-            // High if enemy at target, zero otherwise
-            if (!command.has_target()) return 0.0;
-
-            const Coords targetCoords(command.target().row(), command.target().column());
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) {
-                    return 10.0;  // Enemy at target - very high value
-                }
-            }
-            return 0.0;  // No enemy - don't use
-        }
-
-        // === MOVEMENT - Context-dependent ===
-        case CommandType::MOVE_COMMAND: {
-            if (isDefender) {
-                return 0.0;  // Defenders don't move
-            }
-
-            // Attackers: weight based on distance improvement towards castle
-            if (!command.has_target()) return 4.0;  // Default if no target
-
-            // Get actor unit to determine battalion type and start position
-            const auto* actorUnit = units->Get(command.actor().value());
-            if (!actorUnit) return 4.0;  // Default if can't find actor
-
-            // Get battalion type for distance calculation
-            const auto battalionTypeId = actorUnit->battalion().type();
-            const auto battalionTypePtr = getBattalionType(battalionTypeId);
-            if (!battalionTypePtr) return 4.0;  // Default if can't get battalion type
-
-            // Get ActionPointDistances for this battalion type
-            const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);
-            const auto* apd = (*apdCache)->GetRaw(hexMap, mapId, battalionTypePtr, false, -1);
-            if (!apd) return 4.0;  // Default if can't get distances
-
-            // Calculate minimum distance from start to any castle
-            const Coords startCoords = actorUnit->location();
-            auto minStartDistance = ActionPointDistances::IMPOSSIBLE;
-            for (const auto& castleCoord : castleCoords) {
-                const auto dist = apd->Distance(startCoords, castleCoord);
-                if (dist < minStartDistance) { minStartDistance = dist; }
-            }
-
-            // Calculate minimum distance from end to any castle
-            const Coords endCoords(command.target().row(), command.target().column());
-            auto minEndDistance = ActionPointDistances::IMPOSSIBLE;
-            for (const auto& castleCoord : castleCoords) {
-                const auto dist = apd->Distance(endCoords, castleCoord);
-                if (dist < minEndDistance) { minEndDistance = dist; }
-            }
-
-            // Return weight based on distance improvement
-            // Higher weight if we're moving closer to castle
-            if (minStartDistance == ActionPointDistances::IMPOSSIBLE ||
-                minEndDistance == ActionPointDistances::IMPOSSIBLE) {
-                return 4.0;  // Default if distances are impossible
-            }
-
-            const auto improvement = static_cast<double>(minStartDistance - minEndDistance);
-            return std::max(0.0, improvement);
-        }
-
-        case CommandType::BRAVE_WATER_COMMAND: return 3.0;  // Tactical movement
-        case CommandType::SCOUT_COMMAND:
-            return 2.0;  // Information gathering
-
-        // Terrain manipulation
-        case CommandType::FREEZE_WATER_COMMAND: return 3.0;
-        case CommandType::BUILD_BRIDGE_COMMAND: return 3.0;
-
-        // === LOW VALUE DEFENSIVE/UTILITY (1.0-2.0) ===
-        case CommandType::EXTINGUISH_FIRE_COMMAND: {
-            // High if friendly at target, low otherwise
-            if (!command.has_target()) return 2.0;  // Default
-
-            const Coords targetCoords(command.target().row(), command.target().column());
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() == actorPlayerId) {
-                    return 8.0;  // Friendly at target - high value
-                }
-            }
-            return 1.0;  // No friendly - low value
-        }
-
-        case CommandType::UNIT_REST_COMMAND: return 1.5;
-        case CommandType::FORTIFY_COMMAND: return 2.0;
-
-        // Zero weight - don't use in simulation
-        case CommandType::REPAIR_COMMAND: return 0.0;
-        case CommandType::HIDE_COMMAND: return 0.0;
-        case CommandType::RELEASE_UNIT_COMMAND: return 0.0;
-
-        case CommandType::REINFORCE_COMMAND: return 10.0;
-        case CommandType::MANAGE_PRISONER: return 1.0;
-
-        // === ZERO WEIGHT - NEVER SELECT (0.0) ===
-        // Explicitly bad actions
-        case CommandType::FLEE_COMMAND: return 0.0;  // Never flee in simulation
-        case CommandType::RETREAT_COMMAND: return 0.0;
-        case CommandType::BECOME_OUTLAW_COMMAND: return 0.0;  // Never become outlaw
-        case CommandType::DISMISS_UNIT_COMMAND:
-            return 0.0;  // Never dismiss in combat
-
-        // Actions that are fine as a fallback
-        case CommandType::END_TURN_COMMAND: return 1.0;
-        case CommandType::UNIT_STOP_COMMAND: return 1.0;
-        case CommandType::METEOR_CANCEL_COMMAND: return 1.0;
-
-        // Setup commands (shouldn't appear in combat, but filter anyway)
-        case CommandType::PLACE_UNIT_COMMAND: return 10.0;
-        case CommandType::PLACE_HIDDEN_UNIT_COMMAND: return 1.0;
-        case CommandType::END_PLAYER_SETUP_COMMAND: return 1.0;
-
-        // Unknown/unhandled
-        case CommandType::UNKNOWN_COMMAND:
-        default: return 0.0;  // Don't select unknown commands
-    }
-}
-
-}  // namespace shardok
@@ -1,38 +0,0 @@
-//
-// Fast heuristic weighting for MCTS simulations
-// Provides O(1) weights based on command type and context
-//
-
-#ifndef EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
-#define EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma clang diagnostic pop
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-
-namespace shardok {
-
-// Fast heuristic-based command weighting for MCTS simulation policy
-// Avoids expensive score calculation while maintaining intelligent bias
-class AIHeuristicWeighting {
-public:
-    // Get weight for a command using fast heuristics with game context
-    // Returns weight >= 0.0, where 0.0 means "never select" and higher is more likely
-    static double GetCommandWeight(
-            const net::eagle0::shardok::api::CommandDescriptor& command,
-            const GameStateW& state,
-            const CoordsSet& castleCoords,
-            const APDCache* apdCache,
-            bool isDefender,
-            std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType);
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
@@ -0,0 +1,169 @@
+//
+// Created by dancrosby on 3/4/20.
+//
+
+#ifndef EAGLE0_AISCORECALCULATOR_HPP
+#define EAGLE0_AISCORECALCULATOR_HPP
+
+#include <future>
+
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
+#include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
+
+namespace shardok {
+
+using net::eagle0::shardok::api::GameStateView;
+using GameState = fb::GameState;
+using shardok::PlayerId;
+using std::future;
+using std::vector;
+
+using ScoreValue = double;
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
+
+class AIScoreCalculator {
+public:
+    struct IndexAndScore {
+        size_t index;
+        CommandType type;
+        ScoreValue lookaheadScore;
+        ScoreValue immediateScore;
+    };
+
+private:
+    [[nodiscard]] static auto DefenderScatterStrategyScoreForState(
+            const GameStateW &gameState,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto DefenderHoldCastlesStrategyScoreForState(
+            const GameStateW &gameState,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto FleeStrategyScoreForState(
+            const GameStateW &gameState,
+            PlayerId playerId) -> ScoreValue;
+
+    [[nodiscard]] static auto DefenderScoreForState(
+            const GameStateW &gameState,
+            const AIStrategy &defenderStrategy,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto AttackerScoreForState(
+            const GameStateW &gameState,
+            const AIStrategy &attackerStrategy,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    struct ImmediateAndLookaheadScore {
+        ScoreValue immediateScore;
+        future<ScoreValue> lookaheadScore;
+    };
+
+    static auto BasicLookaheadCalculator(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const shared_ptr<ShardokEngine> &innerEngine,
+            ScoreValue currentUtility,
+            const AIStrategy &attackerStrategy,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> ScoreValue;
+
+    static auto CalcOne(
+            PlayerId pid,
+            bool isDefender,
+            uint32_t commandIndex,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const std::shared_ptr<RandomGenerator> &randomGenerator,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> ImmediateAndLookaheadScore;
+
+    struct CommandEvaluationResult {
+        ScoreValue immediateScore;
+        ScoreValue lookaheadScore;
+    };
+
+    static auto EvaluateCommand(
+            PlayerId pid,
+            bool isDefender,
+            uint32_t commandIndex,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> CommandEvaluationResult;
+
+public:
+    [[nodiscard]] static auto GuessedStateScore(
+            bool isDefender,
+            const GameStateW &state,
+            const AIStrategy &aiStrategy,
+            const CoordsSet &allCastleCoords,
+            const SettingsGetter &settingsGetter,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> ScoreValue;
+
+    [[nodiscard]] static auto BestCommandIndex(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> IndexAndScore;
+
+    [[nodiscard]] static auto CommandScore(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            size_t commandIndex) -> ScoreValue;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AISCORECALCULATOR_HPP
@@ -16,7 +16,7 @@ auto HasAttachedHeroWithProfession(
           unit->attached_hero().profession_info().profession() == profession;
 }

-auto CastleClaimCapableAttackerUnitCount(const GameStateW &gameState) -> int {
+auto CastleClaimCapableAttackerUnitCount(const GameState *gameState) -> int {
    int count = 0;

    for (const auto *unit : *gameState->units()) {
@@ -32,7 +32,7 @@ auto CastleClaimCapableAttackerUnitCount(const GameStateW &gameState) -> int {
    return count;
 }

-auto PlayerInfoForPid(const GameStateW &gs, const PlayerId pid) -> const PlayerInfo * {
+auto PlayerInfoForPid(const GameState *gs, const PlayerId pid) -> const PlayerInfo * {
    if (gs->player_infos()) {
        for (const auto &pi : *gs->player_infos()) {
            if (pi->player_id() == pid) return pi;
@@ -7,7 +7,6 @@

 #include <vector>

-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/unit.hpp"
@@ -26,8 +25,8 @@ auto HasAttachedHeroWithProfession(
        const Unit *unit,
        net::eagle0::shardok::storage::fb::Profession profession) -> bool;

-auto CastleClaimCapableAttackerUnitCount(const GameStateW &gameState) -> int;
-auto PlayerInfoForPid(const GameStateW &, PlayerId pid) -> const PlayerInfo *;
+auto CastleClaimCapableAttackerUnitCount(const GameState *gameState) -> int;
+auto PlayerInfoForPid(const GameState *gs, PlayerId pid) -> const PlayerInfo *;

 }  // namespace shardok

@@ -3,7 +3,6 @@
 //

 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-
 namespace shardok {
 AIStrategy FleeStrategy = AIStrategy{AIStrategy::STRATEGY_FLEE};
 AIStrategy HoldCastlesStrategy = AIStrategy{AIStrategy::STRATEGY_HOLD_CASTLES};
@@ -24,46 +24,16 @@ int AIEvaluationCounter::GetCurrentCount() { return activeCount.load(); }
 auto CalculateTimeBudget(
        const PlayerId playerId,
        const GameSettingsSPtr &settings,
-        const GameStateW &state,
-        const size_t numCommands) -> AITimeBudget {
+        const GameStateW &state) -> AITimeBudget {
    const auto settingsGetter = settings->GetGetter();
    const auto castleCoords = AllCastleCoords(state->hex_map());

-    // Check if we're in setup phase
-    const bool isSetupPhase = state->status()->state() ==
-                              net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP;
-
-    // Get maximum budget cap from settings (in seconds)
-    const double maxBudgetSeconds =
-            settingsGetter.Backing().lookahead_time_budget_maximum_seconds();
-    const double maxBudgetMs = maxBudgetSeconds * 1000.0;
-
-    // During setup, use the setup-specific time budget
-    if (isSetupPhase) {
-        // Dynamic budget: msPerCommand × numCommands
-        const double msPerCommand =
-                settingsGetter.Backing().lookahead_time_budget_per_command_setup_ms();
-        const double budgetMs = msPerCommand * static_cast<double>(numCommands);
-
-        // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
-        const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
-        const auto remainingBudget =
-                std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
-
-        const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();
-
-        return AITimeBudget{
-                .remainingBudget = remainingBudget,
-                .minDepthRequired = minDepth,
-                .isCloseToEnemy = false};  // Not relevant during setup
-    }
-
    // Determine proximity (≤4 hex distance) - applies to both attackers and defenders
    bool isClose = false;
    const auto *units = state->units();

-    for (size_t i = 0; i < units->size() && !isClose; ++i) {
-        const auto *myUnit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size() && !isClose; ++i) {
+        const auto *myUnit = units->Get(i);
        if (myUnit->player_id() != playerId) continue;

        const auto &myCoords = myUnit->location();
@@ -73,8 +43,8 @@ auto CalculateTimeBudget(
        const Cube myCube = OffsetToCube(myCoords);

        // Check distance to enemy units
-        for (size_t j = 0; j < units->size(); ++j) {
-            const auto *enemyUnit = units->Get(static_cast<unsigned int>(j));
+        for (int j = 0; j < units->size(); ++j) {
+            const auto *enemyUnit = units->Get(j);
            if (enemyUnit->player_id() == playerId) continue;

            const auto &enemyCoords = enemyUnit->location();
@@ -102,19 +72,15 @@ auto CalculateTimeBudget(
        }
    }

-    // Get time budget from settings - dynamic based on number of commands
-    // Dynamic budget: msPerCommand × numCommands
-    const double msPerCommand =
-            isClose ? settingsGetter.Backing().lookahead_time_budget_per_command_close_ms()
-                    : settingsGetter.Backing().lookahead_time_budget_per_command_far_ms();
-    const double budgetMs = msPerCommand * static_cast<double>(numCommands);
+    // Get time budget from settings
+    const auto budget = std::chrono::duration<double>(
+            isClose ? settingsGetter.Backing().lookahead_time_budget_close_in_seconds()
+                    : settingsGetter.Backing().lookahead_time_budget_far_in_seconds());

-    // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
-    const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
-    const auto remainingBudget = std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
+    const auto remainingBudget = std::chrono::duration_cast<std::chrono::milliseconds>(budget);

    // Get minimum depth requirement
-    const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();
+    const int minDepth = settingsGetter.Backing().min_lookahead_turns();

    return AITimeBudget{
            .remainingBudget = remainingBudget,
@@ -31,18 +31,15 @@ public:
 // Configuration structure for iterative deepening time budget
 struct AITimeBudget {
    std::chrono::milliseconds remainingBudget;  // Time budget remaining (decremented as used)
-    size_t minDepthRequired;                    // Minimum depth from minLookaheadTurns
+    int minDepthRequired;                       // Minimum depth from minLookaheadTurns
    bool isCloseToEnemy;                        // Proximity flag for budget selection
 };

 // Calculate time budget based on proximity to enemies and castles
-// Time budget is calculated dynamically based on number of available commands:
-//   budget = msPerCommand × numCommands (clamped to 200-5000ms)
 auto CalculateTimeBudget(
        PlayerId playerId,
        const GameSettingsSPtr &settings,
-        const GameStateW &state,
-        size_t numCommands) -> AITimeBudget;
+        const GameStateW &state) -> AITimeBudget;

 }  // namespace shardok

@@ -5,7 +5,6 @@
 #include "AIUnitScoreCalculator.hpp"

 #include <algorithm>
-#include <cstdlib>

 #include "AIAttackLocations.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -89,8 +88,8 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
            break;
    }

-    const double battalionValue = battalionTypeMultiplier * (1.0 + armament / 100.0) *
-                                  (1.0 + training / 100.0) * (0.5 + morale / 100.0) *
+    const double battalionValue = battalionTypeMultiplier * (0.5 + armament / 100.0) *
+                                  (0.5 + training / 100.0) * (0.5 + morale / 100.0) *
                                  unit->battalion().size();

    const double heroValue =
@@ -99,7 +98,7 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
    return battalionValue + heroValue;
 }

-auto archeryValue(const Unit * /*unit*/) -> double {
+auto archeryValue(const Unit *unit) -> double {
    // TODO: make this depend on the value of the targets
    return kArcheryPossibleValue;
 }
@@ -114,7 +113,7 @@ auto reduceValue(const Unit *unit, const Terrain *unitTerrain) -> double {
        return 0.0;
 }

-auto fearValue(const Unit * /*unit*/) -> double {
+auto fearValue(const Unit *unit) -> double {
    // TODO: make this depend on the value of the targets
    return kFearPossibleValue;
 }
@@ -335,8 +334,7 @@ auto UnitValue(
        const AttackLocations &locationsThisSideCanAttackFrom,
        const CoordsSet &locationsInDangerFromEnemy,
        const ActionPointDistances *distances,
-        int meteorRange,
-        double meteorCastVigorCost) -> ScoreValue {
+        const SettingsGetter &settings) -> ScoreValue {
    const auto &location = unit->location();
    if (location.row() < 0) return 0;  // unplaced unit

@@ -344,8 +342,7 @@ auto UnitValue(
            unit->battalion().type() == net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD;

    const int coordsIndex = location.row() * map->column_count() + location.column();
-    const auto *terrain = map->terrain()->Get(coordsIndex);
-
+    const auto &terrain = map->terrain()->Get(coordsIndex);
    double castleMultiplier = 1.0;
    // Only give a multiplier for being in a castle if the castle is useful, and the unit is not
    // undead
@@ -361,8 +358,8 @@ auto UnitValue(
    {
        for (const auto adjacentCoords = HexMapUtils::GetAdjacentCoords(map, location);
             const auto &c : adjacentCoords) {
-            if (const auto *adjTerrain = GetTerrain(map, c);
-                adjTerrain && adjTerrain->modifier().fire().present()) {
+            if (const auto &adjTerrain = GetTerrain(map, c);
+                adjTerrain->modifier().fire().present()) {
                onFireMultiplier *= kAdjacentFireMultiplier;
            }
        }
@@ -381,8 +378,8 @@ auto UnitValue(
            roundsRemaining,
            attackerUnits,
            defenderUnits,
-            meteorRange,
-            meteorCastVigorCost);
+            settings.Backing().meteor_range(),
+            settings.Backing().meteor_cast_vigor_cost());

    // scouting values
    // attack range
@@ -417,7 +414,7 @@ auto UnitValue(
        if (const auto commandingUnitId = unit->commanding_unit_id(); commandingUnitId != -1) {
            const Unit *commandingUnit = nullptr;
            for (const Unit *attackerUnit : attackerUnits) {
-                if (attackerUnit && attackerUnit->unit_id() == commandingUnitId) {
+                if (attackerUnit->unit_id() == commandingUnitId) {
                    commandingUnit = attackerUnit;
                    break;
                }
@@ -425,7 +422,7 @@ auto UnitValue(

            if (commandingUnit == nullptr) {
                for (const Unit *defenderUnit : defenderUnits) {
-                    if (defenderUnit && defenderUnit->unit_id() == commandingUnitId) {
+                    if (defenderUnit->unit_id() == commandingUnitId) {
                        commandingUnit = defenderUnit;
                        break;
                    }
@@ -46,8 +46,7 @@ auto UnitValue(
        const AttackLocations &locationsThisSideCanAttackFrom,
        const CoordsSet &locationsInDangerFromEnemy,
        const ActionPointDistances *distances,
-        int meteorRange,
-        double meteorCastVigorCost) -> ScoreValue;
+        const SettingsGetter &settings) -> ScoreValue;

 }  // namespace shardok

@@ -4,12 +4,10 @@

 #include "AIVictoryConditionScoreCalculator.hpp"

-#include <algorithm>
-#include <ranges>
-
+#include "AIAttackLocations.hpp"
+#include "AIDistanceDebuf.hpp"
+#include "src/main/cpp/net/eagle0/common/ContainerUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIDistanceDebuf.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/victory_condition.hpp"

@@ -43,8 +41,8 @@ auto AttackerDebufForOnFireCriticalTile(
        const vector<const Unit*>& extinguishingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) -> double {
    double minDebuf = 99999.9;

@@ -60,8 +58,8 @@ auto AttackerDebufForOnFireCriticalTile(
                extinguishingUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost,
+                settings,
+                braveWaterActionPointCost,
                lateGame,
                /* includeUndead = */ false);
        if (newDebuf < minDebuf) minDebuf = newDebuf;
@@ -77,8 +75,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
        const vector<const Unit*>& claimableUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) -> double {
    return UNHELD_VALUE * DefenderDistanceBuf(
                                  criticalTileLocation,
@@ -87,8 +85,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
                                  claimableUnits,
                                  apdCache,
                                  alCache,
-                                  battalionTypeGetter,
-                                  braveWaterCost,
+                                  settings,
+                                  braveWaterActionPointCost,
                                  lateGame,
                                  /* includeUndead = */ false);
 }
@@ -100,8 +98,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
        const vector<const Unit*>& attackerUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) {
    const double baseUnitValue =
            defenderUnit->battalion().size() +
@@ -117,16 +115,19 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
                   attackerUnits,
                   apdCache,
                   alCache,
-                   battalionTypeGetter,
-                   braveWaterCost,
+                   settings,
+                   braveWaterActionPointCost,
                   lateGame,
                   /* includeUndead = */ false);
 }

 auto DefenderHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
-        const PlayerInfo* player) -> ScoreValue {
+        const PlayerInfo* player,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const SettingsGetter& settings) -> ScoreValue {
    ScoreValue total = 0.0;

    const auto rc = gameState->hex_map()->row_count();
@@ -151,13 +152,12 @@ auto DefenderHoldsCriticalTilesVictoryScore(
 }

 auto AttackerHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue {
+        const SettingsGetter& settings) -> ScoreValue {
    vector<const Unit*> playerUnits{};
    vector<const Unit*> claimablePlayerUnits{};
    for (const Unit* unit : *gameState->units()) {
@@ -173,6 +173,7 @@ auto AttackerHoldsCriticalTilesVictoryScore(
        return criticalTileLocations.size() * MAX_DEFENDER_HELD_VALUE;
    }

+    const int braveWaterActionPointCost = settings.Backing().brave_water_action_point_cost();
    const MapId mapId = apdCache->GetMapId(gameState->hex_map());

    ScoreValue total = 0.0;
@@ -199,8 +200,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                            claimablePlayerUnits,
                            apdCache,
                            alCache,
-                            battalionTypeGetter,
-                            braveWaterCost,
+                            settings,
+                            braveWaterActionPointCost,
                            IsLateGame(gameState));
                    total += BADLY_HELD_VALUE;
                }
@@ -212,8 +213,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                        playerUnits,
                        apdCache,
                        alCache,
-                        battalionTypeGetter,
-                        braveWaterCost,
+                        settings,
+                        braveWaterActionPointCost,
                        IsLateGame(gameState));
            }
        } else if (terrain->modifier().fire().present()) {
@@ -224,8 +225,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                    claimablePlayerUnits,
                    apdCache,
                    alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                    IsLateGame(gameState));
        } else {
            total -= AttackerDebufForUnoccupiedCriticalTile(
@@ -235,8 +236,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                    claimablePlayerUnits,
                    apdCache,
                    alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                    IsLateGame(gameState));
        }
    }
@@ -245,13 +246,12 @@ auto AttackerHoldsCriticalTilesVictoryScore(
 }

 auto LastPlayerStandingVictoryScore(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue {
-    if (!std::ranges::contains(
+        const SettingsGetter& settings) -> ScoreValue {
+    if (!common::Contains(
                *player->victory_conditions(),
                net::eagle0::shardok::storage::fb::
                        VictoryCondition_VICTORY_CONDITION_LAST_PLAYER_STANDING)) {
@@ -283,8 +283,8 @@ auto LastPlayerStandingVictoryScore(
                                                 playerUnits,
                                                 apdCache,
                                                 alCache,
-                                                 battalionTypeGetter,
-                                                 braveWaterCost,
+                                                 settings,
+                                                 5,
                                                 IsLateGame(gameState),
                                                 /* includeUndead = */ true);
    }
@@ -9,8 +9,6 @@

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -25,26 +23,27 @@ using std::vector;
 using ScoreValue = double;

 auto AttackerHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue;
+        const SettingsGetter& settings) -> ScoreValue;

 auto DefenderHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
-        const PlayerInfo* player) -> ScoreValue;
-
-auto LastPlayerStandingVictoryScore(
-        const GameStateW& gameState,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue;
+        const SettingsGetter& settings) -> ScoreValue;
+
+auto LastPlayerStandingVictoryScore(
+        const GameState* gameState,
+        const PlayerInfo* player,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const SettingsGetter& settings) -> ScoreValue;

 }  // namespace shardok

@@ -11,11 +11,11 @@
 namespace shardok {

 auto UnitIdsRequiringWaterCrossing(
-        const GameStateW &gameState,
+        const GameState *gameState,
        const PlayerId pid,
        const CoordsSet &destinations,
        const APDCache &apdCache,
-        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
+        const SettingsGetter &settings) -> vector<UnitId> {
    // Put out all the fires, except on bridges
    fb::HexMapW mapCopy = fb::CopyHexMap(gameState->hex_map());
    for (uint32_t index = 0; index < mapCopy->terrain()->size(); index++) {
@@ -36,7 +36,7 @@ auto UnitIdsRequiringWaterCrossing(
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != pid) continue;

-        const auto &battType = battalionTypeGetter(unit->battalion().type());
+        const auto &battType = settings.GetBattalionType(unit->battalion().type());

        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) {
            for (const Coords &destination : destinations) {
@@ -74,9 +74,10 @@ auto UnitIdsRequiringWaterCrossing(
 }

 auto UnitIdsToCreateWaterCrossing(
-        const GameStateW &gameState,
+        const GameState *gameState,
        const PlayerId pid,
-        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
+        const APDCache &apdCache,
+        const SettingsGetter &settings) -> vector<UnitId> {
    vector<UnitId> unitIds{};

    for (const auto *unit : *gameState->units()) {
@@ -87,7 +88,7 @@ auto UnitIdsToCreateWaterCrossing(
        if (!unit->has_attached_hero()) continue;

        const auto profession = unit->attached_hero().profession_info().profession();
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());

        if (profession == net::eagle0::shardok::storage::fb::Profession_ENGINEER ||
            (profession == net::eagle0::shardok::storage::fb::Profession_MAGE &&
@@ -195,17 +196,17 @@ auto WaterCrossingTiles(

 // Returns the set of tiles that the attacker should try to approach in order to bridge/freeze
 auto IntendedCrossingStarts(
-        const GameStateW &gameState,
+        const GameState *gameState,
        const vector<UnitId> &unitIdsCreatingCrossing,
        const CoordsSet &tilesToStartCrossingFrom,
+        const MapId &mapId,
        const APDCache &apdCache,
-        const BattalionTypeGetter &battalionTypeGetter) -> CoordsSet {
+        const SettingsGetter &settings) -> CoordsSet {
    CoordsSet intendedCrossingStarts(gameState->hex_map());
-    const MapId mapId = apdCache->GetMapId(gameState->hex_map());
    for (const UnitId uid : unitIdsCreatingCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
        const Coords &location = unit->location();
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());
        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);

        if (location.row() >= 0) {
@@ -218,111 +219,4 @@ auto IntendedCrossingStarts(
    return intendedCrossingStarts;
 }

-using Unit = net::eagle0::shardok::storage::fb::Unit;
-
-constexpr double kNoRequiredCrossingScore = std::numeric_limits<double>::max();
-constexpr double kNoCrossingCreatorsScore = std::numeric_limits<double>::min();
-
-auto WaterCrossingScore(
-        const PlayerId playerId,
-        const BattalionTypeGetter &battalionTypeGetter,
-        const GameStateW &gameState,
-        const CoordsSet &castleCoords,
-        const CoordsSet &startCrossingFrom,
-        const APDCache &apdCache) -> double {
-    uint32_t castleClaimCount = 0;
-    for (const auto *unit : *gameState->units()) {
-        if (unit->player_id() != playerId) continue;
-        const auto status = unit->status();
-        if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
-            status != net::eagle0::shardok::storage::fb::UnitStatus_RESERVE_UNIT)
-            continue;
-        if (!unit->has_attached_hero()) continue;
-
-        ++castleClaimCount;
-    }
-
-    CoordsSet destinations = castleCoords;
-    if (castleClaimCount < castleCoords.size()) {
-        destinations = CoordsSet(gameState->hex_map());
-        for (const auto *enemyUnit : *gameState->units()) {
-            if (enemyUnit->player_id() == playerId) continue;
-            const auto status = enemyUnit->status();
-            if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;
-            AssertValid(enemyUnit->location(), gameState->hex_map());
-            destinations.Add(enemyUnit->location());
-        }
-    }
-
-    const auto unitIdsRequiringCrossing = UnitIdsRequiringWaterCrossing(
-            gameState,
-            playerId,
-            castleCoords,
-            apdCache,
-            battalionTypeGetter);
-    if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;
-
-    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
-    if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;
-
-    double totalScore = 0;
-
-    const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
-
-    // First put a big penalty on the distance for units that can create a crossing
-    for (const UnitId uid : unitIdsCreatingCrossing) {
-        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
-        Coords location = unit->location();
-
-        int thisDistance;
-        if (location.row() < 0) thisDistance = 1000;
-        else {
-            const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
-
-            thisDistance = MinimumDistance(apd, location, startCrossingFrom);
-        }
-
-        totalScore -= thisDistance * 100.0;
-    }
-
-    // Now a smaller penalty for distance for units that need to cross, except if they block -- then
-    // a large penalty
-    for (const UnitId uid : unitIdsRequiringCrossing) {
-        // If this unit ID can also create a crossing, we already handled it
-        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
-
-        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
-        Coords location = unit->location();
-        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
-
-        int thisDistance;
-        if (location.row() < 0) thisDistance = 1000;
-        else { thisDistance = MinimumDistance(apd, location, startCrossingFrom); }
-
-        bool targetBlocks = false;
-        // If we're not capable of creating a crossing, don't get in the way of somebody that is.
-        for (const UnitId crossingUid : unitIdsCreatingCrossing) {
-            const auto *crossingCapableUnit = gameState->units()->Get(crossingUid);
-
-            // Don't check for units that aren't yet placed
-            if (crossingCapableUnit->location().row() < 0) continue;
-            AssertValid(crossingCapableUnit->location(), gameState->hex_map());
-
-            if (thisDistance <
-                MinimumDistance(apd, crossingCapableUnit->location(), startCrossingFrom)) {
-                targetBlocks = true;
-                break;
-            }
-        }
-        if (targetBlocks) continue;
-
-        totalScore -= thisDistance;
-    }
-
-    return totalScore;
-}
-
 }  // namespace shardok
@@ -5,8 +5,6 @@
 #ifndef EAGLE0_AIWATERCROSSINGCALCULATOR_HPP
 #define EAGLE0_AIWATERCROSSINGCALCULATOR_HPP

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -31,17 +29,18 @@ static inline void AssertValid(const Coords& c, const HexMap* hexMap) {

 // Units that need a water crossing to reach at least one of the destinations
 auto UnitIdsRequiringWaterCrossing(
-        const GameStateW& gameState,
+        const GameState* gameState,
        PlayerId pid,
        const CoordsSet& destinations,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
+        const SettingsGetter& settings) -> vector<UnitId>;

 // Units belonging to the player that are capable of creating water crossings
 auto UnitIdsToCreateWaterCrossing(
-        const GameStateW& gameState,
+        const GameState* gameState,
        PlayerId pid,
-        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
+        const APDCache& apdCache,
+        const SettingsGetter& settings) -> vector<UnitId>;

 // Whether a unit of the given type can reach destination from origin, given the current state
 // of the map
@@ -68,20 +67,12 @@ auto WaterCrossingTiles(

 // Returns the set of tiles that the attacker should try to approach in order to bridge/freeze
 auto IntendedCrossingStarts(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const vector<UnitId>& unitIdsCreatingCrossing,
        const CoordsSet& tilesToStartCrossingFrom,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> CoordsSet;
-
-// Calculate score based on water crossing strategy
-auto WaterCrossingScore(
-        PlayerId playerId,
-        const BattalionTypeGetter& battalionTypeGetter,
-        const GameStateW& gameState,
-        const CoordsSet& castleCoords,
-        const CoordsSet& startCrossingFrom,
-        const APDCache& apdCache) -> double;
+        const SettingsGetter& settings) -> CoordsSet;

 }  // namespace shardok

@@ -4,10 +4,8 @@

 #include "AIWaterCrossingCommandChooser.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "AIMinimumDistanceAndTarget.hpp"
+#include "src/main/cpp/net/eagle0/common/ContainerUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.hpp"

 namespace shardok {
@@ -18,11 +16,11 @@ constexpr ScoreValue kNoRequiredCrossingScore = std::numeric_limits<ScoreValue>:
 constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>::min();

 [[nodiscard]] auto AIWaterCrossingCommandChooser::WaterCrossingScore(
-        const BattalionTypeGetter &battalionTypeGetter,
-        const GameStateW &gameState,
+        const SettingsGetter &settingsGetter,
+        const GameState *gameState,
        const CoordsSet &castleCoords,
        const CoordsSet &startCrossingFrom) const -> ScoreValue {
-    uint32_t castleClaimCount = 0;
+    int castleClaimCount = 0;
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != playerId) continue;
        const auto status = unit->status();
@@ -51,13 +49,15 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
            playerId,
            castleCoords,
            apdCache,
-            battalionTypeGetter);
+            settingsGetter);
    if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;

    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
    if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;

+    fprintf(stderr, "%lu units require a water crossing\n", unitIdsRequiringCrossing.size());
+
    ScoreValue totalScore = 0;

    const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
@@ -65,7 +65,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
    // First put a big penalty on the distance for units that can create a crossing
    for (const UnitId uid : unitIdsCreatingCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords location = unit->location();

        int thisDistance;
@@ -83,10 +83,10 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
    // a large penalty
    for (const UnitId uid : unitIdsRequiringCrossing) {
        // If this unit ID can also create a crossing, we already handled it
-        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
+        if (common::Contains(unitIdsCreatingCrossing, uid)) continue;

        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords location = unit->location();
        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);

@@ -118,12 +118,12 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
 }

 auto AIWaterCrossingCommandChooser::StartCrossingFrom(
-        const BattalionTypeGetter &battalionTypeGetter,
-        const GameStateW &gameState,
+        const SettingsGetter &settingsGetter,
+        const GameState *gameState,
        const CoordsSet &castleCoords) const -> CoordsSet {
    CoordsSet startCrossingFrom(gameState->hex_map());

-    uint32_t castleClaimCount = 0;
+    int castleClaimCount = 0;
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != playerId) continue;
        const auto status = unit->status();
@@ -152,16 +152,16 @@ auto AIWaterCrossingCommandChooser::StartCrossingFrom(
            playerId,
            castleCoords,
            apdCache,
-            battalionTypeGetter);
+            settingsGetter);
    if (unitIdsRequiringCrossing.empty()) return startCrossingFrom;

    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
    if (unitIdsCreatingCrossing.empty()) return startCrossingFrom;

    for (const UnitId uid : unitIdsRequiringCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords origin = unit->location();

        // FIXME: this is just grabbing the first starting position, ideally we'd try them all
@@ -6,10 +6,10 @@
 #define EAGLE0_AIWATERCROSSINGCOMMANDCHOOSER_HPP

 #include <utility>
+#include <vector>

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/fb_helpers/FlatbufferWrapper.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
@@ -32,14 +32,14 @@ public:
        : playerId(pid),
          apdCache(std::move(apdCache)) {}

-    [[nodiscard]] auto StartCrossingFrom(
-            const BattalionTypeGetter &battalionTypeGetter,
-            const GameStateW &gameState,
+    auto StartCrossingFrom(
+            const SettingsGetter &settingsGetter,
+            const GameState *gameState,
            const CoordsSet &castleCoords) const -> CoordsSet;

    [[nodiscard]] auto WaterCrossingScore(
-            const BattalionTypeGetter &battalionTypeGetter,
-            const GameStateW &gameState,
+            const SettingsGetter &settingsGetter,
+            const GameState *gameState,
            const CoordsSet &castleCoords,
            const CoordsSet &startCrossingFrom) const -> ScoreValue;
 };
@@ -210,556 +210,4 @@ Where:
 - **Magnitude**: Indicates confidence/importance of the evaluation
 - **Relative scoring**: Only score differences matter, not absolute values

-This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
-
-## AIScoreCalculator Function Reference
-
-### Public Interface Functions
-
-#### `GuessedStateScore`
-**Purpose**: Evaluates the score of a game state from the perspective of the current AI strategy without performing any commands.
-
-**Parameters**:
- `isDefender`: Whether the AI is playing as defender
- `state`: Current game state to evaluate
- `aiStrategy`: Strategy being used (attack castles, hold castles, scatter, etc.)
- `allCastleCoords`: Set of all castle coordinates on the map
- `settingsGetter`: Game configuration and rules
- `apdCache`: Cached action point distances for movement calculations
- `alCache`: Cached attack locations for combat calculations
-
-**Returns**: Score value representing how favorable the state is for the evaluating player (positive = good, negative = bad)
-
-#### `CommandScore`
-**Purpose**: Evaluates the score for a specific command using lookahead search to consider future consequences.
-
-**Parameters**:
- `pid`: Player ID executing the command
- `isDefender`: Whether the player is a defender
- `remainingLookahead`: Depth of recursive search remaining
- `maxRepeatCount`: Number of random simulations for non-deterministic commands
- `guessedEngine`: Current game engine state
- `attackerStrategy`: Strategy being used by attackers
- `currentUtility`: Current game state score before command execution
- `settingsGetter`: Game configuration
- `allCastleCoords`: Castle locations
- `apdCache` & `alCache`: Cached distance/attack calculations
- `commandIndex`: Index of command to evaluate
- `deadline`: Time limit for computation
-
-**Returns**: Future containing the final score after lookahead evaluation
-
-### Internal Core Functions
-
-#### `BuildDecisionTree` (NEW)
-**Purpose**: Builds a complete decision tree containing all evaluated command paths up to the specified depth.
-
-**Process**:
-1. Filters commands using `AICommandFilter` to reduce search space
-2. For each command, calls `ExecuteCommandForTree` to build complete subtrees
-3. Returns full tree with all possible moves and their consequences
-4. Identifies best command within the complete tree structure
-
-**Returns**: `std::future<CommandDecisionTree>` containing the complete decision tree
-
-#### `BestCommandIndex` (Legacy - Wrapper)
-**Purpose**: Backward compatibility wrapper that uses `BuildDecisionTree` but returns traditional `IndexAndScore`.
-
-**Process**:
-1. Calls `BuildDecisionTree` to get complete tree
-2. Extracts best command information for compatibility
-3. Returns only the optimal command details in legacy format
-
-#### `ExecuteCommandForTree` (NEW)
-**Purpose**: Executes a command and creates a tree node with the resulting game state and scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Creates `CommandTreeNode` with command results and game state
-3. Calculates immediate score using `GuessedStateScore`
-4. Calls `RecursiveTreeBuilder` to populate child nodes if depth allows
-5. Calculates lookahead score from children (or uses immediate score)
-
-**Returns**: `std::unique_ptr<CommandTreeNode>` containing the command execution results and subtree
-
-#### `RecursiveTreeBuilder` (NEW)
-**Purpose**: Recursively populates child nodes of a tree node by building subtrees for subsequent moves.
-
-**Process**:
-1. Gets available commands for the next player
-2. Filters commands to reduce search space
-3. For each command, calls `ExecuteCommandForTree` to create child nodes
-4. Handles different command types (deterministic, odds-based, random)
-5. Populates the parent node's children vector with complete subtrees
-
-#### `CalcOne` (Legacy)
-**Purpose**: Executes a single command simulation with specified randomness and returns both immediate and lookahead scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Calculates immediate score using `GuessedStateScore`
-3. Initiates recursive lookahead calculation if depth remains
-4. Handles timeouts gracefully by returning default scores
-
-#### `EvaluateCommand`
-**Purpose**: Lower-level command evaluation that handles different command types appropriately.
-
-**Command Type Handling**:
- **Deterministic**: Single evaluation with average randomness (0.5)
- **Odds-based**: Two evaluations (success/failure) weighted by success probability
- **Non-deterministic**: Multiple evaluations with distributed random values, averaged
-
-#### `BasicLookaheadCalculator`
-**Purpose**: Recursive lookahead search that finds the best future command sequence and propagates scores backward.
-
-**Features**:
- Uses transposition table to cache previously computed positions
- Handles depth limits and terminal states
- Returns futures for asynchronous computation
- Stores results in transposition table for reuse
-
-### Strategy-Specific Scoring Functions
-
-#### `AttackerScoreForState`
-**Purpose**: Calculates state score from attacker perspective based on strategy type.
-
-**Strategy Support**:
- `STRATEGY_ATTACK_CASTLES`: Prioritizes capturing castle positions
- `STRATEGY_ATTACK_UNITS`: Focuses on eliminating defender units
- `STRATEGY_HOLD_CASTLES`: Maintains control of captured castles
- `STRATEGY_CROSS_RIVERS`: Special water crossing objectives
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `DefenderScoreForState`
-**Purpose**: Calculates state score from defender perspective.
-
-**Strategy Support**:
- `STRATEGY_HOLD_CASTLES`: Defend critical castle positions
- `STRATEGY_SCATTER`: Spread units to avoid elimination
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `AttackerUnitsScore`
-**Purpose**: Core unit valuation function that calculates total value of all units on the board with contextual modifiers.
-
-**Features**:
- Uses `UnitValue` for individual unit calculations
- Applies distance multipliers based on proximity to objectives
- Handles special cases like undead, VIP units, and scattered defenders
- Incorporates castle bonuses and environmental penalties
-
-### Specialized Strategy Functions
-
-#### `DefenderScatterStrategyScoreForState`
-**Purpose**: Implements scatter strategy scoring that rewards defensive units for staying far from enemies and friendlies.
-
-#### `DefenderHoldCastlesStrategyScoreForState`
-**Purpose**: Implements castle defense strategy with victory condition scoring.
-
-#### `FleeStrategyScoreForState`
-**Purpose**: Implements flee strategy that heavily penalizes remaining on the battlefield.
-
-### Utility Functions
-
-#### `AttackerMultiplierForTargetDistance`
-**Purpose**: Calculates distance-based scoring multipliers for attackers based on proximity to priority targets.
-
-**Features**:
- Uses recursive priority list evaluation
- Accounts for occupied vs. unoccupied targets
- Incorporates brave water crossing capabilities
- Uses cached action point distances for efficiency
-
-#### `CommandSorter`
-**Purpose**: Comparison function for ranking commands by lookahead score (primary) and immediate score (tiebreaker).
-
-#### `IsDeterministic`
-**Purpose**: Determines if a command type has predictable outcomes or requires random simulation.
-
-### Performance and Caching
-
-#### `EffectiveDistanceCache`
-**Purpose**: Memoization cache for expensive distance calculations between units and targets.
-
-#### `AttackerScorePerformanceLogger`
-**Purpose**: Performance monitoring system that tracks call frequency and timing for `AttackerScoreForState`.
-
-The function architecture supports parallel evaluation, caching, and recursive lookahead while maintaining separation between strategy-specific logic and core evaluation mechanics.
-
-## Decision Tree Data Structures (NEW)
-
-### CommandTreeNode
-**Purpose**: Represents a single command execution and its consequences in the decision tree.
-
-**Key Fields**:
- `commandIndex`: Index of the command in the original command list
- `commandType`: Type of command (MOVE, MELEE, END_TURN, etc.)
- `immediateScore`: Score of the game state immediately after this command
- `lookaheadScore`: Best achievable score considering future moves
- `resultingGameState`: Game state after command execution
- `children`: Vector of child nodes representing subsequent possible moves
- `playerId`, `depth`, `isDefender`: Metadata about the command context
-
-**Features**:
- Stores complete game state for each decision point
- Maintains parent-child relationships for tree traversal
- Supports both immediate and lookahead scoring
- Contains metadata for debugging and analysis
-
-### CommandDecisionTree
-**Purpose**: Complete decision tree containing all evaluated command paths from a given position.
-
-**Key Fields**:
- `rootNodes`: All possible first moves from the starting position
- `bestCommand`: Pointer to the optimal root command
- `maxDepth`: Maximum lookahead depth of the tree
- `totalNodes`: Total number of nodes in the tree (for statistics)
-
-**Features**:
- Provides complete visibility into AI decision-making process
- Enables analysis of alternative moves and their consequences
- Supports tree statistics and debugging information
- Maintains backward compatibility through `GetBestCommandIndex()`
-
-**Memory Management**:
- Uses `std::unique_ptr` for automatic memory cleanup
- `GameStateW` objects are stored directly (not shared pointers for simplicity)
- Tree structure ensures proper cleanup when nodes go out of scope
-
-### Tree vs. Legacy Approach Comparison
-
-| Aspect | Legacy (Single Best) | Tree-Based (Complete) |
-|--------|---------------------|----------------------|
-| **Output** | Best command only | Complete decision tree |
-| **Memory** | Minimal | Higher (stores all paths) |
-| **Analysis** | Limited visibility | Full decision transparency |
-| **Debugging** | Single command info | Complete move sequences |
-| **Performance** | Slightly faster | Comparable (same calculations) |
-| **Compatibility** | Direct usage | Wrapper maintains compatibility |
-
-### Usage Patterns
-
-**For AI Decision Making**:
-```cpp
-auto treeFuture = BuildDecisionTree(pid, isDefender, depth, maxRepeat,
-                                   engine, strategy, utility, settings,
-                                   castles, apdCache, alCache, deadline);
-CommandDecisionTree tree = treeFuture.get();
-size_t bestCommand = tree.bestCommand->commandIndex;
-```
-
-**For Analysis and Debugging**:
-```cpp
-CommandDecisionTree tree = treeFuture.get();
-// Examine all possible moves
-for (const auto& rootNode : tree.rootNodes) {
-    std::cout << "Command " << rootNode->commandIndex
-              << " Score: " << rootNode->lookaheadScore << std::endl;
-    // Traverse children to see consequences
-    for (const auto& child : rootNode->children) {
-        // ... analyze child moves
-    }
-}
-```
-
-**Legacy Compatibility**:
-```cpp
-// Existing code continues to work unchanged
-auto indexScoreFuture = BestCommandIndex(pid, isDefender, ...);
-IndexAndScore result = indexScoreFuture.get();
-size_t bestCommand = result.index;
-```
-
-The tree-based approach provides complete decision transparency while maintaining full backward compatibility with existing AI code.
-
-## MCTS Alternative: Randomness Handling Recommendations
-
-The new MCTS-based AI system is available in `MCTSAI.hpp/.cpp` and provides an alternative to the iterative deepening approach. However, the current MCTS implementation uses simplified randomness handling compared to the sophisticated approach in the original system.
-
-### Current MCTS Limitations
-
-1. **Expansion Phase**: Uses average rolls (0.5) for all commands during tree expansion
-2. **Simulation Phase**: Uses random command selection with average rolls
-3. **Missing**: No explicit chance nodes for commands with `HasOdds()`
-4. **Missing**: No multi-sample evaluation for stochastic commands
-
-### Recommended Improvements: Chance Node Integration
-
-#### 1. **Explicit Chance Nodes** (Highest Priority)
-
-For commands with `HasOdds()`, create explicit chance nodes in the MCTS tree:
-
-```cpp
-// During MCTSExpansion
-if (descriptor->HasOdds()) {
-    // Create TWO child nodes: success and failure
-    auto successNode = CreateMCTSNode(commandIndex, SUCCESS_VARIANT);
-    auto failureNode = CreateMCTSNode(commandIndex, FAILURE_VARIANT);
-
-    // Execute with deterministic rolls (matching original system)
-    ExecuteWithRoll(successNode, 1.0 - successChance/2.0);  // High roll
-    ExecuteWithRoll(failureNode, (1.0 - successChance)/2.0); // Low roll
-
-    // Set probability weights for selection
-    successNode->probabilityWeight = successChance;
-    failureNode->probabilityWeight = 1.0 - successChance;
-}
-```
-
-#### 2. **Weighted Selection for Chance Nodes**
-
-Modify `MCTSSelection` to handle chance nodes:
-
-```cpp
-if (node->isChanceNode) {
-    // Select based on probability distribution, not UCB1
-    return SelectByProbability(node->children);
-} else {
-    // Normal UCB1 selection for decision nodes
-    return node->GetBestChild(explorationConstant);
-}
-```
-
-#### 3. **Probability-Weighted Backpropagation**
-
-Update backpropagation to account for chance node probabilities:
-
-```cpp
-void MCTSBackpropagation(MCTSNode* node, double reward) {
-    while (node) {
-        node->visitCount++;
-
-        // Weight reward by probability for chance nodes
-        double weightedReward = reward;
-        if (node->parent && node->parent->isChanceNode) {
-            weightedReward *= node->probabilityWeight;
-        }
-
-        node->totalReward += weightedReward;
-        node->averageReward = node->totalReward / node->visitCount;
-        node = node->parent;
-    }
-}
-```
-
-#### 4. **Multi-Sample Commands**
-
-For commands without explicit odds but with randomness, use stratified sampling:
-
-```cpp
-// During expansion, create multiple child nodes with different rolls
-for (int sample = 0; sample < numSamples; ++sample) {
-    double roll = static_cast<double>(sample) / (numSamples - 1);
-    auto sampleNode = CreateMCTSNodeWithRoll(commandIndex, roll);
-    sampleNode->probabilityWeight = 1.0 / numSamples;
-}
-```
-
-### Benefits of Chance Node Integration
-
-1. **Accurate Evaluation**: Preserves the sophisticated randomness handling from the original system
-2. **Better Convergence**: MCTS can properly explore both success/failure outcomes
-3. **Realistic Simulations**: Tree accurately represents game's probability distributions
-4. **Comparable Results**: Makes MCTS results directly comparable to iterative deepening
-
-### Implementation Priority
-
-1. **Phase 1**: Add explicit chance nodes for `HasOdds()` commands
-2. **Phase 2**: Implement probability-weighted selection and backpropagation
-3. **Phase 3**: Add multi-sample support for general stochastic commands
-4. **Phase 4**: Optimize performance with lazy expansion of chance nodes
-
-### Alternative: Determinization Approach
-
-If explicit chance nodes prove too complex, consider **determinization**:
-
- Run multiple MCTS trees with different fixed random seeds
- Aggregate results across all determinizations
- Simpler to implement but potentially less accurate than explicit chance nodes
-
-### Switching Between AI Systems
-
-Both AI systems (`IterativeDeepeningAI` and `MCTSAI`) implement compatible interfaces. The algorithm is selected at **runtime** via the ShardokAIClient constructor:
-
-```cpp
-// Using Iterative Deepening (default)
-ShardokAIClient client(playerId, isDefender, hexMap, settings);
-// Or explicitly:
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::ITERATIVE_DEEPENING);
-
-// Using MCTS
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::MCTS);
-
-// Note: MCTS configuration can be customized via MCTSConfig:
-// - maxIterations: 10000 (max MCTS iterations per move)
-// - maxSimulationDepth: 10 (depth for rollout phase)
-// - maxTreeDepth: 20 (max tree depth to prevent stack overflow)
-// - explorationConstant: 1.414 (UCB1 exploration vs exploitation)
-// - useMultithreading: true (APD cache is thread-safe with TLS + mutex protection)
-// - numThreads: 4
-```
-
-The selection is made per AI client instance, allowing different algorithms for different players or game situations within the same server process.
-
-#### Direct AI Usage (Lower Level)
-
-Both AI systems can also be used directly:
-
-```cpp
-// Using Iterative Deepening directly
-auto iterativeAI = IterativeDeepeningAI(playerId, isDefender, strategy,
-                                       castleCoords, apdCache, alCache);
-auto result = iterativeAI.IterativeSearch(settings, state, commands, budget);
-
-// Using MCTS directly
-auto mctsAI = MCTSAI(playerId, isDefender, strategy,
-                    castleCoords, apdCache, alCache);
-auto result = mctsAI.Search(settings, state, commands, budget);
-```
-
-#### Algorithm Comparison
-
-| Feature | Iterative Deepening | MCTS |
-|---------|-------------------|------|
-| **Randomness Handling** | Sophisticated (chance nodes, multi-sample) | Simplified (average rolls) |
-| **Performance** | Single-threaded | Multithreaded |
-| **Search Type** | Fixed depth with iterative deepening | Adaptive with time budget |
-| **Memory Usage** | Lower | Higher (maintains tree) |
-| **Max Tree Depth** | Limited by lookahead setting | Limited by `maxTreeDepth` config (default: 20) |
-| **Tree Destruction** | Not applicable | Iterative (avoids stack overflow) |
-| **Best For** | Precise evaluation, production | Performance testing, fast decisions |
-
-The MCTS implementation provides a solid foundation. Known limitations:
-1. **Randomness Handling**: Simplified compared to iterative deepening (no explicit chance nodes)
-2. **Simulation Quality**: Uses random rollouts instead of sophisticated evaluation
-
-Note: The APD cache is fully thread-safe using thread-local storage and mutex-protected shared cache.
-
-Adding chance node handling and ensuring thread safety would make it a superior replacement for the iterative deepening approach while maintaining the sophisticated randomness evaluation that makes the current system effective.
-
-## MCTS Configuration Options
-
-The MCTS AI system provides extensive configuration through the `MCTSConfig` structure:
-
-### Core MCTS Parameters
-
-```cpp
-struct MCTSConfig {
-    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
-    int maxSimulationDepth = 1000;       // Maximum depth for rollout
-    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
-    bool useMultithreading = true;       // Enable parallel MCTS
-    int numThreads = 16;                 // Number of threads for parallel MCTS (when enabled)
-    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
-    bool enableTranspositionDetection = true;  // Enable pruning of duplicate states
-    double immediateScoreTieBreakThreshold = 5.0;  // When avg rewards differ by less than this, prefer higher immediate score
-    double visitCountTolerance = 0.05;  // Treat visit counts as equal if within this % of best count
-    bool enableImmediateScoreInUCB1 = true;  // Apply immediate score tie-breaking in UCB1 selection too
-};
-```
-
-### Exploration vs Exploitation
-
- **`explorationConstant`**: Controls the exploration vs exploitation balance in UCB1 selection
-  - Higher values (>1.414): More exploration of unvisited nodes
-  - Lower values (<1.414): More exploitation of known good moves
-  - Default: 1.414 (√2, theoretical optimum for UCB1)
-
-### Tree Structure Limits
-
- **`maxTreeDepth`**: Prevents stack overflow in deep game trees
-  - Default: 2000 (very high limit for most tactical scenarios)
-  - Terminal detection stops expansion when this depth is reached
-
- **`maxSimulationDepth`**: Controls rollout length during simulation phase
-  - Default: 1000 (sufficient for most tactical scenarios)
-  - Longer simulations provide more accurate estimates but use more time
-
-### Multithreading Configuration
-
- **`useMultithreading`**: Enable/disable parallel MCTS execution
-  - Default: true (takes advantage of modern multi-core CPUs)
-  - Requires thread-safe game engine and scoring components
-
- **`numThreads`**: Number of worker threads for parallel tree building
-  - Default: 16 (adjust based on available CPU cores)
-  - More threads can improve search speed but with diminishing returns
-
-### Simulation Policies
-
-The `MCTSSimulationPolicy` enum controls how commands are selected during the rollout phase:
-
- **`RANDOM`**: Pure random selection from all available commands
-  - Fastest but least informed simulations
-  - Good baseline for testing MCTS convergence
-
- **`FILTERED_RANDOM`**: Random selection from AICommandFilter-approved commands
-  - Eliminates obviously bad moves (moving away from objectives, etc.)
-  - Better simulation quality with minimal overhead
-
- **`BEST_IMMEDIATE`**: Always choose command with highest immediate score
-  - Most informed simulations
-  - Slower but higher quality rollouts
-  - Default setting for production use
-
- **`WEIGHTED_BEST_IMMEDIATE`**: Random selection weighted by immediate score ranking
-  - Balances exploration with informed choice
-  - Alternative to pure greedy selection
-
-### Transposition Detection
-
- **`enableTranspositionDetection`**: Enable pruning of duplicate game states
-  - Default: true (improves search efficiency)
-  - Uses hash-based state identification
-  - Prevents wasted computation on equivalent positions reached via different move sequences
-
-### Immediate Score Tie-Breaking
-
-These settings address MCTS's tendency to choose indirect paths when direct paths lead to the same outcome:
-
- **`immediateScoreTieBreakThreshold`**: Score difference threshold for tie-breaking
-  - Default: 5.0 (when backpropagated rewards differ by less than this, prefer immediate score)
-  - Helps AI choose direct moves over equivalent indirect sequences
-  - Improves user experience by reducing unnecessary intermediate moves
-
- **`visitCountTolerance`**: Visit count equality threshold for tie-breaking
-  - Default: 0.05 (5% tolerance - visit counts within this percentage are considered equal)
-  - Prevents minor visit count differences from overriding immediate score preferences
-
- **`enableImmediateScoreInUCB1`**: Apply immediate score tie-breaking during exploration
-  - Default: true (consistent tie-breaking in both exploration and final selection)
-  - When UCB1 values are very close, prefer nodes with higher immediate scores
-  - Improves convergence on direct paths to objectives
-
-### Usage Example
-
-```cpp
-// Custom MCTS configuration for performance testing
-MCTSConfig config;
-config.explorationConstant = 2.0;  // More exploration
-config.simulationPolicy = MCTSSimulationPolicy::FILTERED_RANDOM;  // Faster rollouts
-config.numThreads = 8;  // Reduce threads for testing environment
-config.immediateScoreTieBreakThreshold = 10.0;  // More aggressive tie-breaking
-
-MCTSAI ai(playerId, isDefender, strategy, castleCoords, apdCache, alCache, config);
-```
-
-### Configuration Recommendations
-
-**For Production Use:**
- Use default settings for balanced performance and quality
- Consider reducing `numThreads` on systems with limited CPU cores
- `BEST_IMMEDIATE` simulation policy provides highest quality decisions
-
-**For Performance Testing:**
- `FILTERED_RANDOM` or `RANDOM` simulation policies for faster rollouts
- Lower `explorationConstant` (1.0) for more exploitation
- Disable transposition detection for baseline comparison
-
-**For Analysis/Debugging:**
- Single-threaded execution (`useMultithreading = false`) for deterministic results
- Higher `immediateScoreTieBreakThreshold` to emphasize direct paths
- `BEST_IMMEDIATE` simulation for most predictable behavior
-
-The configuration system allows fine-tuning MCTS behavior for different scenarios while maintaining compatibility with the existing AI infrastructure.
+This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
@@ -1,16 +1,5 @@
 load("//tools:copts.bzl", "COPTS")

-cc_library(
-    name = "ai_common_types",
-    hdrs = ["AICommonTypes.hpp"],
-    copts = COPTS,
-    visibility = ["//visibility:public"],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:battalion_type",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-    ],
-)
-
 cc_library(
    name = "ai_attacker_strategy_selector",
    srcs = ["AIAttackerStrategySelector.cpp"],
@@ -22,7 +11,6 @@ cc_library(
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_flee_decision_calculator",
        ":ai_score_utilities",
        ":ai_strategy",
        ":ai_water_crossing_command_chooser",
@@ -39,15 +27,14 @@ cc_library(
    hdrs = ["AIAttackGroups.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_common_types",
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:hex_map_cc_fbs",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
@@ -59,10 +46,6 @@ cc_library(
    srcs = ["AIAttackLocations.cpp"],
    hdrs = ["AIAttackLocations.hpp"],
    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
    deps = [
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/map:terrain",
@@ -87,7 +70,6 @@ cc_library(
        ":ai_score_utilities",
        ":ai_strategy",
        ":ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
@@ -101,14 +83,11 @@ cc_library(
    hdrs = ["AIDistanceDebuf.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_common_types",
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
@@ -137,93 +116,26 @@ cc_library(
    hdrs = ["AIScoreUtilities.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
    ],
 )

-cc_library(
-    name = "ai_flee_decision_calculator",
-    srcs = ["AIFleeDecisionCalculator.cpp"],
-    hdrs = ["AIFleeDecisionCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_score_utilities",
-        ":ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "ai_heuristic_weighting",
-    srcs = ["AIHeuristicWeighting.cpp"],
-    hdrs = ["AIHeuristicWeighting.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "ai_command_evaluator",
-    srcs = ["AICommandEvaluator.cpp"],
-    hdrs = ["AICommandEvaluator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_command_filter",
-        ":ai_strategy",
-        ":transposition_table",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_cube_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
 cc_library(
    name = "ai_command_filter",
    srcs = ["AICommandFilter.cpp"],
    hdrs = ["AICommandFilter.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
-        ":ai_common_types",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
@@ -235,16 +147,22 @@ cc_library(
 )

 cc_library(
-    name = "transposition_table",
-    srcs = ["TranspositionTable.cpp"],
-    hdrs = ["TranspositionTable.hpp"],
+    name = "ai_score_calculator",
+    srcs = ["AIScoreCalculator.cpp"],
+    hdrs = ["AIScoreCalculator.hpp"],
    copts = COPTS,
    visibility = [
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        ":ai_attacker_strategy_selector",
+        ":ai_command_filter",
+        ":ai_unit_score_calculator",
+        ":ai_victory_condition_score_calculator",
+        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library/view_filters:game_state_guesser",
    ],
 )

@@ -254,13 +172,11 @@ cc_library(
    hdrs = ["AIStrategy.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
        ":ai_attack_groups",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
    ],
 )

@@ -270,7 +186,6 @@ cc_library(
    hdrs = ["AIUnitScoreCalculator.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
@@ -281,6 +196,26 @@ cc_library(
    ],
 )

+cc_library(
+    name = "ai_victory_condition_score_calculator",
+    srcs = ["AIVictoryConditionScoreCalculator.cpp"],
+    hdrs = ["AIVictoryConditionScoreCalculator.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
+    ],
+    deps = [
+        ":ai_attack_groups",
+        ":ai_attack_locations",
+        ":ai_distance_debuf",
+        ":ai_score_utilities",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
+    ],
+)
+
 cc_library(
    name = "ai_water_crossing_calculator",
    srcs = ["AIWaterCrossingCalculator.cpp"],
@@ -288,14 +223,10 @@ cc_library(
    copts = COPTS,
    visibility = [
        "//src/main/cpp/net/eagle0/shardok:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
-        ":ai_common_types",
        ":ai_minimum_distance_and_target",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
        "//src/main/cpp/net/eagle0/shardok/library/fb_helpers:hex_map_helpers",
@@ -326,7 +257,6 @@ cc_library(
    hdrs = ["AITimeBudget.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
@@ -345,18 +275,16 @@ cc_library(
    hdrs = ["IterativeDeepeningAI.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
        ":ai_attacker_strategy_selector",
-        ":ai_command_evaluator",
        ":ai_defender_strategy_selector",
+        ":ai_score_calculator",
        ":ai_time_budget",
        ":ai_water_crossing_command_chooser",
        "//src/main/cpp/net/eagle0/common:time_utils",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
@@ -364,13 +292,21 @@ cc_library(
 )

 cc_library(
-    name = "ai_config",
-    hdrs = ["AIConfig.hpp"],
+    name = "ai_flee_decision_calculator",
+    srcs = ["AIFleeDecisionCalculator.cpp"],
+    hdrs = ["AIFleeDecisionCalculator.hpp"],
    copts = COPTS,
    visibility = [
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
+    deps = [
+        ":ai_score_utilities",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
+        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
+    ],
 )

 cc_library(
@@ -381,21 +317,15 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":ai_attacker_strategy_selector",
-        ":ai_config",
        ":ai_defender_strategy_selector",
        ":ai_flee_decision_calculator",
-        ":ai_iterative_deepening",  # Direct dependency for runtime selection
+        ":ai_iterative_deepening",
+        ":ai_score_calculator",
        ":ai_time_budget",
        ":ai_water_crossing_command_chooser",
        "//src/main/cpp/net/eagle0/common:time_utils",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:shardok_mcts_ai",  # MCTS with abstraction layer
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:mcts_optimized_ai_score_calculator",  # Bounded linear scorer for MCTS
-        "//src/main/cpp/net/eagle0/shardok/ai/score:normalized_ai_score_calculator",  # Normalized [0,1] scorer for ML training
-        "//src/main/cpp/net/eagle0/shardok/ai/score:standard_ai_score_calculator",  # Standard unbounded scorer (default)
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/util:game_state_dumper",
        "@com_google_protobuf//:protobuf",
    ],
 )
@@ -10,9 +10,8 @@
 #include <utility>

 #include "AIAttackerStrategySelector.hpp"
-#include "AICommandEvaluator.hpp"
-#include "TranspositionTable.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/common/TimeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"

 namespace shardok {
@@ -24,16 +23,14 @@ IterativeDeepeningAI::IterativeDeepeningAI(
        const bool isDefender,
        AIStrategy strategy,
        const CoordsSet& castleCoords,
-        const AIScoreCalculator& scorer,
        const APDCache& apdCache,
-        BattalionTypeGetter battalionTypeGetter)
+        const ALCache& alCache)
    : playerId(playerId),
      isDefender(isDefender),
      strategy(std::move(strategy)),
      castleCoords(castleCoords),
-      scorer(scorer),
      apdCache(apdCache),
-      battalionTypeGetter(std::move(battalionTypeGetter)) {}  // Move the function object
+      alCache(alCache) {}

 auto IterativeDeepeningAI::IterativeSearch(
        const GameSettingsSPtr& settings,
@@ -46,11 +43,6 @@ auto IterativeDeepeningAI::IterativeSearch(
    const auto initialBudgetMs = initialBudget.remainingBudget;
    SearchResult result;

-    // Increment TT age for replacement strategy (new search)
-    g_transpositionTable.incrementAge();
-
-    // DEBUG: Clear TT to see if that's causing the suspicious depth reaching
-    // g_transpositionTable.clear();  // Uncomment to test without cross-search caching
    if (commands.empty()) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
        printf("ID AI: Commands are empty, returning early\n");
@@ -59,19 +51,24 @@ auto IterativeDeepeningAI::IterativeSearch(
        return result;
    }

-    // Check if we're in SET_UP phase and enforce maximum depth limit
+    // Check if we're in SET_UP phase
    bool isSetupPhase =
            (state->status()->state() ==
             net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP);
-    // Limit depth to prevent thread pool exhaustion and keep search reasonable
-    size_t maxDepth = isSetupPhase ? 2 : 8;
+    int maxDepth = isSetupPhase ? 2 : std::numeric_limits<int>::max();

    // Calculate current utility and create engine once for all command evaluations
    const auto& settingsGetter = settings->GetGetter();
    const auto guessedEngine = ShardokEngine(settings, state);
    const auto maxRepeatCount = settingsGetter.Backing().ai_utility_repeat_count();
-    const ScoreValue currentUtility =
-            scorer.GuessedStateScore(isDefender, state, strategy, castleCoords);
+    const ScoreValue currentUtility = AIScoreCalculator::GuessedStateScore(
+            isDefender,
+            state,
+            strategy,
+            castleCoords,
+            settingsGetter,
+            apdCache,
+            alCache);

    // Initialize data structures for tracking scores at each depth
    scoresByDepth.clear();
@@ -79,10 +76,10 @@ auto IterativeDeepeningAI::IterativeSearch(
    highestDepthCompleted.clear();
    highestDepthCompleted.resize(commands.size(), 0);

-    size_t currentDepth = 1;
+    int currentDepth = 1;
    size_t previousBestCommand = 0;  // Track best command from previous depth
    size_t evaluatedCountAtHighestDepth = 0;
-    auto completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
+    EvaluationCompletionReason completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;

    // Main iterative deepening loop
    while ((currentDepth == 1 || !IsTimeExpired(timeBudget)) && currentDepth <= maxDepth) {
@@ -92,37 +89,27 @@ auto IterativeDeepeningAI::IterativeSearch(
                scoresByDepth,
                highestDepthCompleted);

-        size_t evaluatedCount = 0;
+        int evaluatedCount = 0;
        bool allEvaluated = true;
        bool allEndTurnCommands = true;  // Track if all commands are END_TURN

-        // Start all command evaluations for this depth
-        std::vector<std::pair<size_t, std::future<SearchResult>>> futures;
-        futures.reserve(sortedIndices.size());
-
+        // Try to evaluate all commands at this depth, within budget constraints
        for (size_t cmdIndex : sortedIndices) {
            if (currentDepth > 1 && IsTimeExpired(timeBudget)) {
                allEvaluated = false;
                break;
            }

-            auto future = SearchCommandAtDepthWithEngine(
+            auto cmdResult = SearchCommandAtDepthWithEngine(
                    guessedEngine,
-                    scorer,
+                    settingsGetter,
                    maxRepeatCount,
                    commands,
                    cmdIndex,
-                    currentDepth,  // Pass current iteration depth as desired search depth
+                    currentDepth,
                    currentUtility,
                    timeBudget);

-            futures.emplace_back(cmdIndex, std::move(future));
-        }
-
-        // Now wait for all futures and collect results
-        for (auto& [cmdIndex, future] : futures) {
-            auto cmdResult = future.get();
-
            // Ensure scoresByDepth[cmdIndex] has enough space
            if (scoresByDepth[cmdIndex].size() <= currentDepth) {
                scoresByDepth[cmdIndex].resize(currentDepth + 1);
@@ -155,13 +142,13 @@ auto IterativeDeepeningAI::IterativeSearch(
            // Log if best command changed from previous depth
            if (currentDepth > 1 && currentBestCommand != previousBestCommand) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
-                printf("ID AI: Best command changed at depth %lu:\n", currentDepth);
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                printf("ID AI: Best command changed at depth %d:\n", currentDepth);
+                printf("  Depth %d best: command %zu (score %.2f) - %s\n",
                       currentDepth - 1,
                       previousBestCommand,
                       scoresByDepth[previousBestCommand][currentDepth - 1],
                       commands[previousBestCommand].DebugString().c_str());
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                printf("  Depth %d best: command %zu (score %.2f) - %s\n",
                       currentDepth,
                       currentBestCommand,
                       currentBestScore,
@@ -188,12 +175,12 @@ auto IterativeDeepeningAI::IterativeSearch(
        // This indicates we've hit END_TURN in the lookahead
        if (currentDepth > 1 && evaluatedCount > 0) {
            bool scoresUnchanged = true;
-            size_t unchangedCount = 0;
+            int unchangedCount = 0;

            for (size_t i = 0; i < sortedIndices.size() && i < evaluatedCount; ++i) {
+                size_t cmdIndex = sortedIndices[i];
                // This command was evaluated at both current and previous depth
-                if (size_t cmdIndex = sortedIndices[i];
-                    scoresByDepth[cmdIndex].size() > currentDepth &&
+                if (scoresByDepth[cmdIndex].size() > currentDepth &&
                    scoresByDepth[cmdIndex].size() > currentDepth - 1) {
                    // Check if score changed between depth N-1 and depth N
                    if (std::abs(
@@ -217,11 +204,10 @@ auto IterativeDeepeningAI::IterativeSearch(
        // Check if we've used more than 50% of total budget
        auto totalElapsed = std::chrono::steady_clock::now() - startTime;
        auto totalElapsedMs = std::chrono::duration_cast<std::chrono::milliseconds>(totalElapsed);
-        double budgetUsedPercent = static_cast<double>(totalElapsedMs.count()) /
-                                   static_cast<double>(initialBudgetMs.count());
+        double budgetUsedPercent = (double)totalElapsedMs.count() / initialBudgetMs.count();

        if (budgetUsedPercent > 0.5) {
-            printf("ID AI: Stopping after depth %lu - used %.1f%% of time budget\n",
+            printf("ID AI: Stopping after depth %d - used %.1f%% of time budget\n",
                   currentDepth,
                   budgetUsedPercent * 100);
            completionReason = EvaluationCompletionReason::NOT_ENOUGH_TIME_TO_CONTINUE;
@@ -256,8 +242,6 @@ auto IterativeDeepeningAI::IterativeSearch(
               result.availableCommandCount);
    }

-    // Print TranspositionTable statistics
-    g_transpositionTable.printStats();
    return result;
 }

@@ -267,16 +251,16 @@ bool IterativeDeepeningAI::IsTimeExpired(const AITimeBudget& budget) {

 auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
        const ShardokEngine& guessedEngine,
-        const AIScoreCalculator& scorer,
+        const GameSettings::Getter& settingsGetter,
        const int maxRepeatCount,
        const std::vector<CommandProto>& commands,
        const size_t commandIndex,
-        const int desiredDepth,
+        const int depth,
        const ScoreValue currentUtility,
-        AITimeBudget& timeBudget) const -> std::future<SearchResult> {
+        AITimeBudget& timeBudget) const -> SearchResult {
    SearchResult result;
    result.bestCommandIndex = commandIndex;
-    result.depthAchieved = desiredDepth;
+    result.depthAchieved = depth;
    result.searchCompleted = true;
    result.minimumDepthCompleted = true;
    result.availableCommandCount = commands.size();
@@ -284,62 +268,55 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(

    if (commandIndex >= commands.size()) {
        result.bestScore = 0.0;
-        std::promise<SearchResult> p;
-        p.set_value(result);
-        return p.get_future();
+        return result;
    }

-    // Track concurrent evaluations and adjust time accounting
-    AIEvaluationCounter counter;
-    const auto startTime = std::chrono::steady_clock::now();
+    try {
+        // Track concurrent evaluations and adjust time accounting
+        AIEvaluationCounter counter;
+        const auto startTime = std::chrono::steady_clock::now();

-    // Calculate deadline from remaining time budget
-    const auto deadline = startTime + timeBudget.remainingBudget;
+        // Use CommandScore to evaluate the specific command at the given depth
+        const auto commandScore = AIScoreCalculator::CommandScore(
+                playerId,
+                isDefender,
+                depth,
+                maxRepeatCount,
+                guessedEngine,
+                strategy,
+                currentUtility,
+                settingsGetter,
+                castleCoords,
+                apdCache,
+                alCache,
+                commandIndex);

-    // Create command evaluator for lookahead search
-    AICommandEvaluator evaluator(scorer, apdCache, battalionTypeGetter);
+        // Calculate time used and adjust based on concurrent evaluations
+        const auto elapsed = std::chrono::steady_clock::now() - startTime;
+        const int concurrentCount = counter.GetCurrentCount();
+        const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
+        const auto adjustedElapsedMs =
+                std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);

-    // Get the future from EvaluateCommand - don't wait yet
-    // Note: EvaluateCommand expects remainingLookahead, not desiredDepth
-    // desiredDepth 1 = evaluate immediate (remainingLookahead 0)
-    // desiredDepth 2 = look 1 move ahead (remainingLookahead 1)
-    // desiredDepth N = look N-1 moves ahead (remainingLookahead N-1)
-    auto commandScoreFuture = evaluator.EvaluateCommand(
-            playerId,
-            isDefender,
-            desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
-            maxRepeatCount,
-            guessedEngine,
-            strategy,
-            currentUtility,
-            castleCoords,
-            commandIndex,
-            deadline);
+        // Deduct adjusted time from remaining budget
+        timeBudget.remainingBudget -= adjustedElapsedMs;

-    // Calculate time and adjust budget before waiting
-    // This is needed because we need to update timeBudget synchronously
-    const auto commandScore = commandScoreFuture.get();
+        result.bestScore = commandScore;
+    } catch (const std::exception& e) {
+        // If evaluation fails, return a neutral score rather than crashing
+#if DEBUG_ITERATIVE_DEEPENING_TIMINGS
+        printf("SearchCommandAtDepthWithEngine: evaluation failed with exception: %s\n", e.what());
+#endif
+        result.bestScore = 0.0;
+    }

-    const auto elapsed = std::chrono::steady_clock::now() - startTime;
-    const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
-    const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
-    const auto adjustedElapsedMs =
-            std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);
-
-    // Deduct adjusted time from remaining budget
-    timeBudget.remainingBudget -= adjustedElapsedMs;
-
-    result.bestScore = commandScore;
-
-    std::promise<SearchResult> p;
-    p.set_value(result);
-    return p.get_future();
+    return result;
 }

 auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(
-        const size_t currentDepth,
+        int currentDepth,
        const std::vector<std::vector<ScoreValue>>& scoresByDepth,
-        const std::vector<size_t>& highestDepthCompleted) -> std::vector<size_t> {
+        const std::vector<int>& highestDepthCompleted) const -> std::vector<size_t> {
    std::vector<size_t> indices(scoresByDepth.size());
    std::iota(indices.begin(), indices.end(), 0);

@@ -349,21 +326,11 @@ auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(
    }

    // Sort by score at previous depth
-    const size_t prevDepth = currentDepth - 1;
-    std::ranges::sort(indices, [&](const size_t a, const size_t b) {
-        // Bounds check - if indices are out of range, or inner vectors are too small, treat as not
-        // evaluated
-        if (a >= scoresByDepth.size() || b >= scoresByDepth.size() ||
-            a >= highestDepthCompleted.size() || b >= highestDepthCompleted.size()) {
-            return a < b;  // Maintain stable order for out-of-bounds indices
-        }
-
-        // Check if the scores for previous depth exist
+    int prevDepth = currentDepth - 1;
+    std::sort(indices.begin(), indices.end(), [&](size_t a, size_t b) {
+        // Only consider commands that were evaluated at previous depth
        if (highestDepthCompleted[a] >= prevDepth && highestDepthCompleted[b] >= prevDepth) {
-            // Additional safety check for inner vector size
-            if (scoresByDepth[a].size() > prevDepth && scoresByDepth[b].size() > prevDepth) {
-                return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
-            }
+            return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
        }
        // Commands not evaluated at prev depth go to the end
        return highestDepthCompleted[a] >= prevDepth;
@@ -374,7 +341,7 @@ auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(

 auto IterativeDeepeningAI::SelectBestResult(
        const std::vector<std::vector<ScoreValue>>& scoresByDepth,
-        const std::vector<size_t>& highestDepthCompleted) -> SearchResult {
+        const std::vector<int>& highestDepthCompleted) const -> SearchResult {
    SearchResult result;
    result.bestScore = -std::numeric_limits<ScoreValue>::infinity();
    result.searchCompleted = false;
@@ -382,8 +349,9 @@ auto IterativeDeepeningAI::SelectBestResult(
    // Find the command with best score at its highest evaluated depth
    for (size_t i = 0; i < scoresByDepth.size(); ++i) {
        if (highestDepthCompleted[i] > 0) {
-            const size_t depth = highestDepthCompleted[i];
-            if (ScoreValue score = scoresByDepth[i][depth]; score > result.bestScore) {
+            int depth = highestDepthCompleted[i];
+            ScoreValue score = scoresByDepth[i][depth];
+            if (score > result.bestScore) {
                result.bestScore = score;
                result.bestCommandIndex = i;
                result.depthAchieved = depth;
@@ -6,13 +6,11 @@
 #define EAGLE0_ITERATIVEDEEPENINGAI_HPP

 #include <chrono>
-#include <future>
 #include <vector>

 #include "AIStrategy.hpp"
 #include "AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -24,7 +22,6 @@ namespace shardok {
 class ShardokEngine;
 using ScoreValue = double;
 using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;

 /// Reason why AI evaluation completed at the achieved depth.
 enum class EvaluationCompletionReason {
@@ -38,7 +35,7 @@ public:
    struct SearchResult {
        size_t bestCommandIndex;
        ScoreValue bestScore;
-        size_t depthAchieved;
+        int depthAchieved;
        std::chrono::milliseconds timeUsed;
        bool minimumDepthCompleted;
        bool searchCompleted;
@@ -63,50 +60,48 @@ public:
            bool isDefender,
            AIStrategy strategy,
            const CoordsSet& castleCoords,
-            const AIScoreCalculator& scorer,
            const APDCache& apdCache,
-            BattalionTypeGetter battalionTypeGetter);  // Pass by value
+            const ALCache& alCache);

    [[nodiscard]] SearchResult IterativeSearch(
            const GameSettingsSPtr& settings,
            const GameStateW& state,
            const std::vector<CommandProto>& commands,
-            const AITimeBudget& initialBudget) const;
+            const AITimeBudget& timeBudget) const;

 private:
    PlayerId playerId;
    bool isDefender;
    AIStrategy strategy;
    CoordsSet castleCoords;
-    const AIScoreCalculator& scorer;
    const APDCache& apdCache;
-    BattalionTypeGetter battalionTypeGetter;  // Store by value, not reference!
+    const ALCache& alCache;

    // Reusable vectors to reduce memory allocations
    mutable std::vector<std::vector<ScoreValue>> scoresByDepth;
-    mutable std::vector<size_t> highestDepthCompleted;
+    mutable std::vector<int> highestDepthCompleted;
    mutable std::vector<size_t> reusableSortedIndices;

    [[nodiscard]] static bool IsTimeExpired(const AITimeBudget& budget);

-    [[nodiscard]] std::future<SearchResult> SearchCommandAtDepthWithEngine(
+    [[nodiscard]] SearchResult SearchCommandAtDepthWithEngine(
            const ShardokEngine& guessedEngine,
-            const AIScoreCalculator& scorer,
+            const GameSettings::Getter& settingsGetter,
            int maxRepeatCount,
            const std::vector<CommandProto>& commands,
            size_t commandIndex,
-            int desiredDepth,
+            int depth,
            ScoreValue currentUtility,
            AITimeBudget& timeBudget) const;

-    [[nodiscard]] static std::vector<size_t> GetCommandsSortedByPreviousDepth(
-            size_t currentDepth,
+    [[nodiscard]] std::vector<size_t> GetCommandsSortedByPreviousDepth(
+            int currentDepth,
            const std::vector<std::vector<ScoreValue>>& scoresByDepth,
-            const std::vector<size_t>& highestDepthCompleted);
+            const std::vector<int>& highestDepthCompleted) const;

-    [[nodiscard]] static SearchResult SelectBestResult(
+    [[nodiscard]] SearchResult SelectBestResult(
            const std::vector<std::vector<ScoreValue>>& scoresByDepth,
-            const std::vector<size_t>& highestDepthCompleted);
+            const std::vector<int>& highestDepthCompleted) const;
 };

 }  // namespace shardok
@@ -13,16 +13,12 @@
 #include <google/protobuf/util/message_differencer.h>

 #include "AIAttackerStrategySelector.hpp"
-#include "AIConfig.hpp"
 #include "AIDefenderStrategySelector.hpp"
 #include "AIFleeDecisionCalculator.hpp"
 #include "AIScoreUtilities.hpp"
 #include "AITimeBudget.hpp"
 #include "IterativeDeepeningAI.hpp"
-#include "mcts/ShardokMCTSAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/MCTSOptimizedAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/NormalizedAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/StandardAIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/common/TimeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/view_filters/GameStateGuesser.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/action_result_view.pb.h"
@@ -34,7 +30,7 @@ using net::eagle0::shardok::api::GameStateView;

 static constexpr bool kPerformanceLogging = true;

-void ApplyUpdate(GameStateView & /*currentView*/, const ActionResultView & /*update*/) {}
+void ApplyUpdate(GameStateView &currentView, const ActionResultView &update) {}

 auto RoundsRemaining(const GameSettingsSPtr &settings, const GameStateView &gsv) -> int {
    const int maxRounds = settings->GetGetter().Backing().max_rounds();
@@ -46,17 +42,11 @@ ShardokAIClient::ShardokAIClient(
        const PlayerId playerId,
        const bool isDefender,
        const HexMap *hexMap,
-        const SettingsGetter &settings,
-        const AIAlgorithmType aiAlgorithmType,
-        const ScoringCalculatorType scoringCalculatorType,
-        const mcts::MCTSConfig &mctsConfig)
+        const SettingsGetter &settings)
    : playerId(playerId),
      isDefender(isDefender),
-      aiAlgorithmType(aiAlgorithmType),
-      scoringCalculatorType(scoringCalculatorType),
      alCache(std::make_unique<AttackLocationsCache>(hexMap, settings)),
-      waterCrossingCommandChooser(playerId, apdCache),
-      mctsConfig(mctsConfig) {
+      waterCrossingCommandChooser(playerId, apdCache) {
    // Pre-generate the most common cache entries for better performance
    const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);

@@ -102,108 +92,40 @@ auto ShardokAIClient::StandardChooseCommandIndex(
        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
    const auto settingsGetter = settings->GetGetter();
    const auto guessedEngine = ShardokEngine(settings, guessedState);
+
+    // Calculate time budget based on game situation using new settings
+    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState);
+
    const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
    const auto commandCount = guessedCommands.size();

-    // Calculate time budget based on game situation using new dynamic per-command settings
-    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState, commandCount);
-
-    // Configure MCTS based on proximity to enemy
-    // When far from enemy: use AVERAGING with maxPlayerFlips=0 (single-player lookahead)
-    //   - AVERAGING naturally penalizes longer paths through variance
-    //   - No opponent nodes, so no one-bad-child problem
-    // When close to enemy: use MINIMAX with maxPlayerFlips=1 (adversarial lookahead)
-    //   - MINIMAX correctly models opponent choosing best response
-    //   - Explores through one opponent turn for tactical accuracy
-    auto adjustedMCTSConfig = mctsConfig;
-    // adjustedMCTSConfig.maxPlayerFlips = 0;
-    // if (timeBudget.isCloseToEnemy) {
-    //     adjustedMCTSConfig.maxPlayerFlips = 1;
-    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::MINIMAX;
-    //     if constexpr (kPerformanceLogging) {
-    //         printf("MCTS Config: Close to enemy - using maxPlayerFlips=1, MINIMAX backprop\n");
-    //     }
-    // } else {
-    //     adjustedMCTSConfig.maxPlayerFlips = 0;
-    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::AVERAGING;
-    //     if constexpr (kPerformanceLogging) {
-    //         printf("MCTS Config: Far from enemy - using maxPlayerFlips=0, AVERAGING backprop\n");
-    //     }
-    // }
-
    assert(commandCount == realAvailableCommands.size());
-    for (size_t i = 0; i < commandCount; i++) {
+    for (int i = 0; i < commandCount; i++) {
        CheckCommand(realAvailableCommands[i], guessedCommands[i]);
    }

-    // Extract values directly from settings for strategy selection
-    const auto maxRounds = settingsGetter.Backing().max_rounds();
-    const auto braveWaterCost = settingsGetter.Backing().brave_water_action_point_cost();
-    const auto battalionTypeGetter = [&settingsGetter](BattalionTypeId typeId) {
-        return settingsGetter.GetBattalionType(typeId);
-    };
-
-    // Create scorer for actual scoring during search - type selected at construction
-    std::unique_ptr<AIScoreCalculator> scorer;
-    switch (scoringCalculatorType) {
-        case ScoringCalculatorType::NORMALIZED:
-            scorer = MakeNormalizedAIScoreCalculator(settingsGetter, apdCache, alCache);
-            break;
-        case ScoringCalculatorType::MCTS_OPTIMIZED:
-            scorer = MakeMCTSOptimizedAIScoreCalculator(settingsGetter, apdCache, alCache);
-            break;
-        case ScoringCalculatorType::STANDARD:
-        default: scorer = MakeStandardAIScoreCalculator(settingsGetter, apdCache, alCache); break;
-    }
-
    // Determine strategy once for consistent scoring throughout iterative deepening
    const auto castleCoords = AllCastleCoords(guessedState->hex_map());
    const AIStrategy strategy = isDefender ? AIDefenderStrategySelector::BestDefenderStrategy(
                                                     guessedState,
                                                     castleCoords,
-                                                     maxRounds,
                                                     apdCache,
-                                                     battalionTypeGetter)
+                                                     settingsGetter)
                                           : AIAttackerStrategySelector::BestAttackerStrategy(
                                                     playerId,
                                                     guessedState,
                                                     castleCoords,
-                                                     maxRounds,
                                                     apdCache,
                                                     alCache,
-                                                     battalionTypeGetter,
-                                                     braveWaterCost,
+                                                     settingsGetter,
                                                     waterCrossingCommandChooser,
                                                     realAvailableCommands);

-    // AI implementation chosen at runtime via constructor parameter
-    IterativeDeepeningAI::SearchResult search_result;
-
-    if (aiAlgorithmType == AIAlgorithmType::MCTS) {
-        // Using Monte Carlo Tree Search AI (with abstraction layer)
-        ShardokMCTSAI ai(
-                playerId,
-                isDefender,
-                strategy,
-                castleCoords,
-                *scorer,
-                apdCache,
-                alCache,
-                adjustedMCTSConfig);
-        search_result = ai.Search(settings, guessedState, timeBudget);
-    } else {
-        // Using Iterative Deepening AI (default)
-        IterativeDeepeningAI ai(
-                playerId,
-                isDefender,
-                strategy,
-                castleCoords,
-                *scorer,
-                apdCache,
-                battalionTypeGetter);
-        search_result =
-                ai.IterativeSearch(settings, guessedState, realAvailableCommands, timeBudget);
-    }
+    // Use iterative deepening AI for Phase 2 implementation
+    IterativeDeepeningAI
+            iterativeAI(playerId, isDefender, strategy, castleCoords, apdCache, alCache);
+    auto search_result =
+            iterativeAI.IterativeSearch(settings, guessedState, realAvailableCommands, timeBudget);

    CommandChoiceResults result{};
    result.chosenIndex = search_result.bestCommandIndex;
@@ -219,11 +141,9 @@ auto ShardokAIClient::StandardChooseCommandIndex(
                   result.commandCountEvaluated,
                   result.availableCommandCount);
        }
-        const auto chosenCommandType = realAvailableCommands[result.chosenIndex].type();
-        printf("ID AI: Search complete - achieved depth %d for best command %zu (%s)\n",
+        printf("ID AI: Search complete - achieved depth %d for best command %zu\n",
               result.depthAchieved,
-               result.chosenIndex,
-               net::eagle0::shardok::common::CommandType_Name(chosenCommandType).c_str());
+               result.chosenIndex);

        fflush(stdout);
    }
@@ -269,21 +189,13 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
        return LateRoundAttackerChooseCommandIndex(settings, guessedState, realAvailableCommands);
    }

-    // Extract values directly from settings for flee decision evaluation
-    const auto settingsGetter = settings->GetGetter();
-    const auto maxRounds = settingsGetter.Backing().max_rounds();
-    const auto minimumFleeOddsThreshold = settingsGetter.Backing().ai_minimum_flee_odds_threshold();
-    const auto desperateFleeThreshold = settingsGetter.Backing().ai_desperate_flee_threshold();
-
    // Use the flee decision calculator
    const auto fleeDecision = AIFleeDecisionCalculator::EvaluateFleeVsFight(
            playerId,
+            settings,
            guessedState,
            realAvailableCommands,
            fleeCommand,
-            maxRounds,
-            minimumFleeOddsThreshold,
-            desperateFleeThreshold,
 #ifdef DEBUG_FLEE_DECISIONS
            true  // Enable debug logging
 #else
@@ -12,12 +12,10 @@
 #include <vector>

 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIConfig.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"

 namespace shardok {
@@ -40,17 +38,12 @@ class ShardokAIClient {
 private:
    const PlayerId playerId;
    const bool isDefender;
-    const AIAlgorithmType aiAlgorithmType;
-    const ScoringCalculatorType scoringCalculatorType;

    APDCache apdCache = std::make_shared<ActionPointDistancesCache>();
    ALCache alCache;

    const AIWaterCrossingCommandChooser waterCrossingCommandChooser;

-    // MCTS configuration (only used when aiAlgorithmType == MCTS)
-    mcts::MCTSConfig mctsConfig;
-
    [[nodiscard]] auto StandardChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
@@ -74,20 +67,13 @@ public:
            PlayerId playerId,
            bool isDefender,
            const HexMap* hexMap,
-            const SettingsGetter& settings,
-            AIAlgorithmType aiAlgorithmType,
-            ScoringCalculatorType scoringCalculatorType,
-            const mcts::MCTSConfig& mctsConfig);
+            const SettingsGetter& settings);
    ~ShardokAIClient() = default;

    [[nodiscard]] auto GetPlayerId() const -> PlayerId { return playerId; }

    [[nodiscard]] auto ChooseCommandIndex(const ShardokEngine& engine) const
            -> CommandChoiceResults;
-
-    // MCTS configuration methods (only relevant when using MCTS algorithm)
-    [[nodiscard]] auto GetMCTSConfig() const -> const mcts::MCTSConfig& { return mctsConfig; }
-    void SetMCTSConfig(const mcts::MCTSConfig& config) { mctsConfig = config; }
 };
 }  // namespace shardok

@@ -1,113 +0,0 @@
-//
-// TranspositionTable.cpp - Implementation of game state evaluation cache
-//
-
-#include "TranspositionTable.hpp"
-
-#include <cstdio>
-#include <cstring>
-
-namespace shardok {
-
-// Global instance
-TranspositionTable g_transpositionTable;
-
-TranspositionTable::TranspositionTable() : table(TABLE_SIZE) {
-    // Initialize all entries to zero
-    clear();
-}
-
-uint64_t TranspositionTable::hashGameState(const GameStateW& state) const {
-    // The FlatBuffer is contiguous in memory and units are sorted by ID,
-    // so we can just hash the raw bytes for order-independent hashing
-    // Use ComputeFNV1aHash to avoid creating a string copy
-    return state.ComputeFNV1aHash();
-}
-
-std::optional<ScoreValue>
-TranspositionTable::probe(const GameStateW& state, int depth, PlayerId player) {
-    stats.probes++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    const auto& entry = table[index];
-
-    // Check if this entry matches our position using FULL hash
-    uint64_t stored_hash = entry.hash_full.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-    uint8_t stored_player = entry.player_id.load(std::memory_order_relaxed);
-
-    if (stored_hash == hash && stored_depth >= depth && stored_player == player) {
-        stats.hits++;
-        float score = entry.score.load(std::memory_order_relaxed);
-        return static_cast<ScoreValue>(score);
-    }
-
-    // Track collisions (different position mapped to same index)
-    // Note: We use depth==0 to indicate empty entries, not hash==0
-    if (stored_depth != 0 && stored_hash != hash) { stats.collisions++; }
-
-    return std::nullopt;
-}
-
-void TranspositionTable::store(
-        const GameStateW& state,
-        int depth,
-        PlayerId player,
-        ScoreValue score) {
-    stats.stores++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    auto& entry = table[index];
-
-    // Simple replacement strategy: always replace if:
-    // 1. Entry is from an older search (different age)
-    // 2. New search is deeper
-    // 3. Entry is empty (depth == 0)
-
-    uint16_t stored_age = entry.age.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-
-    bool should_replace = (stored_depth == 0) ||          // Empty entry (depth 0 means unused)
-                          (stored_age != current_age) ||  // Old entry
-                          (depth >= stored_depth);        // Deeper or equal search
-
-    if (should_replace) {
-        // Store all fields with relaxed ordering (TT races are benign)
-        entry.hash_full.store(hash, std::memory_order_relaxed);
-        entry.score.store(static_cast<float>(score), std::memory_order_relaxed);
-        entry.depth.store(static_cast<uint8_t>(depth), std::memory_order_relaxed);
-        entry.player_id.store(static_cast<uint8_t>(player), std::memory_order_relaxed);
-        entry.age.store(current_age, std::memory_order_relaxed);
-    }
-}
-
-void TranspositionTable::clear() {
-    // Reset all entries
-    for (auto& entry : table) {
-        entry.hash_full.store(0, std::memory_order_relaxed);
-        entry.score.store(0.0f, std::memory_order_relaxed);
-        entry.depth.store(0, std::memory_order_relaxed);
-        entry.player_id.store(0, std::memory_order_relaxed);
-        entry.age.store(0, std::memory_order_relaxed);
-    }
-
-    stats.reset();
-    current_age = 0;
-}
-
-void TranspositionTable::printStats() const {
-    printf("TranspositionTable Stats:\n");
-    printf("  Probes: %llu\n", stats.probes.load());
-    printf("  Hits: %llu (%.1f%%)\n", stats.hits.load(), stats.hitRate());
-    printf("  Stores: %llu\n", stats.stores.load());
-    printf("  Collisions: %llu\n", stats.collisions.load());
-    printf("  Table size: %zu entries (%.1f MB)\n",
-           TABLE_SIZE,
-           (TABLE_SIZE * sizeof(TTEntry)) / (1024.0 * 1024.0));
-}
-
-}  // namespace shardok
@@ -1,91 +0,0 @@
-//
-// TranspositionTable.hpp - Cache for game state evaluations to avoid redundant calculations
-//
-
-#ifndef EAGLE0_TRANSPOSITIONTABLE_HPP
-#define EAGLE0_TRANSPOSITIONTABLE_HPP
-
-#include <atomic>
-#include <cstdint>
-#include <optional>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-namespace shardok {
-
-using ScoreValue = double;
-// PlayerId already defined in ShardokCTypes.h
-
-class TranspositionTable {
-public:
-    // Statistics for monitoring effectiveness
-    struct Stats {
-        std::atomic<uint64_t> probes{0};
-        std::atomic<uint64_t> hits{0};
-        std::atomic<uint64_t> stores{0};
-        std::atomic<uint64_t> collisions{0};
-
-        double hitRate() const {
-            uint64_t p = probes.load();
-            return p > 0 ? (100.0 * hits.load() / p) : 0.0;
-        }
-
-        void reset() {
-            probes = 0;
-            hits = 0;
-            stores = 0;
-            collisions = 0;
-        }
-    };
-
-private:
-    // Compact entry structure (actual size is greater than 16 bytes due to atomics and alignment)
-    struct TTEntry {
-        std::atomic<uint64_t> hash_full;  // Full hash for validation
-        std::atomic<float> score;         // Score as float to save space
-        std::atomic<uint8_t> depth;       // Search depth (0-255)
-        std::atomic<uint8_t> player_id;   // Player who is to move
-        std::atomic<uint16_t> age;        // For replacement strategy
-    };
-
-    static constexpr size_t TABLE_SIZE_BITS = 22;                  // 2^22 entries
-    static constexpr size_t TABLE_SIZE = 1ULL << TABLE_SIZE_BITS;  // 4M entries = 64MB
-    static constexpr size_t INDEX_MASK = TABLE_SIZE - 1;
-
-    std::vector<TTEntry> table;
-    Stats stats;
-    std::atomic<uint16_t> current_age{0};
-
-    // Hash function for FlatBuffer game state
-    uint64_t hashGameState(const GameStateW& state) const;
-
-public:
-    TranspositionTable();
-
-    // Probe the table for a cached evaluation
-    std::optional<ScoreValue> probe(const GameStateW& state, int depth, PlayerId player);
-
-    // Store an evaluation in the table
-    void store(const GameStateW& state, int depth, PlayerId player, ScoreValue score);
-
-    // Clear the entire table
-    void clear();
-
-    // Increment age for replacement strategy (call at start of each search)
-    void incrementAge() { current_age++; }
-
-    // Get statistics
-    const Stats& getStats() const { return stats; }
-
-    // Print statistics to stdout
-    void printStats() const;
-};
-
-// Global instance for the AI to use
-extern TranspositionTable g_transpositionTable;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_TRANSPOSITIONTABLE_HPP
@@ -1,25 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "shardok_mcts_ai",
-    srcs = ["ShardokMCTSAI.cpp"],
-    hdrs = ["ShardokMCTSAI.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:abstract_mcts_ai",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_iterative_deepening",  # For SearchResult compatibility
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_time_budget",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:shardok_mcts_factory",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-    ],
-)
@@ -1,111 +0,0 @@
-//
-// Shardok-specific MCTS AI implementation using abstract interfaces
-//
-
-#include "ShardokMCTSAI.hpp"
-
-#include "adapters/ShardokGameEngine.hpp"
-#include "adapters/ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-
-namespace shardok {
-
-ShardokMCTSAI::ShardokMCTSAI(
-        PlayerId playerId,
-        bool isDefender,
-        AIStrategy strategy,
-        const CoordsSet& castleCoords,
-        const AIScoreCalculator& scoreCalculator,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        MCTSConfig config)
-    : abstractAI_(std::make_unique<mcts::AbstractMCTSAI>(
-              static_cast<mcts::MCTSPlayerId>(
-                      playerId),  // Use actual player ID for correct scoring
-              config)),
-      isDefender_(isDefender),
-      strategy_(strategy),
-      castleCoords_(castleCoords),
-      scoreCalculator_(scoreCalculator),
-      apdCache_(apdCache),
-      alCache_(alCache) {}
-
-auto ShardokMCTSAI::Search(
-        const GameSettingsSPtr& settings,
-        const GameStateW& state,
-        const AITimeBudget& budget) const -> SearchResult {
-    // Compute critical tiles once to avoid 8.5% runtime overhead in ShardokEngine construction
-    const auto criticalTiles = GetCriticalTileLocations(state->hex_map());
-
-    // Create Shardok engine for simulation
-    ShardokEngine engine(settings, state, criticalTiles, 0, false);
-
-    // Create game state adapter
-    auto gameState = mcts::ShardokMCTSFactory::createGameState(
-            state,
-            &scoreCalculator_,  // Pass the score calculator
-            settings,           // Pass shared_ptr directly
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            apdCache_,
-            alCache_,
-            criticalTiles);
-
-    // Create game engine adapter (passing critical tiles to avoid recomputation)
-    auto gameEngine = mcts::ShardokMCTSFactory::createGameEngine(
-            engine,
-            &scoreCalculator_,  // Pass the score calculator
-            settings,
-            apdCache_,
-            alCache_,
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            criticalTiles);
-
-    // Perform abstract search
-    const auto timeLimit = budget.remainingBudget;
-    const auto abstractResult = abstractAI_->Search(*gameEngine, *gameState, timeLimit);
-
-    // Report cache statistics for performance analysis
-    if (auto* shardokEngine = dynamic_cast<mcts::ShardokGameEngine*>(gameEngine.get())) {
-        shardokEngine->reportCacheStatistics();
-    }
-
-    // Get unfiltered command count for consistent reporting with IterativeDeepeningAI
-    // (MCTS uses filtered commands internally, but we report unfiltered count for metrics)
-    const auto unfilteredCommands = engine.GetAvailableCommandsForAIPlayer(
-            static_cast<PlayerId>(gameState->currentPlayerId()));
-    const size_t unfilteredCount = unfilteredCommands ? unfilteredCommands->size() : 0;
-
-    // Convert result back to Shardok format
-    SearchResult result;
-    // Map filtered index back to original unfiltered index
-    result.bestCommandIndex =
-            gameEngine->mapFilteredIndexToOriginal(abstractResult.bestActionIndex, *gameState);
-    result.bestScore = abstractResult.bestScore;
-    result.depthAchieved = static_cast<size_t>(abstractResult.searchDepth);
-    result.commandCountEvaluated = static_cast<size_t>(abstractResult.nodesEvaluated);
-    result.timeUsed = abstractResult.searchTime;
-    result.availableCommandCount = unfilteredCount;
-    result.minimumDepthCompleted =
-            (abstractResult.searchDepth >= static_cast<int>(budget.minDepthRequired));
-    result.searchCompleted = true;  // MCTS is anytime - always returns a valid result
-
-    // Determine completion reason based on what actually happened
-    if (abstractResult.foundWinningMove || unfilteredCount == 0) {
-        // Found a terminal winning state or no commands available
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-    } else {
-        // Normal case - time budget exhausted while exploring
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
-    }
-
-    return result;
-}
-
-}  // namespace shardok
@@ -1,73 +0,0 @@
-//
-// Shardok-specific MCTS AI that wraps the abstract implementation
-//
-
-#ifndef EAGLE0_SHARDOK_MCTSAI_HPP
-#define EAGLE0_SHARDOK_MCTSAI_HPP
-
-#include <memory>
-#include <vector>
-
-#include "adapters/ShardokMCTSFactory.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/AbstractMCTSAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"  // For SearchResult compatibility
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#pragma clang diagnostic pop
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-
-class ShardokMCTSAI {
-public:
-    using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-    using SearchResult = IterativeDeepeningAI::SearchResult;
-    using MCTSConfig = mcts::MCTSConfig;
-
-    ShardokMCTSAI(
-            PlayerId playerId,
-            bool isDefender,
-            AIStrategy strategy,
-            const CoordsSet& castleCoords,
-            const AIScoreCalculator& scoreCalculator,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            MCTSConfig config = MCTSConfig{});
-
-    // Main search interface - compatible with IterativeDeepeningAI
-    [[nodiscard]] auto Search(
-            const GameSettingsSPtr& settings,
-            const GameStateW& state,
-            const AITimeBudget& budget) const -> SearchResult;
-
-    // Configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return abstractAI_->GetConfig(); }
-    void SetConfig(const MCTSConfig& newConfig) { abstractAI_->SetConfig(newConfig); }
-
-private:
-    std::unique_ptr<mcts::AbstractMCTSAI> abstractAI_;
-
-    // Shardok-specific context
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet& castleCoords_;
-    const AIScoreCalculator& scoreCalculator_;
-    const APDCache& apdCache_;
-    const ALCache& alCache_;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_MCTSAI_HPP
@@ -1,82 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "shardok_action",
-    srcs = ["ShardokAction.cpp"],
-    hdrs = ["ShardokAction.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_action",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "shardok_game_state",
-    srcs = ["ShardokGameState.cpp"],
-    hdrs = ["ShardokGameState.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_state",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
-
-cc_library(
-    name = "shardok_game_engine",
-    srcs = ["ShardokGameEngine.cpp"],
-    hdrs = ["ShardokGameEngine.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        ":shardok_action",
-        ":shardok_game_state",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_engine",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_heuristic_weighting",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
-
-cc_library(
-    name = "shardok_mcts_factory",
-    srcs = ["ShardokMCTSFactory.cpp"],
-    hdrs = ["ShardokMCTSFactory.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        ":shardok_action",
-        ":shardok_game_engine",
-        ":shardok_game_state",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-    ],
-)
@@ -1,71 +0,0 @@
-//
-// Shardok-specific action adapter implementation
-//
-
-#include "ShardokAction.hpp"
-
-#include <sstream>
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma clang diagnostic pop
-
-namespace shardok {
-namespace mcts {
-
-ShardokAction::ShardokAction(const CommandProto& command, size_t index)
-    : command_(command),
-      commandIndex_(index) {}
-
-ShardokAction::ShardokAction(CommandProto&& command, size_t index)
-    : command_(std::move(command)),
-      commandIndex_(index) {}
-
-int ShardokAction::getType() const { return static_cast<int>(command_.type()); }
-
-std::string ShardokAction::getDescription() const {
-    std::stringstream ss;
-
-    // Show player
-    ss << "P" << static_cast<int>(command_.player()) << " ";
-
-    ss << net::eagle0::shardok::common::CommandType_Name(command_.type());
-
-    if (command_.has_actor()) { ss << " Unit:" << command_.actor().value(); }
-
-    if (command_.has_target()) {
-        const auto& coord = command_.target();
-        ss << " @(" << coord.row() << "," << coord.column() << ")";
-    }
-
-    return ss.str();
-}
-
-int ShardokAction::getActorId() const {
-    if (command_.has_actor()) { return command_.actor().value(); }
-    return -1;
-}
-
-std::pair<int, int> ShardokAction::getTarget() const {
-    if (command_.has_target()) {
-        const auto& coord = command_.target();
-        return std::make_pair(coord.row(), coord.column());
-    }
-    return std::make_pair(-1, -1);
-}
-
-std::unique_ptr<MCTSAction> ShardokAction::clone() const {
-    return std::make_unique<ShardokAction>(command_, commandIndex_);
-}
-
-bool ShardokAction::equals(const MCTSAction& other) const {
-    const auto* shardokOther = dynamic_cast<const ShardokAction*>(&other);
-    if (!shardokOther) { return false; }
-
-    return commandIndex_ == shardokOther->commandIndex_ &&
-           command_.SerializeAsString() == shardokOther->command_.SerializeAsString();
-}
-
-}  // namespace mcts
-}  // namespace shardok
@@ -1,50 +0,0 @@
-//
-// Shardok-specific action adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_ACTION_HPP
-#define EAGLE0_SHARDOK_ACTION_HPP
-
-#include <memory>
-#include <string>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSAction.hpp"
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#pragma clang diagnostic pop
-
-namespace shardok {
-namespace mcts {
-
-class ShardokAction : public MCTSAction {
-public:
-    using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-    ShardokAction(const CommandProto& command, size_t index);
-    ShardokAction(CommandProto&& command, size_t index);
-
-    // MCTSAction interface implementation
-    [[nodiscard]] size_t getIndex() const override { return commandIndex_; }
-    [[nodiscard]] std::string getDescription() const override;
-    [[nodiscard]] std::unique_ptr<MCTSAction> clone() const override;
-    [[nodiscard]] bool equals(const MCTSAction& other) const override;
-
-    // Shardok-specific methods (not part of abstract interface)
-    [[nodiscard]] int getType() const;
-    [[nodiscard]] int getActorId() const;
-    [[nodiscard]] std::pair<int, int> getTarget() const;
-
-    // Shardok-specific accessor
-    [[nodiscard]] const CommandProto& getCommand() const { return command_; }
-
-private:
-    CommandProto command_;
-    size_t commandIndex_;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_ACTION_HPP
@@ -1,383 +0,0 @@
-//
-// Shardok-specific game engine adapter implementation
-//
-
-#include "ShardokGameEngine.hpp"
-
-#include <chrono>
-
-#include "ShardokAction.hpp"
-#include "ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIHeuristicWeighting.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-// Thread-local cache for legal actions (avoids lock contention in multithreaded simulation)
-thread_local gtl::flat_hash_map<uint64_t, ShardokGameEngine::LegalActionsCache>
-        ShardokGameEngine::legalActionsCache_;
-thread_local uint64_t ShardokGameEngine::cacheHits_ = 0;
-thread_local uint64_t ShardokGameEngine::cacheMisses_ = 0;
-thread_local uint64_t ShardokGameEngine::timeInHashComputation_ = 0;
-thread_local uint64_t ShardokGameEngine::timeInLegalActionsComputation_ = 0;
-
-ShardokGameEngine::ShardokGameEngine(
-        [[maybe_unused]] const ShardokEngine* engine,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& gameSettings,
-        const APDCache* apdCache,
-        const ALCache* alCache,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const CoordsSet& criticalTileCoords)
-    : scoreCalculator_(scoreCalculator),
-      gameSettings_(gameSettings),
-      apdCache_(apdCache),
-      alCache_(alCache),
-      isDefender_(isDefender),
-      strategy_(strategy),
-      castleCoords_(castleCoords),
-      criticalTileCoords_(criticalTileCoords) {
-    // Thread-local cache is automatically initialized per thread
-    // Reserve space to reduce rehashing (based on profiling: ~30-50K unique states per search)
-    legalActionsCache_.reserve(100000);
-}
-
-std::unique_ptr<MCTSGameState> ShardokGameEngine::applyAction(
-        const MCTSGameState& state,
-        const MCTSAction& action) const {
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
-
-    if (!shardokState || !shardokAction) { return nullptr; }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Use cached engine if available (avoids recomputing GetAvailableCommands for same state)
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        // Clone the cached engine to preserve command cache
-        engine = std::make_shared<ShardokEngine>(*cachedEngine);
-    } else {
-        // Create fresh engine and populate command cache
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache (result intentionally unused, just populating cache)
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        // Cache the engine for future use with this state
-        shardokState->setCachedEngine(engine);
-        // Clone it for applying the action (don't mutate the cached engine)
-        engine = std::make_shared<ShardokEngine>(*engine);
-    }
-
-    engine->PostCommand(currentPlayer, shardokAction->getIndex(), nullptr);
-
-    // Create and return the new state (don't cache the mutated engine)
-    auto newState = std::make_unique<ShardokGameState>(
-            engine->GetCurrentGameState(),
-            scoreCalculator_,
-            gameSettings_.get(),
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            *apdCache_,
-            *alCache_,
-            criticalTileCoords_);
-
-    // Don't pre-compute hash - let it be computed lazily on first use
-    // Many states (especially in simulation) never need their hash computed
-    return newState;
-}
-
-void ShardokGameEngine::applyActionMutable(
-        std::unique_ptr<MCTSGameState>& state,
-        const MCTSAction& action) const {
-    auto* shardokState = dynamic_cast<ShardokGameState*>(state.get());
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
-
-    if (!shardokState || !shardokAction) {
-        // Fallback to default implementation
-        state = applyAction(*state, action);
-        return;
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state->currentPlayerId());
-
-    // Use cached engine if available
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = std::make_shared<ShardokEngine>(*cachedEngine);
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache (result intentionally unused, just populating cache)
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        shardokState->setCachedEngine(engine);
-        engine = std::make_shared<ShardokEngine>(*engine);
-    }
-
-    engine->PostCommand(currentPlayer, shardokAction->getIndex(), nullptr);
-    shardokState->getMutableShardokState() = engine->GetCurrentGameState();
-    // Clear the cached engine and hash since the state has been mutated
-    shardokState->setCachedEngine(nullptr);
-    shardokState->invalidateHashCache();
-}
-
-std::vector<std::unique_ptr<MCTSAction>> ShardokGameEngine::getLegalActions(
-        const MCTSGameState& state,
-        MCTSPlayerId /*rootPlayerId*/,
-        int currentPlayerFlips,
-        int maxPlayerFlips) const {
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    if (!shardokState) { return {}; }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Check if we've exceeded the maximum allowed player flips
-    // currentPlayerFlips is the number of times the player has changed since root
-    // maxPlayerFlips is the maximum number of changes we allow
-    // If maxPlayerFlips is 0, only explore root player's moves (stop when player first changes)
-    // If maxPlayerFlips is 1, explore through opponent's response (stop after opponent's moves)
-    if (currentPlayerFlips > maxPlayerFlips) {
-        return {};  // Stop exploration - we've exceeded the flip limit
-    }
-
-    // Time hash computation
-    const auto hashStart = std::chrono::high_resolution_clock::now();
-    const uint64_t stateHash = shardokState->hash();
-    const auto hashEnd = std::chrono::high_resolution_clock::now();
-    timeInHashComputation_ +=
-            std::chrono::duration_cast<std::chrono::microseconds>(hashEnd - hashStart).count();
-
-    // Check transposition table for cached legal actions
-    if (auto it = legalActionsCache_.find(stateHash); it != legalActionsCache_.end()) {
-        cacheHits_++;
-
-        // Use cached engine
-        shardokState->setCachedEngine(it->second.engine);
-
-        // Get commands from the cached engine (Engine already caches these internally)
-        const CommandListSPtr commands =
-                it->second.engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-        if (!commands || commands->empty()) { return {}; }
-
-        // Convert to MCTSActions using stored filtered indices
-        std::vector<std::unique_ptr<MCTSAction>> actions;
-        actions.reserve(it->second.filteredIndices.size());
-
-        for (const size_t origIdx : it->second.filteredIndices) {
-            if (origIdx < commands->size()) {
-                const auto& cmd = commands->at(origIdx);
-                actions.push_back(std::make_unique<ShardokAction>(cmd->GetCommandProto(), origIdx));
-            }
-        }
-
-        return actions;
-    }
-
-    cacheMisses_++;
-
-    // Time legal actions computation
-    const auto actionsStart = std::chrono::high_resolution_clock::now();
-
-    // Use cached engine if available, otherwise create and cache it
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = cachedEngine;
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_);
-        shardokState->setCachedEngine(engine);
-    }
-
-    const CommandListSPtr commands = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-    if (!commands || commands->empty()) { return {}; }
-
-    // Filter commands using AICommandFilter (matching original MCTSAI behavior)
-    // Use gameSettings for battalion type lookups
-    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
-            commands,
-            currentPlayer,
-            isDefender_,
-            shardokState->getShardokState(),
-            *apdCache_,
-            [this](BattalionTypeId typeId) {
-                return gameSettings_->GetGetter().GetBattalionType(typeId);
-            });
-
-    // Convert only filtered commands to MCTSActions
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    actions.reserve(filteredIndices.size());
-
-    for (const size_t idx : filteredIndices) {
-        if (idx < commands->size()) {
-            const auto& cmd = commands->at(idx);
-            actions.push_back(std::make_unique<ShardokAction>(cmd->GetCommandProto(), idx));
-        }
-    }
-
-    const auto actionsEnd = std::chrono::high_resolution_clock::now();
-    timeInLegalActionsComputation_ +=
-            std::chrono::duration_cast<std::chrono::microseconds>(actionsEnd - actionsStart)
-                    .count();
-
-    // Store in transposition table for future lookups
-    // Note: We only store filtered indices and the engine (which caches commands internally)
-    // This avoids duplicating heavy protocol buffer objects
-    LegalActionsCache entry;
-    entry.filteredIndices = filteredIndices;
-    entry.engine = engine;
-    legalActionsCache_[stateHash] = std::move(entry);
-
-    return actions;
-}
-
-bool ShardokGameEngine::isTerminal(const MCTSGameState& state) const { return state.isTerminal(); }
-
-double ShardokGameEngine::evaluateState(const MCTSGameState& state, MCTSPlayerId playerId) const {
-    return state.score(playerId);
-}
-
-std::vector<size_t> ShardokGameEngine::filterActions(
-        const std::vector<std::unique_ptr<MCTSAction>>& actions,
-        const MCTSGameState& /*state*/) const {
-    // All filtering is already done in getLegalActions() using AICommandFilter
-    // This method is used by simulation policies and doesn't need additional filtering
-    std::vector<size_t> indices;
-    indices.reserve(actions.size());
-    for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
-    return indices;
-}
-
-std::vector<double> ShardokGameEngine::getActionWeights(
-        const std::vector<std::unique_ptr<MCTSAction>>& actions,
-        const MCTSGameState& state) const {
-    // Cast to ShardokGameState to access Shardok-specific methods
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    if (!shardokState) {
-        throw MCTSInternalError(
-                "ShardokGameEngine::getActionWeights called with non-Shardok state - this "
-                "indicates a type mismatch in the MCTS adapter layer");
-    }
-
-    // Use AIHeuristicWeighting for fast O(1) context-aware command weighting
-    std::vector<double> weights;
-    weights.reserve(actions.size());
-
-    for (const auto& action : actions) {
-        const auto* shardokAction = dynamic_cast<const ShardokAction*>(action.get());
-        if (!shardokAction) {
-            throw MCTSInternalError(
-                    "ShardokGameEngine::getActionWeights encountered non-Shardok action - this "
-                    "indicates a type mismatch in the MCTS adapter layer");
-        }
-        weights.push_back(AIHeuristicWeighting::GetCommandWeight(
-                shardokAction->getCommand(),
-                shardokState->getShardokState(),
-                castleCoords_,
-                apdCache_,
-                isDefender_,
-                [this](BattalionTypeId typeId) {
-                    return gameSettings_->GetGetter().GetBattalionType(typeId);
-                }));
-    }
-
-    return weights;
-}
-
-double ShardokGameEngine::getActionScore(
-        const MCTSGameState& state,
-        const MCTSAction& action,
-        MCTSPlayerId playerId) const {
-    auto newState = applyAction(state, action);
-    if (!newState) { return 0.0; }
-    return newState->score(playerId);
-}
-
-bool ShardokGameEngine::shouldStopSearch(
-        const MCTSGameState& /*state*/,
-        int /*iterations*/,
-        std::chrono::steady_clock::time_point /*startTime*/) const {
-    // Could add early termination logic here
-    return false;
-}
-
-size_t ShardokGameEngine::mapFilteredIndexToOriginal(
-        size_t filteredIndex,
-        const MCTSGameState& state) const {
-    // Get the filtered actions (uses cached engine)
-    auto actions = getLegalActions(state, state.currentPlayerId(), 0, 0);
-
-    // Check bounds
-    if (filteredIndex >= actions.size()) { return filteredIndex; }
-
-    // Extract the original index from the ShardokAction
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(actions[filteredIndex].get());
-    if (!shardokAction) { return filteredIndex; }
-
-    // ShardokAction stores the original unfiltered index
-    return shardokAction->getIndex();
-}
-
-void ShardokGameEngine::reportCacheStatistics() const {
-    const uint64_t totalLookups = cacheHits_ + cacheMisses_;
-    if (totalLookups > 0) {
-        const double hitRate = static_cast<double>(cacheHits_) / static_cast<double>(totalLookups);
-        const double avgHashTimeUs =
-                static_cast<double>(timeInHashComputation_) / static_cast<double>(totalLookups);
-        const double avgActionsTimeUs =
-                cacheMisses_ > 0 ? static_cast<double>(timeInLegalActionsComputation_) /
-                                           static_cast<double>(cacheMisses_)
-                                 : 0.0;
-
-        printf("Legal Actions Cache Stats:\n");
-        printf("  Lookups: %llu hits, %llu misses, %.1f%% hit rate, %zu entries\n",
-               static_cast<unsigned long long>(cacheHits_),
-               static_cast<unsigned long long>(cacheMisses_),
-               hitRate * 100.0,
-               legalActionsCache_.size());
-        printf("  Timing: %.2f us avg hash, %.2f us avg actions (on miss)\n",
-               avgHashTimeUs,
-               avgActionsTimeUs);
-        printf("  Total time: %.2f ms in hash, %.2f ms in actions\n",
-               timeInHashComputation_ / 1000.0,
-               timeInLegalActionsComputation_ / 1000.0);
-
-        // Calculate if transposition table is worth it
-        const double timeWithCache = timeInHashComputation_ + timeInLegalActionsComputation_;
-        const double timeWithoutCache =
-                avgActionsTimeUs * static_cast<double>(totalLookups);  // All lookups recompute
-        const double savings = (timeWithoutCache - timeWithCache) / timeWithoutCache * 100.0;
-        printf("  Cache savings: %.1f%% vs. no cache (%.2f ms saved)\n",
-               savings,
-               (timeWithoutCache - timeWithCache) / 1000.0);
-    }
-}
-
-void ShardokGameEngine::resetCacheStatistics() {
-    cacheHits_ = 0;
-    cacheMisses_ = 0;
-    timeInHashComputation_ = 0;
-    timeInLegalActionsComputation_ = 0;
-}
-
-}  // namespace shardok::mcts
@@ -1,127 +0,0 @@
-//
-// Shardok-specific game engine adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_GAME_ENGINE_HPP
-#define EAGLE0_SHARDOK_GAME_ENGINE_HPP
-
-#include <atomic>
-#include <functional>
-#include <gtl/phmap.hpp>
-#include <memory>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AICommandFilter;
-class AIScoreCalculator;
-class RandomGenerator;
-
-// Use existing type definitions from the Shardok codebase
-// GameSettingsSPtr and SettingsGetter are defined in GameSettings.hpp
-
-namespace mcts {
-
-class ShardokGameEngine : public MCTSGameEngine {
-public:
-    ShardokGameEngine(
-            const ShardokEngine* engine,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& gameSettings,
-            const APDCache* apdCache,
-            const ALCache* alCache,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const CoordsSet& criticalTileCoords);
-
-    // MCTSGameEngine interface implementation
-    [[nodiscard]] std::unique_ptr<MCTSGameState> applyAction(
-            const MCTSGameState& state,
-            const MCTSAction& action) const override;
-
-    void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
-            const override;
-
-    [[nodiscard]] std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
-            const MCTSGameState& state,
-            MCTSPlayerId rootPlayerId,
-            int currentPlayerFlips,
-            int maxPlayerFlips) const override;
-
-    [[nodiscard]] bool isTerminal(const MCTSGameState& state) const override;
-
-    [[nodiscard]] double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
-            const override;
-
-    [[nodiscard]] std::vector<size_t> filterActions(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& state) const override;
-
-    [[nodiscard]] std::vector<double> getActionWeights(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& state) const override;
-
-    [[nodiscard]] double getActionScore(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            MCTSPlayerId playerId) const override;
-
-    [[nodiscard]] bool shouldStopSearch(
-            const MCTSGameState& state,
-            int iterations,
-            std::chrono::steady_clock::time_point startTime) const override;
-
-    [[nodiscard]] size_t mapFilteredIndexToOriginal(
-            size_t filteredIndex,
-            const MCTSGameState& state) const override;
-
-    // Report transposition table statistics
-    void reportCacheStatistics() const;
-
-    // Reset cache statistics
-    void resetCacheStatistics();
-
-private:
-    // Transposition table entry for caching legal actions
-    // Note: We don't store command protos since the Engine already caches them
-    struct LegalActionsCache {
-        std::vector<size_t> filteredIndices;
-        std::shared_ptr<ShardokEngine> engine;  // Engine with populated command cache
-    };
-
-    const AIScoreCalculator* scoreCalculator_;
-    const GameSettingsSPtr gameSettings_;
-    const APDCache* apdCache_;
-    const ALCache* alCache_;
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet& castleCoords_;
-    // Computed once to avoid 8.5% overhead per engine construction
-    const CoordsSet& criticalTileCoords_;
-
-    // Transposition table for legal actions (thread-local to avoid lock contention)
-    // Each thread maintains its own cache during multithreaded simulation
-    static thread_local gtl::flat_hash_map<uint64_t, LegalActionsCache> legalActionsCache_;
-    static thread_local uint64_t cacheHits_;
-    static thread_local uint64_t cacheMisses_;
-
-    // Performance timing (in microseconds)
-    static thread_local uint64_t timeInHashComputation_;
-    static thread_local uint64_t timeInLegalActionsComputation_;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_ENGINE_HPP
@@ -1,103 +0,0 @@
-//
-// Shardok-specific game state adapter implementation
-//
-
-#include "ShardokGameState.hpp"
-
-#include <sstream>
-#include <string>
-#include <utility>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-ShardokGameState::ShardokGameState(
-        GameStateW state,
-        const AIScoreCalculator* calculator,
-        const GameSettings* settings,
-        const bool isDefender,
-        AIStrategy strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        const CoordsSet& criticalTileCoords)
-    : state_(std::move(state)),
-      scoreCalculator_(calculator),
-      settings_(settings),
-      isDefender_(isDefender),
-      strategy_(std::move(strategy)),
-      castleCoords_(castleCoords),
-      apdCache_(apdCache),
-      alCache_(alCache),
-      criticalTileCoords_(criticalTileCoords) {}
-
-uint64_t ShardokGameState::hash() const {
-    if (!hashCached_) {
-        cachedHash_ = state_.ComputeFNV1aHash();
-        hashCached_ = true;
-    }
-    return cachedHash_;
-}
-
-double ShardokGameState::score(MCTSPlayerId /*playerId*/) const {
-    // Always return score from the perspective of the AI that created this state (isDefender_).
-    // The playerId parameter is ignored - adversarial logic happens in selection, not scoring.
-    return scoreCalculator_->GuessedStateScore(isDefender_, state_, strategy_, castleCoords_);
-}
-
-MCTSPlayerId ShardokGameState::currentPlayerId() const { return state_->current_player(); }
-
-bool ShardokGameState::isTerminal() const {
-    // Check if game status indicates the game is over
-    if (state_->status()) {
-        const auto gameStatus = state_->status()->state();
-        if (gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_VICTORY ||
-            gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_DRAW) {
-            return true;
-        }
-    }
-
-    // Check max rounds
-    if (state_->current_round() >= settings_->GetGetter().Backing().max_rounds()) { return true; }
-
-    return false;
-}
-
-std::unique_ptr<MCTSGameState> ShardokGameState::clone() const {
-    auto cloned = std::make_unique<ShardokGameState>(
-            state_,
-            scoreCalculator_,
-            settings_,
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            apdCache_,
-            alCache_,
-            criticalTileCoords_);
-    // Don't copy the cached engine - each state needs its own
-    return cloned;
-}
-
-bool ShardokGameState::equals(const MCTSGameState& other) const {
-    const auto* shardokOther = dynamic_cast<const ShardokGameState*>(&other);
-    if (!shardokOther) { return false; }
-
-    return hash() == shardokOther->hash();
-}
-
-MCTSPlayerId ShardokGameState::getWinner() const {
-    // Note: FlatBuffer doesn't have a winner field
-    // In practice, this would need to determine winner from victory conditions
-    return -1;  // No winner
-}
-
-std::string ShardokGameState::toString() const {
-    std::stringstream ss;
-    ss << "ShardokGameState[Round:" << static_cast<int>(state_->current_round())
-       << " Player:" << currentPlayerId() << " Hash:" << hash() << "]";
-    return ss.str();
-}
-
-}  // namespace shardok::mcts
@@ -1,83 +0,0 @@
-//
-// Shardok-specific game state adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_GAME_STATE_HPP
-#define EAGLE0_SHARDOK_GAME_STATE_HPP
-
-#include <memory>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-
-namespace mcts {
-
-class ShardokGameState : public MCTSGameState {
-public:
-    ShardokGameState(
-            GameStateW state,
-            const AIScoreCalculator* calculator,
-            const GameSettings* settings,
-            bool isDefender,
-            AIStrategy strategy,
-            const CoordsSet& castleCoords,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            const CoordsSet& criticalTileCoords);
-
-    // MCTSGameState interface implementation
-    [[nodiscard]] uint64_t hash() const override;
-    [[nodiscard]] double score(MCTSPlayerId playerId) const override;
-    [[nodiscard]] MCTSPlayerId currentPlayerId() const override;
-    [[nodiscard]] bool isTerminal() const override;
-    [[nodiscard]] std::unique_ptr<MCTSGameState> clone() const override;
-    [[nodiscard]] bool equals(const MCTSGameState& other) const override;
-    [[nodiscard]] MCTSPlayerId getWinner() const override;
-    [[nodiscard]] std::string toString() const override;
-
-    // Shardok-specific accessors
-    [[nodiscard]] const GameStateW& getShardokState() const { return state_; }
-    [[nodiscard]] GameStateW& getMutableShardokState() { return state_; }
-    [[nodiscard]] bool isDefender() const { return isDefender_; }
-    [[nodiscard]] const GameSettings* getSettings() const { return settings_; }
-    [[nodiscard]] const CoordsSet& getCriticalTileCoords() const { return criticalTileCoords_; }
-
-    // Engine caching for performance (avoids recomputing available commands)
-    void setCachedEngine(std::shared_ptr<ShardokEngine> engine) const { cachedEngine_ = engine; }
-    [[nodiscard]] std::shared_ptr<ShardokEngine> getCachedEngine() const { return cachedEngine_; }
-
-    // Invalidate hash cache when state is mutated
-    void invalidateHashCache() const {
-        hashCached_ = false;
-        cachedHash_ = 0;
-    }
-
-private:
-    GameStateW state_;
-    const AIScoreCalculator* scoreCalculator_;
-    const GameSettings* settings_;
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet& castleCoords_;
-    const APDCache& apdCache_;
-    const ALCache& alCache_;
-    mutable uint64_t cachedHash_ = 0;
-    mutable bool hashCached_ = false;
-    const CoordsSet& criticalTileCoords_;
-    mutable std::shared_ptr<ShardokEngine> cachedEngine_;  // Engine with cached available commands
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_STATE_HPP
@@ -1,85 +0,0 @@
-//
-// Factory implementation for creating Shardok-specific MCTS components
-//
-
-#include "ShardokMCTSFactory.hpp"
-
-#include "ShardokAction.hpp"
-#include "ShardokGameEngine.hpp"
-#include "ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-std::unique_ptr<MCTSGameEngine> ShardokMCTSFactory::createGameEngine(
-        const ShardokEngine& engine,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& gameSettings,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const CoordsSet& criticalTileCoords) {
-    return std::make_unique<ShardokGameEngine>(
-            &engine,
-            scoreCalculator,
-            gameSettings,
-            &apdCache,
-            &alCache,
-            isDefender,
-            strategy,
-            castleCoords,
-            criticalTileCoords);
-}
-
-std::unique_ptr<MCTSGameState> ShardokMCTSFactory::createGameState(
-        const GameStateW& state,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& settings,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        const CoordsSet& criticalTileCoords) {
-    return std::make_unique<ShardokGameState>(
-            state,
-            scoreCalculator,
-            settings.get(),  // Get raw pointer from shared_ptr
-            isDefender,
-            strategy,
-            castleCoords,
-            apdCache,
-            alCache,
-            criticalTileCoords);
-}
-
-std::vector<std::unique_ptr<MCTSAction>> ShardokMCTSFactory::createActions(
-        const std::vector<CommandProto>& commands) {
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    actions.reserve(commands.size());
-
-    for (size_t i = 0; i < commands.size(); ++i) {
-        actions.push_back(std::make_unique<ShardokAction>(commands[i], i));
-    }
-
-    return actions;
-}
-
-std::vector<std::unique_ptr<MCTSAction>> ShardokMCTSFactory::createActionsFromCommandList(
-        const CommandListSPtr& commands) {
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    if (!commands) { return actions; }
-
-    actions.reserve(commands->size());
-    for (size_t i = 0; i < commands->size(); ++i) {
-        const auto& cmd = (*commands)[i];
-        actions.push_back(std::make_unique<ShardokAction>(cmd->GetCommandProto(), i));
-    }
-
-    return actions;
-}
-
-}  // namespace shardok::mcts
@@ -1,85 +0,0 @@
-//
-// Factory for creating Shardok-specific MCTS components
-//
-
-#ifndef EAGLE0_SHARDOK_MCTS_FACTORY_HPP
-#define EAGLE0_SHARDOK_MCTS_FACTORY_HPP
-
-#include <functional>
-#include <memory>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-class GameStateW;
-class GameSettings;
-
-// Use existing type definitions to avoid conflicts
-// These are already defined in the Shardok codebase:
-// - APDCache in ActionPointDistancesCache.hpp
-// - ALCache in AIAttackLocations.hpp
-// - CommandListSPtr in ShardokCommand.hpp
-// - SettingsGetter in GameSettings.hpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-namespace mcts {
-
-// Forward declarations
-class MCTSGameEngine;
-class MCTSGameState;
-class MCTSAction;
-
-class ShardokMCTSFactory {
-public:
-    using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-    // Create a Shardok game engine adapter
-    [[nodiscard]] static std::unique_ptr<MCTSGameEngine> createGameEngine(
-            const ShardokEngine& engine,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& gameSettings,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const CoordsSet& criticalTileCoords);
-
-    // Create a Shardok game state adapter
-    [[nodiscard]] static std::unique_ptr<MCTSGameState> createGameState(
-            const GameStateW& state,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& settings,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            const CoordsSet& criticalTileCoords);
-
-    // Convert Shardok commands to MCTS actions
-    [[nodiscard]] static std::vector<std::unique_ptr<MCTSAction>> createActions(
-            const std::vector<CommandProto>& commands);
-
-    // Convert from command list to MCTS actions
-    [[nodiscard]] static std::vector<std::unique_ptr<MCTSAction>> createActionsFromCommandList(
-            const CommandListSPtr& commands);
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_MCTS_FACTORY_HPP
@@ -1,58 +0,0 @@
-//
-// Created by dancrosby on 3/4/20.
-//
-
-#ifndef EAGLE0_AISCORECALCULATOR_HPP
-#define EAGLE0_AISCORECALCULATOR_HPP
-
-#include <future>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-
-namespace shardok {
-
-using shardok::PlayerId;
-using std::future;
-using std::vector;
-
-using ScoreValue = double;
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-// Forward declarations
-class ShardokEngine;
-struct AIStrategy;
-
-/// Abstract base class for AI scoring algorithms.
-/// Allows testing different scoring strategies by implementing different scorers.
-class AIScoreCalculator {
-public:
-    virtual ~AIScoreCalculator() = default;
-
-    // Rule of five: explicitly default or delete copy/move operations
-    AIScoreCalculator(const AIScoreCalculator &) = default;
-    AIScoreCalculator &operator=(const AIScoreCalculator &) = default;
-    AIScoreCalculator(AIScoreCalculator &&) = default;
-    AIScoreCalculator &operator=(AIScoreCalculator &&) = default;
-
-protected:
-    AIScoreCalculator() = default;
-
-public:
-    /// Evaluate the score of a guessed game state based on the current AI strategy.
-    /// DOES NOT perform lookahead - this is pure state evaluation.
-    /// For lookahead search, use AICommandEvaluator which depends on this interface.
-    [[nodiscard]] virtual auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords) const -> ScoreValue = 0;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AISCORECALCULATOR_HPP
@@ -1,113 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "ai_score_calculator_interface",
-    hdrs = ["AIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_locations",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "ai_victory_condition_score_calculator",
-    srcs = ["AIVictoryConditionScoreCalculator.cpp"],
-    hdrs = ["AIVictoryConditionScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:__pkg__",  # Needed by abstract base class
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_groups",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_locations",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_common_types",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_distance_debuf",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_score_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
-    ],
-)
-
-cc_library(
-    name = "normalized_ai_score_calculator",
-    srcs = ["NormalizedAIScoreCalculator.cpp"],
-    hdrs = ["NormalizedAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:ai_score_calculator_shared_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
-
-cc_library(
-    name = "standard_ai_score_calculator",
-    srcs = ["StandardAIScoreCalculator.cpp"],
-    hdrs = ["StandardAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-    ],
-)
-
-cc_library(
-    name = "mcts_optimized_ai_score_calculator",
-    srcs = ["MCTSOptimizedAIScoreCalculator.cpp"],
-    hdrs = ["MCTSOptimizedAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:ai_score_calculator_shared_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-    ],
-)
@@ -1,243 +0,0 @@
-//
-// MCTS-Optimized implementation of AIScoreCalculator
-// Uses bounded linear scoring tuned for MCTS exploration/exploitation balance
-//
-
-#include "MCTSOptimizedAIScoreCalculator.hpp"
-
-#include <algorithm>
-#include <unordered_map>
-
-#include "private/AIScoreCalculatorSharedUtilities.hpp"
-#include "private/AbstractAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-using net::eagle0::shardok::storage::fb::BattalionTypeId;
-
-// Bring shared utilities into scope
-using score_calculator_internal::FleeStrategyScoreForState;
-using score_calculator_internal::UnitsScoreComponents;
-
-// Scoring constants tuned for MCTS
-namespace {
-
-// Scale constants designed to produce score differences in the range that works well for MCTS
-// With C=1.41 and typical parent visits ~10000, exploration term ≈ 0.42
-// We want:
-// - Early game tactical moves: 0.3-0.5 difference (ratio 0.7-1.2x exploration)
-// - Mid game advantages (10-30%): 4.0-8.0 difference (ratio 9-19x exploration)
-// - Late game crushing advantages: 10-40 difference (ratio 24-95x exploration)
-
-// Maximum contribution from proportional unit advantage (applies to both battle sizes)
-// A 100% unit advantage (all attacker, no defender) produces ±80 score
-constexpr double UNITS_SCORE_SCALE = 80.0;
-
-// Normalizer for victory condition scores (also proportional to army size)
-// Typical victory condition range: -3000 to 0 (raw), becomes approximately -30 to 0 (normalized)
-constexpr double VICTORY_SCORE_SCALE = 400.0;
-
-// Minimum reference value to avoid division by zero in edge cases
-constexpr double MIN_REFERENCE_VALUE = 1000.0;
-
-}  // anonymous namespace
-
-/// MCTS-Optimized implementation of AIScoreCalculator.
-/// Produces bounded linear scores that balance MCTS exploration and exploitation.
-/// Inherits from AbstractAIScoreCalculator to share common functionality.
-class MCTSOptimizedAIScoreCalculator : public AbstractAIScoreCalculator {
-public:
-    MCTSOptimizedAIScoreCalculator(
-            int maxRounds,
-            ActionPoints braveWaterCost,
-            int meteorRange,
-            double meteorCastVigorCost,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
-            std::vector<BattalionTypeSPtr> battalionTypes,
-            const APDCache &apdCache,
-            const ALCache &alCache)
-        : AbstractAIScoreCalculator(
-                  maxRounds,
-                  braveWaterCost,
-                  meteorRange,
-                  meteorCastVigorCost,
-                  minimumFleeOddsThreshold,
-                  desperateFleeThreshold,
-                  std::move(battalionTypes),
-                  apdCache,
-                  alCache) {}
-
-    [[nodiscard]] auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords) const -> ScoreValue override;
-
-    // Implement pure virtual methods from AbstractAIScoreCalculator
-    [[nodiscard]] auto InterpretDefenderOutcome(GameOutcome outcome) const -> ScoreValue override;
-    [[nodiscard]] auto InterpretAttackerOutcome(GameOutcome outcome) const -> ScoreValue override;
-
-    [[nodiscard]] auto AttackerFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineAttackerScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderScatterScores(const UnitsScoreComponents &components) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderHoldCastlesScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-private:
-    [[nodiscard]] auto DefenderFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-};
-
-// Implementation of MCTSOptimizedAIScoreCalculator methods
-
-auto MCTSOptimizedAIScoreCalculator::InterpretDefenderOutcome(GameOutcome outcome) const
-        -> ScoreValue {
-    // Use bounded values instead of INT_MAX/MIN for numerical stability
-    switch (outcome) {
-        case GameOutcome::DEFENDER_VICTORY: return 1000.0;
-        case GameOutcome::ATTACKER_VICTORY: return -1000.0;
-        case GameOutcome::DRAW: return 0.0;
-        case GameOutcome::FLEE_OUTCOME: return 0.0;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto MCTSOptimizedAIScoreCalculator::InterpretAttackerOutcome(GameOutcome outcome) const
-        -> ScoreValue {
-    // Use bounded values instead of INT_MAX/MIN for numerical stability
-    switch (outcome) {
-        case GameOutcome::ATTACKER_VICTORY: return 1000.0;
-        case GameOutcome::DEFENDER_VICTORY: return -1000.0;
-        case GameOutcome::DRAW: return 0.0;
-        case GameOutcome::FLEE_OUTCOME: return 0.0;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto MCTSOptimizedAIScoreCalculator::CombineAttackerScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int roundsRemaining) const -> ScoreValue {
-    // Use actual total army value as reference (scales with battle size)
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // Normalize proportional unit difference to approximately [-80, +80] range
-    const double unitsDiff = components.attackerUnitsValue - components.defenderUnitsValue;
-    const double unitsScore = (unitsDiff / reference) * UNITS_SCORE_SCALE;
-
-    // Normalize victory condition (also proportional to army size) to approximately [-40, 0] range
-    const double victoryScore = (victoryConditionScore / reference) * VICTORY_SCORE_SCALE;
-
-    // Weight units by rounds remaining (early: units matter less, late: units dominate)
-    const double unitsMultiplier =
-            static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-
-    return unitsMultiplier * unitsScore + victoryScore;
-}
-
-auto MCTSOptimizedAIScoreCalculator::CombineDefenderScatterScores(
-        const UnitsScoreComponents &components) const -> ScoreValue {
-    // Use actual total army value as reference
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // For scatter strategy, just maximize proportional defender advantage
-    const double unitsDiff = components.defenderUnitsValue - components.attackerUnitsValue;
-    return (unitsDiff / reference) * UNITS_SCORE_SCALE;
-}
-
-auto MCTSOptimizedAIScoreCalculator::CombineDefenderHoldCastlesScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int roundsRemaining) const -> ScoreValue {
-    // Use actual total army value as reference
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // Similar to attacker, but from defender's perspective
-    const double unitsDiff = components.defenderUnitsValue - components.attackerUnitsValue;
-    const double unitsScore = (unitsDiff / reference) * UNITS_SCORE_SCALE;
-    const double victoryScore = (victoryConditionScore / reference) * VICTORY_SCORE_SCALE;
-
-    const double unitsMultiplier =
-            static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-
-    return unitsMultiplier * unitsScore + victoryScore;
-}
-
-auto MCTSOptimizedAIScoreCalculator::DefenderFleeStrategyScoreForState(
-        const GameStateW &gameState) const -> ScoreValue {
-    for (const auto *pi : *gameState->player_infos()) {
-        if (pi->is_defender()) { return FleeStrategyScoreForState(gameState, pi->player_id()); }
-    }
-    throw ShardokInternalErrorException("Unable to find defender for FleeStrategy");
-}
-
-auto MCTSOptimizedAIScoreCalculator::AttackerFleeStrategyScoreForState(
-        const GameStateW &gameState) const -> ScoreValue {
-    for (const PlayerInfo *pi : *gameState->player_infos()) {
-        if (!pi->is_defender()) { return FleeStrategyScoreForState(gameState, pi->player_id()); }
-    }
-    throw ShardokInternalErrorException("Unable to find attacker for FleeStrategy");
-}
-
-auto MCTSOptimizedAIScoreCalculator::GuessedStateScore(
-        const bool isDefender,
-        const GameStateW &state,
-        const AIStrategy &aiStrategy,
-        const CoordsSet &allCastleCoords) const -> ScoreValue {
-    const int roundsRemaining = GetMaxRounds() - state->current_round();
-
-    if (isDefender) {
-        return DefenderScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-    }
-    return AttackerScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-}
-
-// Factory function implementation
-auto MakeMCTSOptimizedAIScoreCalculator(
-        const SettingsGetter &settingsGetter,
-        const APDCache &apdCache,
-        const ALCache &alCache) -> std::unique_ptr<AIScoreCalculator> {
-    // Extract all battalion types into a vector indexed by BattalionTypeId
-    std::vector<BattalionTypeSPtr> battalionTypes(BattalionTypeId::BattalionTypeId_MAX + 1);
-    for (int typeId = BattalionTypeId::BattalionTypeId_MIN;
-         typeId <= BattalionTypeId::BattalionTypeId_MAX;
-         typeId++) {
-        auto battalionTypeId = static_cast<BattalionTypeId>(typeId);
-        battalionTypes[battalionTypeId] = settingsGetter.GetBattalionType(battalionTypeId);
-    }
-
-    return std::make_unique<MCTSOptimizedAIScoreCalculator>(
-            settingsGetter.Backing().max_rounds(),
-            settingsGetter.Backing().brave_water_action_point_cost(),
-            settingsGetter.Backing().meteor_range(),
-            settingsGetter.Backing().meteor_cast_vigor_cost(),
-            settingsGetter.Backing().ai_minimum_flee_odds_threshold(),
-            settingsGetter.Backing().ai_desperate_flee_threshold(),
-            std::move(battalionTypes),
-            apdCache,
-            alCache);
-}
-
-}  // namespace shardok
@@ -1,32 +0,0 @@
-//
-// MCTS-Optimized implementation of AIScoreCalculator
-// Uses bounded linear scoring tuned for MCTS exploration/exploitation balance
-//
-
-#ifndef EAGLE0_MCTSOPTIMIZEDAISCORECALCULATOR_HPP
-#define EAGLE0_MCTSOPTIMIZEDAISCORECALCULATOR_HPP
-
-#include <memory>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-
-using APDCache = std::shared_ptr<ActionPointDistancesCache>;
-using ALCache = std::unique_ptr<AttackLocationsCache>;
-
-/// Factory function to create an MCTSOptimizedAIScoreCalculator.
-/// Returns a unique_ptr to AIScoreCalculator to hide the implementation.
-[[nodiscard]] auto MakeMCTSOptimizedAIScoreCalculator(
-        const SettingsGetter& settingsGetter,
-        const APDCache& apdCache,
-        const ALCache& alCache) -> std::unique_ptr<AIScoreCalculator>;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTSOPTIMIZEDAISCORECALCULATOR_HPP
@@ -1,388 +0,0 @@
-# MCTS-Optimized Scoring Algorithm Design
-
-## Problem Statement
-
-We need a scoring algorithm that makes MCTS perform well by providing score differences in the right range:
-
- **Standard Scorer**: Returns unbounded relative scores. Small differences get amplified in MCTS UCB formula, causing over-exploitation (commits to 1-2 high-scoring nodes too early).
- **Normalized Scorer**: Returns scores in [0,1] range with power transformation (exponent=0.1). Differences are too compressed (~0.02-0.05), causing over-exploration (all nodes explored equally, AI makes bad choices).
-
-### MCTS Requirements
-
-After ~100 visits, the **exploitation term** (cumulative_score / visits) should be comparable to the **exploration term** (C * sqrt(ln(parent_visits) / visits)).
-
-With C=1.41 and typical parent visits ~10000:
- Exploration term: 1.41 * sqrt(ln(10000) / 100) ≈ 0.42
- **Target exploitation differences: 0.5 to 2.0**
-
-This means individual scores should differ by **0.5 to 2.0** between meaningfully different positions.
-
-## Scale Analysis from Codebase
-
-### Unit Values
- Single unit context-free value: 500-3000 (depends on battalion type, stats, size)
- With modifiers (castle, terrain, ranged): 1000-6000 per unit
- Full army (10 units max): 10,000-40,000
- Typical strong army: ~20,000
-
-### Victory Condition Scores
- Castle held by defender: -(battalion_size + vigor) * distance_debuf ≈ -800 per castle
- Distance debuf: 0.0 (adjacent) to 1.0 (unreachable), typically 0.9-0.95
- 3 castles held by defender at medium distance: ≈ -2400
- Range: 0 (all captured) to -3000 (all held, far away)
-
-### Terminal States
- Victory: INT_MAX (or 1.0 for normalized)
- Defeat: INT_MIN (or 0.0 for normalized)
- Flee/Draw: 0 (or 0.5 for normalized)
- Captured unit: -10,000
- Captured VIP: -25,000
-
-## Proposed Algorithm: Bounded Linear Scorer
-
-### Design Principles
-
-1. **Normalized scale**: Map scores to approximately [-15, +15] range
-2. **Separate components**: Units and victory conditions contribute separately
-3. **Preserve relative importance**: Victory conditions dominate early, units become important as advantage grows
-4. **Round-based weighting**: Similar to Standard scorer, weight units by rounds remaining
-
-### Constants
-
-```cpp
-constexpr double UNITS_SCORE_SCALE = 80.0;      // Max contribution from proportional unit advantage
-constexpr double VICTORY_SCORE_SCALE = 400.0;   // Normalizer for victory conditions (also proportional)
-constexpr double MIN_REFERENCE_VALUE = 1000.0;  // Avoid division by zero in edge cases
-```
-
-**Key insights**:
-1. Both unit scores AND victory condition scores scale proportionally with battle size (victory scores use battalion.size() in their calculation). Therefore, we normalize both by the **actual total army value** rather than a fixed reference.
-
-2. **MCTS requires stronger signal than minimax**: Minimax (Iterative Deepening) just picks argmax, so even tiny score differences (0.01) work fine. MCTS needs score differences comparable to the exploration term (~0.4-0.5) to guide search effectively. We use 10x larger scale constants to amplify tactical differences like positioning, distance to objectives, and incremental unit advantages.
-
-### Attacker Score Formula
-
-```cpp
-auto CombineAttackerScores(
-    const UnitsScoreComponents &components,
-    double victoryConditionScore,
-    int roundsRemaining) const -> ScoreValue {
-
-    // Use actual total army value as reference (scales with battle size)
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // Normalize proportional unit difference to [-8, +8] range
-    const double unitsDiff = components.attackerUnitsValue - components.defenderUnitsValue;
-    const double unitsScore = (unitsDiff / reference) * UNITS_SCORE_SCALE;
-
-    // Normalize victory condition (also proportional to army size) to approximately [-10, 0] range
-    const double victoryScore = (victoryConditionScore / reference) * VICTORY_SCORE_SCALE;
-
-    // Weight units by rounds remaining (early: units matter less, late: units dominate)
-    const double unitsMultiplier =
-        static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-
-    return unitsMultiplier * unitsScore + victoryScore;
-}
-```
-
-### Defender Score Formula
-
-```cpp
-auto CombineDefenderScatterScores(
-    const UnitsScoreComponents &components) const -> ScoreValue {
-
-    // Use actual total army value as reference
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // For scatter strategy, just maximize proportional defender advantage
-    const double unitsDiff = components.defenderUnitsValue - components.attackerUnitsValue;
-    return (unitsDiff / reference) * UNITS_SCORE_SCALE;
-}
-
-auto CombineDefenderHoldCastlesScores(
-    const UnitsScoreComponents &components,
-    double victoryConditionScore,
-    int roundsRemaining) const -> ScoreValue {
-
-    // Use actual total army value as reference
-    const double totalArmyValue = components.attackerUnitsValue + components.defenderUnitsValue;
-    const double reference = std::max(totalArmyValue, MIN_REFERENCE_VALUE);
-
-    // Similar to attacker, but from defender's perspective
-    const double unitsDiff = components.defenderUnitsValue - components.attackerUnitsValue;
-    const double unitsScore = (unitsDiff / reference) * UNITS_SCORE_SCALE;
-    const double victoryScore = (victoryConditionScore / reference) * VICTORY_SCORE_SCALE;
-
-    const double unitsMultiplier =
-        static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-
-    return unitsMultiplier * unitsScore + victoryScore;
-}
-```
-
-### Terminal States
-
-```cpp
-auto InterpretAttackerOutcome(GameOutcome outcome) const -> ScoreValue {
-    switch (outcome) {
-        case GameOutcome::ATTACKER_VICTORY: return 1000.0;  // Large but bounded
-        case GameOutcome::DEFENDER_VICTORY: return -1000.0;
-        case GameOutcome::DRAW: return 0.0;
-        case GameOutcome::FLEE_OUTCOME: return 0.0;
-    }
-}
-```
-
-Note: Using bounded values (±1000) instead of INT_MAX/MIN ensures numerical stability in MCTS and clearer signal that these are terminal states.
-
-## Example Score Traces
-
-### Large Battle Scenarios (10v10, ~40000 total army)
-
-#### Scenario 1: Even armies, attacker needs to capture 3 castles
- Units: attacker 20000, defender 20000 (total: 40000)
- Victory: -2850 (3 castles * 950 each, medium distance)
- Rounds: 15/30 remaining
-
-Score:
- reference = 40000
- unitsDiff = 0
- unitsScore = 0
- victoryScore = (-2850 / 40000) * 400.0 = -28.5
- unitsMultiplier = 0.5
- **total = 0.5 * 0 + (-28.5) = -28.5**
-
-#### Scenario 2: Slight attacker advantage (10%)
- Units: attacker 22000, defender 18000 (diff: +4000, total: 40000)
- Victory: -2850
- Rounds: 15/30
-
-Score:
- unitsScore = (4000 / 40000) * 80.0 = 8.0
- victoryScore = -28.5
- unitsMultiplier = 0.5
- **total = 0.5 * 8.0 + (-28.5) = -24.5**
- **Difference from Scenario 1: 4.0** ✓
-
-#### Scenario 3: Large attacker advantage (30%)
- Units: attacker 26000, defender 14000 (diff: +12000, total: 40000)
- Victory: -2850
- Rounds: 15/30
-
-Score:
- unitsScore = (12000 / 40000) * 80.0 = 24.0
- victoryScore = -28.5
- unitsMultiplier = 0.5
- **total = 0.5 * 24.0 + (-28.5) = -16.5**
- **Difference from Scenario 2: 8.0** ✓
-
-### Small Battle Scenarios (2v2, ~4000 total army)
-
-#### Scenario 4: Even small armies, 1 castle
- Units: attacker 2000, defender 2000 (total: 4000)
- Victory: -475 (1 castle * 500 * 0.95 distance)
- Rounds: 15/30
-
-Score:
- reference = 4000
- unitsScore = 0
- victoryScore = (-475 / 4000) * 400.0 = -47.5
- **total = 0.5 * 0 + (-47.5) = -47.5**
-
-#### Scenario 5: Slight advantage in small battle (10%)
- Units: attacker 2200, defender 1800 (diff: +400, total: 4000)
- Victory: -475
- Rounds: 15/30
-
-Score:
- unitsScore = (400 / 4000) * 80.0 = 8.0
- victoryScore = -47.5
- **total = 0.5 * 8.0 + (-47.5) = -43.5**
- **Difference from Scenario 4: 4.0** ✓
-
-### Early Game Scenario: Single unit movement
-
-#### Scenario 6: Early game, single unit advances toward castle
- Units: attacker 20000, defender 20000 (total: 40000)
- Victory before: -2850 (distance debuf = 0.95)
- Victory after: -2829 (distance debuf = 0.943, one unit moved closer)
- Change in victory score: +21
- Rounds: 28/30 (early game)
-
-Score change:
- victoryScoreChange = (21 / 40000) * 400.0 = 0.21
- Additionally, the moving unit (value 2000) gets better distance multiplier:
-  - Before: 2000 * 0.25 = 500
-  - After: 2000 * 0.279 = 558
-  - Diff = 58, normalized: (58 / 40000) * 80.0 = 0.116
- unitsMultiplier = 28/30 = 0.933
- **Total improvement: 0.21 + 0.933 * 0.116 = 0.32** ✓
-
-With exploration term ~0.42, this gives exploitation/exploration ratio of **0.76** - still below 1.0 but much better than before (was 0.05). MCTS will slightly prefer better moves while still exploring alternatives.
-
-### Scale Consistency Verification
-
-Comparing **10% advantage** in both battle sizes:
- Large battle (Scenario 2): diff = **4.0**
- Small battle (Scenario 5): diff = **4.0**
-
-**Perfect scaling!** Same proportional advantage → same score difference, regardless of battle size.
-
-Early game tactical moves now produce meaningful signals (0.3-0.5 range) that guide MCTS while still allowing healthy exploration.
-
-## MCTS Behavior Verification
-
-After 100 visits with C=1.41, exploration term ~0.42:
-
-**Early game (single unit tactical moves):**
- Good positioning move: **0.32** (ratio 0.76x exploration)
- MCTS explores broadly but slightly favors better moves
-
-**Mid game (unit advantages matter):**
- 10% army advantage: **4.0** (ratio 9.5x exploration)
- 30% army advantage: **8.0** (ratio 19x exploration)
- MCTS strongly commits to maintaining/increasing army advantage
-
-**Late game (large differences):**
- Major strategic advantages: **10-40** (ratio 24-95x exploration)
- MCTS decisively exploits winning positions
-
-This progression is ideal:
- **Early game**: Healthy exploration (ratio < 1.0) when moves are genuinely similar
- **Mid game**: Strong exploitation (ratio 9-19x) when clear advantages exist
- **Late game**: Decisive exploitation (ratio > 20x) to close out wins
-
-This avoids both pathologies:
- Not over-exploiting (like Standard scorer which overcommitted to tiny early differences)
- Not over-exploring (like Normalized scorer which explored equally even with large advantages)
-
-## Why MCTS Needs Stronger Signal Than Minimax
-
-**Iterative Deepening (minimax)** works fine with tiny score differences (0.01-0.1) because:
- It explores all moves to the same depth
- It simply picks `argmax(scores)`
- Even a 0.01 difference causes it to prefer the better move
-
-**MCTS** needs much larger differences (0.3-4.0) because:
- It uses UCB formula: `score/visits + C*sqrt(ln(parent_visits)/visits)`
- The exploration term (~0.4) can dominate small exploitation differences
- With differences < 0.1, MCTS explores all moves almost equally (over-exploration)
- With differences > 10.0, MCTS commits too early (over-exploitation)
-
-**Solution**: Use 10x larger scale constants than initially designed, specifically tuned so that:
- Early game tactical moves (positioning, distance) produce 0.3-0.5 differences
- Mid game advantages (10-30% army strength) produce 4.0-8.0 differences
- Late game crushing advantages produce 10-40 differences
-
-This gives MCTS the right balance: explore when moves are similar, exploit when advantages are clear.
-
-## Implementation Notes
-
-1. **Use same calculation structure**: Inherit from AbstractAIScoreCalculator like Standard and Normalized
-2. **Reuse unit scoring**: Use existing CalculateUnitsScoreComponents and victory condition calculators
-3. **Only change combination**: Override CombineAttackerScores, CombineDefenderScores, etc.
-4. **Bounded terminals**: Use ±1000 instead of INT_MAX/MIN for numerical stability
-5. **No transformation**: Unlike Normalized, don't apply power transformation - linear scaling is sufficient
-6. **Scale constants tuned for MCTS**: 10x larger than naive normalization to provide appropriate signal strength
-
-## Testing with Integration Tests
-
-Before integrating with MCTS, test the new scorer with **IterativeDeepeningAI** using the AI integration test infrastructure.
-
-### Integration Test Infrastructure
-
-The codebase now has comprehensive AI integration tests in `src/test/cpp/net/eagle0/shardok/ai/AIIntegrationTest.cpp` that use:
-
-1. **AIPerformanceTestHelpers** (`src/test/cpp/net/eagle0/shardok/library/AIPerformanceTestHelpers.{cpp,hpp}`):
-   - `CreatePerfTestGameState(settings, defenderToggle)` creates a 6v6 scenario on the Alah map
-   - Properly initializes units with correct battalion sizes (800 for longbowmen, capacity-based for others)
-   - Handles both attacker and defender perspectives
-   - Returns GameStateW in SETUP phase with 6 units per player in reserve
-
-2. **ShardokAIClient** integration:
-   - Tests use the full AI client interface, not just the search algorithm
-   - Time budgets set to 3s for reasonable test execution time
-   - Handles both setup phase placement and first turn movement
-
-3. **Acceptable Position Sets** for handling AI non-determinism:
-   - AI decisions may vary due to internal tie-breaking and search order
-   - Tests define sets of acceptable positions for each unit
-   - Example from AttackerAI_Setup_PlacesUnitsCorrectly:
-     ```cpp
-     std::set<net::eagle0::shardok::storage::fb::Coords> acceptablePositions{
-         net::eagle0::shardok::storage::fb::Coords(0, 11),
-         net::eagle0::shardok::storage::fb::Coords(1, 10),
-         // ... more acceptable positions
-     };
-     ```
-
-### Adding Tests for New Scorers
-
-To test MCTSOptimizedAIScoreCalculator (or any new scorer) with IterativeDeepeningAI:
-
-1. **Add test cases following the existing pattern** in `AIIntegrationTest.cpp`:
-   ```cpp
-   TEST(MCTSOptimizedScorerTest, AttackerAI_Setup_PlacesUnitsCorrectly) {
-       auto settings = GetDefaultGameSettingsForTest();
-       auto gameStateW = CreatePerfTestGameState(settings, /*defenderToggle=*/false);
-       auto hexMap = gameStateW.GetHexMap().ToProto();
-
-       // Use MCTSOptimizedAIScoreCalculator instead of StandardAIScoreCalculator
-       auto scoreCalculator = std::make_shared<MCTSOptimizedAIScoreCalculator>(
-           /*playerId=*/0, /*isDefender=*/false, hexMap, settings->GetGetter());
-
-       ShardokAIClient client(
-           /*playerId=*/0, /*isDefender=*/false, hexMap, settings,
-           scoreCalculator, std::chrono::milliseconds(3000));
-
-       // ... rest of test follows existing pattern
-   }
-   ```
-
-2. **Update BUILD.bazel** to add the new scorer as a dependency:
-   ```bazel
-   deps = [
-       # ... existing deps ...
-       "//src/main/cpp/net/eagle0/shardok/ai/score:mcts_optimized_ai_score_calculator",
-   ]
-   ```
-
-3. **Test patterns to implement**:
-   - **Setup Phase Tests**: Verify AI places units in reasonable starting positions
-     - `AttackerAI_Setup_PlacesUnitsCorrectly`: Attacker should place at start zone (0,11)-(1,13)
-     - `DefenderAI_Setup_OccupiesCastles`: Defender should occupy castle tiles
-   - **First Turn Tests**: Verify AI makes sensible initial moves
-     - `AttackerAI_FirstTurn_MovesUnitsCorrectly`: Attacker should advance toward objectives
-     - Use acceptable position sets to handle non-determinism
-   - **Score Range Verification**: Add assertions to verify scores are in expected ranges
-     ```cpp
-     // Example: verify scores are bounded as expected
-     auto searchResult = client.GetBestCommand(gameStateW);
-     EXPECT_GE(searchResult.score, -50.0);  // Reasonable lower bound
-     EXPECT_LE(searchResult.score, 50.0);   // Reasonable upper bound
-     ```
-
-4. **Performance Regression Testing**:
-   - Run `./scripts/ai_perf_test.sh` to verify the new scorer doesn't cause performance degradation
-   - Compare commands evaluated at each depth vs. StandardAIScoreCalculator
-   - See CLAUDE.md "Performance Testing" section for detailed instructions
-
-### Why Test with IterativeDeepeningAI First
-
-The new scoring algorithm should work with **both** IterativeDeepeningAI and MCTS:
- If it fails with IterativeDeepeningAI, the scoring logic itself is broken
- If it passes with IterativeDeepeningAI but fails with MCTS, the issue is MCTS-specific
- This allows incremental testing and debugging
-
-Once the scorer passes integration tests with IterativeDeepeningAI, then integrate with MCTS and compare behavior.
-
-## Alternative Names
-
- `BoundedLinearAIScoreCalculator`
- `MCTSOptimizedAIScoreCalculator`
- `LinearNormalizedAIScoreCalculator`
-
-Recommend: **`MCTSOptimizedAIScoreCalculator`** to clearly indicate purpose.
@@ -1,252 +0,0 @@
-//
-// Normalized [0,1] implementation of AIScoreCalculator
-//
-
-#include "NormalizedAIScoreCalculator.hpp"
-
-#include <cmath>
-#include <unordered_map>
-
-#include "private/AIScoreCalculatorSharedUtilities.hpp"
-#include "private/AbstractAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-using net::eagle0::shardok::storage::fb::BattalionTypeId;
-
-// Bring shared utilities into scope
-using score_calculator_internal::UnitsScoreComponents;
-
-/// Normalized implementation of AIScoreCalculator that produces scores in [0, 1] range.
-/// Inherits from AbstractAIScoreCalculator to share common functionality.
-class NormalizedAIScoreCalculator : public AbstractAIScoreCalculator {
-public:
-    NormalizedAIScoreCalculator(
-            int maxRounds,
-            ActionPoints braveWaterCost,
-            int meteorRange,
-            double meteorCastVigorCost,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
-            std::vector<BattalionTypeSPtr> battalionTypes,
-            const APDCache &apdCache,
-            const ALCache &alCache)
-        : AbstractAIScoreCalculator(
-                  maxRounds,
-                  braveWaterCost,
-                  meteorRange,
-                  meteorCastVigorCost,
-                  minimumFleeOddsThreshold,
-                  desperateFleeThreshold,
-                  std::move(battalionTypes),
-                  apdCache,
-                  alCache) {}
-
-    [[nodiscard]] auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords) const -> ScoreValue override;
-
-    // Implement pure virtual methods from AbstractAIScoreCalculator
-    [[nodiscard]] auto InterpretDefenderOutcome(GameOutcome outcome) const -> ScoreValue override;
-    [[nodiscard]] auto InterpretAttackerOutcome(GameOutcome outcome) const -> ScoreValue override;
-
-    [[nodiscard]] auto AttackerFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineAttackerScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderScatterScores(const UnitsScoreComponents &components) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderHoldCastlesScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-private:
-    [[nodiscard]] auto DefenderFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-
-    /// Applies power transformation to spread out compressed scores for MCTS.
-    /// Maps [0,1] → [0,1] but pushes values away from 0.5 toward the extremes.
-    /// Terminal states (0.0, 1.0) are unchanged.
-    [[nodiscard]] auto TransformForMCTS(ScoreValue score) const -> ScoreValue;
-};
-
-// Implementation of NormalizedAIScoreCalculator methods
-
-auto NormalizedAIScoreCalculator::InterpretDefenderOutcome(GameOutcome outcome) const
-        -> ScoreValue {
-    switch (outcome) {
-        case GameOutcome::DEFENDER_VICTORY: return 1.0;
-        case GameOutcome::ATTACKER_VICTORY: return 0.0;
-        case GameOutcome::DRAW: return 0.5;
-        case GameOutcome::FLEE_OUTCOME: return 0.5;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto NormalizedAIScoreCalculator::InterpretAttackerOutcome(GameOutcome outcome) const
-        -> ScoreValue {
-    switch (outcome) {
-        case GameOutcome::ATTACKER_VICTORY: return 1.0;
-        case GameOutcome::DEFENDER_VICTORY: return 0.0;
-        case GameOutcome::DRAW: return 0.5;
-        case GameOutcome::FLEE_OUTCOME: return 0.5;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto NormalizedAIScoreCalculator::CombineDefenderScatterScores(
-        const UnitsScoreComponents &components) const -> ScoreValue {
-    // For defender, we flip the perspective: defenderValue is (1), attackerValue is (2)
-    const double defenderValue = components.defenderUnitsValue;
-    const double attackerValue = components.attackerUnitsValue;
-
-    // No victory condition for scatter strategy
-    const double denominator = defenderValue + attackerValue;
-    if (denominator == 0.0) { return 0.5; }
-
-    return defenderValue / denominator;
-}
-
-auto NormalizedAIScoreCalculator::CombineDefenderHoldCastlesScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int /*roundsRemaining*/) const -> ScoreValue {
-    // For defender, flip perspective
-    const double defenderValue = components.defenderUnitsValue;
-    const double attackerValue = components.attackerUnitsValue;
-
-    // Apply normalization
-    double numerator;
-    double denominator;
-
-    if (victoryConditionScore >= 0) {
-        numerator = defenderValue + victoryConditionScore;
-        denominator = defenderValue + attackerValue + victoryConditionScore;
-    } else {
-        numerator = defenderValue;
-        denominator = defenderValue + attackerValue - victoryConditionScore;
-    }
-
-    if (denominator == 0.0) { return 0.5; }
-
-    return numerator / denominator;
-}
-
-auto NormalizedAIScoreCalculator::DefenderFleeStrategyScoreForState(
-        const GameStateW & /*gameState*/) const -> ScoreValue {
-    // FLEE strategy doesn't fit the [0,1] model well - return 0.5
-    return 0.5;
-}
-
-auto NormalizedAIScoreCalculator::AttackerFleeStrategyScoreForState(
-        const GameStateW & /*gameState*/) const -> ScoreValue {
-    // FLEE strategy doesn't fit the [0,1] model well - return 0.5
-    return 0.5;
-}
-
-auto NormalizedAIScoreCalculator::CombineAttackerScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int /*roundsRemaining*/) const -> ScoreValue {
-    const double attackerUnitsValue = components.attackerUnitsValue;
-    const double defenderUnitsValue = components.defenderUnitsValue;
-
-    // Apply normalization formula
-    double numerator;
-    double denominator;
-
-    if (victoryConditionScore >= 0) {
-        // Positive victory condition: add to numerator
-        numerator = attackerUnitsValue + victoryConditionScore;
-        denominator = attackerUnitsValue + defenderUnitsValue + victoryConditionScore;
-    } else {
-        // Negative victory condition: subtract from denominator (making it larger)
-        numerator = attackerUnitsValue;
-        denominator = attackerUnitsValue + defenderUnitsValue - victoryConditionScore;
-    }
-
-    // Handle edge case of all zeros
-    if (denominator == 0.0) { return 0.5; }
-
-    return numerator / denominator;
-}
-
-auto NormalizedAIScoreCalculator::TransformForMCTS(ScoreValue score) const -> ScoreValue {
-    // Power transformation exponent - lower values spread scores more toward extremes
-    // Tuned for MCTS: balances exploration vs exploitation
-    // - Too low (e.g., 0.3): over-exploitation like standard scorer
-    // - Too high (e.g., 0.9): over-exploration like untransformed normalized
-    // - 0.6-0.7: sweet spot for MCTS
-    constexpr double EXPONENT = 0.1;
-
-    if (score > 0.5) {
-        // Map [0.5, 1.0] → [0.5, 1.0] with power curve
-        // (score - 0.5) * 2.0 maps to [0, 1], apply power, then scale back
-        return 0.5 + 0.5 * std::pow((score - 0.5) * 2.0, EXPONENT);
-    } else {
-        // Map [0.0, 0.5] → [0.0, 0.5] with power curve (symmetric)
-        return 0.5 - 0.5 * std::pow((0.5 - score) * 2.0, EXPONENT);
-    }
-}
-
-auto NormalizedAIScoreCalculator::GuessedStateScore(
-        const bool isDefender,
-        const GameStateW &state,
-        const AIStrategy &aiStrategy,
-        const CoordsSet &allCastleCoords) const -> ScoreValue {
-    const int roundsRemaining = GetMaxRounds() - state->current_round();
-
-    ScoreValue rawScore;
-    if (isDefender) {
-        rawScore = DefenderScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-    } else {
-        rawScore = AttackerScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-    }
-
-    // Apply power transformation to spread out scores for MCTS
-    return TransformForMCTS(rawScore);
-}
-
-// Factory function implementation
-auto MakeNormalizedAIScoreCalculator(
-        const SettingsGetter &settingsGetter,
-        const APDCache &apdCache,
-        const ALCache &alCache) -> std::unique_ptr<AIScoreCalculator> {
-    // Extract all battalion types into a vector indexed by BattalionTypeId
-    std::vector<BattalionTypeSPtr> battalionTypes(BattalionTypeId::BattalionTypeId_MAX + 1);
-    for (int typeId = BattalionTypeId::BattalionTypeId_MIN;
-         typeId <= BattalionTypeId::BattalionTypeId_MAX;
-         typeId++) {
-        auto battalionTypeId = static_cast<BattalionTypeId>(typeId);
-        battalionTypes[battalionTypeId] = settingsGetter.GetBattalionType(battalionTypeId);
-    }
-
-    return std::make_unique<NormalizedAIScoreCalculator>(
-            settingsGetter.Backing().max_rounds(),
-            settingsGetter.Backing().brave_water_action_point_cost(),
-            settingsGetter.Backing().meteor_range(),
-            settingsGetter.Backing().meteor_cast_vigor_cost(),
-            settingsGetter.Backing().ai_minimum_flee_odds_threshold(),
-            settingsGetter.Backing().ai_desperate_flee_threshold(),
-            std::move(battalionTypes),
-            apdCache,
-            alCache);
-}
-
-}  // namespace shardok
@@ -1,44 +0,0 @@
-//
-// Normalized [0,1] implementation of AIScoreCalculator
-//
-
-#ifndef EAGLE0_NORMALIZEDAISCORECALCULATOR_HPP
-#define EAGLE0_NORMALIZEDAISCORECALCULATOR_HPP
-
-#include <memory>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-
-using APDCache = std::shared_ptr<ActionPointDistancesCache>;
-using ALCache = std::unique_ptr<AttackLocationsCache>;
-
-/// Factory function to create a NormalizedAIScoreCalculator.
-/// Returns a unique_ptr to AIScoreCalculator to hide the implementation.
-///
-/// The normalized scorer produces scores in the range [0, 1] where:
-/// - 0.0 = complete defender victory
-/// - 1.0 = complete attacker victory
-/// - 0.5 = neutral/draw state
-///
-/// Terminal states (victory/defeat) always return 1.0 or 0.0.
-/// Non-terminal states use asymmetric normalization:
-/// - If victory condition >= 0:
-///   score = (attackerUnits + victoryCondition) / (attackerUnits + defenderUnits +
-///   victoryCondition)
-/// - If victory condition < 0:
-///   score = attackerUnits / (attackerUnits + defenderUnits - victoryCondition)
-[[nodiscard]] auto MakeNormalizedAIScoreCalculator(
-        const SettingsGetter& settingsGetter,
-        const APDCache& apdCache,
-        const ALCache& alCache) -> std::unique_ptr<AIScoreCalculator>;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_NORMALIZEDAISCORECALCULATOR_HPP
@@ -1,281 +0,0 @@
-//
-// Standard implementation of AIScoreCalculator
-//
-
-#include "StandardAIScoreCalculator.hpp"
-
-#include <atomic>
-#include <chrono>
-#include <unordered_map>
-
-#include "private/AIScoreCalculatorSharedUtilities.hpp"
-#include "private/AbstractAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-using net::eagle0::shardok::storage::fb::BattalionTypeId;
-
-// Bring shared utilities into scope
-using score_calculator_internal::AttackerMultiplierForTargetDistance;
-using score_calculator_internal::CAPTURED_UNIT_SCORE;
-using score_calculator_internal::CAPTURED_VIP_SCORE;
-using score_calculator_internal::EffectiveDistanceCache;
-using score_calculator_internal::FleeStrategyScoreForState;
-using score_calculator_internal::UNITS_BASE_MULTIPLIER;
-
-// Forward declare the implementation class
-class StandardAIScoreCalculator;
-
-// Anonymous namespace for helper functions that don't need access to scorer
-namespace {
-
-#define LOGGING_ 0
-#define PERFORMANCE_LOGGING_ 0
-
-// Performance logging for AttackerScoreForState
-struct AttackerScorePerformanceLogger {
-    static constexpr int LOG_INTERVAL = 100000;
-
-    static std::atomic<int> callCount;
-    static std::atomic<double> intervalTime;
-    static std::atomic<double> totalTime;
-
-    static void LogCall(double duration) {
-        callCount.fetch_add(1);
-        intervalTime.fetch_add(duration);
-        totalTime.fetch_add(duration);
-
-        if (callCount.load() % LOG_INTERVAL == 0) {
-            double intervalAvg = intervalTime.load() / LOG_INTERVAL;
-            double overallAvg = totalTime.load() / callCount.load();
-            printf("AttackerScoreForState: %d calls, last %d avg: %.1f µs, overall avg: %.1f µs\n",
-                   callCount.load(),
-                   LOG_INTERVAL,
-                   intervalAvg * 1000000.0,
-                   overallAvg * 1000000.0);
-            intervalTime.store(0.0);  // Reset for next interval
-        }
-    }
-};
-
-std::atomic<int> AttackerScorePerformanceLogger::callCount{0};
-std::atomic<double> AttackerScorePerformanceLogger::intervalTime{0.0};
-std::atomic<double> AttackerScorePerformanceLogger::totalTime{0.0};
-
-// RAII timer for automatic performance logging
-class AttackerScoreTimer {
-private:
-    std::chrono::high_resolution_clock::time_point startTime;
-
-public:
-    AttackerScoreTimer() : startTime(std::chrono::high_resolution_clock::now()) {}
-
-    ~AttackerScoreTimer() {
-        auto endTime = std::chrono::high_resolution_clock::now();
-        auto duration =
-                std::chrono::duration_cast<std::chrono::duration<double>>(endTime - startTime);
-        AttackerScorePerformanceLogger::LogCall(duration.count());
-    }
-};
-}  // anonymous namespace
-
-/// Standard implementation of AIScoreCalculator that uses the default scoring algorithm.
-/// Inherits from AbstractAIScoreCalculator to share common functionality.
-class StandardAIScoreCalculator : public AbstractAIScoreCalculator {
-public:
-    StandardAIScoreCalculator(
-            int maxRounds,
-            ActionPoints braveWaterCost,
-            int meteorRange,
-            double meteorCastVigorCost,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
-            std::vector<BattalionTypeSPtr> battalionTypes,
-            const APDCache &apdCache,
-            const ALCache &alCache)
-        : AbstractAIScoreCalculator(
-                  maxRounds,
-                  braveWaterCost,
-                  meteorRange,
-                  meteorCastVigorCost,
-                  minimumFleeOddsThreshold,
-                  desperateFleeThreshold,
-                  std::move(battalionTypes),
-                  apdCache,
-                  alCache) {}
-
-    [[nodiscard]] auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords) const -> ScoreValue override;
-
-    // Implement pure virtual methods from AbstractAIScoreCalculator
-    [[nodiscard]] auto InterpretDefenderOutcome(GameOutcome outcome) const -> ScoreValue override;
-    [[nodiscard]] auto InterpretAttackerOutcome(GameOutcome outcome) const -> ScoreValue override;
-
-    [[nodiscard]] auto AttackerFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineAttackerScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderScatterScores(const UnitsScoreComponents &components) const
-            -> ScoreValue override;
-
-    [[nodiscard]] auto CombineDefenderHoldCastlesScores(
-            const UnitsScoreComponents &components,
-            double victoryConditionScore,
-            int roundsRemaining) const -> ScoreValue override;
-
-private:
-    // Implementation methods (converted from internal namespace functions)
-    [[nodiscard]] auto AttackerUnitsScore(
-            const GameStateW &gameState,
-            int roundsRemaining,
-            bool attackerWantsCastles,
-            bool defenderShouldScatter,
-            const vector<TargetPriorityList> &attackerTargetPriorities,
-            const MapId &mapId) const -> ScoreValue;
-
-    [[nodiscard]] auto DefenderFleeStrategyScoreForState(const GameStateW &gameState) const
-            -> ScoreValue override;
-};
-
-// Implementation of StandardAIScoreCalculator methods
-
-auto StandardAIScoreCalculator::InterpretDefenderOutcome(GameOutcome outcome) const -> ScoreValue {
-    switch (outcome) {
-        case GameOutcome::DEFENDER_VICTORY: return INT_MAX;
-        case GameOutcome::ATTACKER_VICTORY: return INT_MIN;
-        case GameOutcome::DRAW: return 0;
-        case GameOutcome::FLEE_OUTCOME: return 0;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto StandardAIScoreCalculator::InterpretAttackerOutcome(GameOutcome outcome) const -> ScoreValue {
-    switch (outcome) {
-        case GameOutcome::ATTACKER_VICTORY: return INT_MAX;
-        case GameOutcome::DEFENDER_VICTORY: return INT_MIN;
-        case GameOutcome::DRAW: return 0;
-        case GameOutcome::FLEE_OUTCOME: return 0;
-    }
-    throw ShardokInternalErrorException("Unknown GameOutcome");
-}
-
-auto StandardAIScoreCalculator::AttackerUnitsScore(
-        const GameStateW &gameState,
-        int roundsRemaining,
-        bool attackerWantsCastles,
-        bool defenderShouldScatter,
-        const vector<TargetPriorityList> &attackerTargetPriorities,
-        const MapId &mapId) const -> ScoreValue {
-    // Use the base class implementation to get separated attacker/defender values
-    const auto components = CalculateUnitsScoreComponents(
-            gameState,
-            roundsRemaining,
-            attackerWantsCastles,
-            defenderShouldScatter,
-            attackerTargetPriorities,
-            mapId);
-
-    // Standard scorer returns the difference (attacker - defender)
-    return components.attackerUnitsValue - components.defenderUnitsValue;
-}
-
-auto StandardAIScoreCalculator::CombineDefenderScatterScores(
-        const UnitsScoreComponents &components) const -> ScoreValue {
-    // For defender scatter, we want to maximize defender units and minimize attacker units
-    // From defender's perspective: negate the attacker-defender difference
-    return components.defenderUnitsValue - components.attackerUnitsValue;
-}
-
-auto StandardAIScoreCalculator::CombineDefenderHoldCastlesScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int roundsRemaining) const -> ScoreValue {
-    // From defender's perspective: negate the attacker-defender difference
-    const double unitsDifference = components.defenderUnitsValue - components.attackerUnitsValue;
-    const double unitsMultiplier =
-            static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-    return UNITS_BASE_MULTIPLIER * unitsMultiplier * unitsDifference + victoryConditionScore;
-}
-
-auto StandardAIScoreCalculator::DefenderFleeStrategyScoreForState(const GameStateW &gameState) const
-        -> ScoreValue {
-    for (const auto *pi : *gameState->player_infos()) {
-        if (pi->is_defender()) { return FleeStrategyScoreForState(gameState, pi->player_id()); }
-    }
-    throw ShardokInternalErrorException("Unable to find defender for FleeStrategy");
-}
-
-auto StandardAIScoreCalculator::AttackerFleeStrategyScoreForState(const GameStateW &gameState) const
-        -> ScoreValue {
-    for (const PlayerInfo *pi : *gameState->player_infos()) {
-        if (!pi->is_defender()) { return FleeStrategyScoreForState(gameState, pi->player_id()); }
-    }
-    throw ShardokInternalErrorException("Unable to find attacker for FleeStrategy");
-}
-
-auto StandardAIScoreCalculator::CombineAttackerScores(
-        const UnitsScoreComponents &components,
-        const double victoryConditionScore,
-        const int roundsRemaining) const -> ScoreValue {
-    const double unitsDifference = components.attackerUnitsValue - components.defenderUnitsValue;
-    const double unitsMultiplier =
-            static_cast<double>(roundsRemaining) / static_cast<double>(GetMaxRounds());
-    return UNITS_BASE_MULTIPLIER * unitsMultiplier * unitsDifference + victoryConditionScore;
-}
-
-auto StandardAIScoreCalculator::GuessedStateScore(
-        const bool isDefender,
-        const GameStateW &state,
-        const AIStrategy &aiStrategy,
-        const CoordsSet &allCastleCoords) const -> ScoreValue {
-    const int roundsRemaining = GetMaxRounds() - state->current_round();
-
-    if (isDefender) {
-        return DefenderScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-    }
-    return AttackerScoreForState(state, aiStrategy, allCastleCoords, roundsRemaining);
-}
-
-// Factory function implementation
-auto MakeStandardAIScoreCalculator(
-        const SettingsGetter &settingsGetter,
-        const APDCache &apdCache,
-        const ALCache &alCache) -> std::unique_ptr<AIScoreCalculator> {
-    // Extract all battalion types into a vector indexed by BattalionTypeId
-    std::vector<BattalionTypeSPtr> battalionTypes(BattalionTypeId::BattalionTypeId_MAX + 1);
-    for (int typeId = BattalionTypeId::BattalionTypeId_MIN;
-         typeId <= BattalionTypeId::BattalionTypeId_MAX;
-         typeId++) {
-        auto battalionTypeId = static_cast<BattalionTypeId>(typeId);
-        battalionTypes[battalionTypeId] = settingsGetter.GetBattalionType(battalionTypeId);
-    }
-
-    return std::make_unique<StandardAIScoreCalculator>(
-            settingsGetter.Backing().max_rounds(),
-            settingsGetter.Backing().brave_water_action_point_cost(),
-            settingsGetter.Backing().meteor_range(),
-            settingsGetter.Backing().meteor_cast_vigor_cost(),
-            settingsGetter.Backing().ai_minimum_flee_odds_threshold(),
-            settingsGetter.Backing().ai_desperate_flee_threshold(),
-            std::move(battalionTypes),
-            apdCache,
-            alCache);
-}
-
-}  // namespace shardok
@@ -1,31 +0,0 @@
-//
-// Standard implementation of AIScoreCalculator
-//
-
-#ifndef EAGLE0_STANDARDAISCORECALCULATOR_HPP
-#define EAGLE0_STANDARDAISCORECALCULATOR_HPP
-
-#include <memory>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-
-using APDCache = std::shared_ptr<ActionPointDistancesCache>;
-using ALCache = std::unique_ptr<AttackLocationsCache>;
-
-/// Factory function to create a StandardAIScoreCalculator.
-/// Returns a unique_ptr to AIScoreCalculator to hide the implementation.
-[[nodiscard]] auto MakeStandardAIScoreCalculator(
-        const SettingsGetter& settingsGetter,
-        const APDCache& apdCache,
-        const ALCache& alCache) -> std::unique_ptr<AIScoreCalculator>;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_STANDARDAISCORECALCULATOR_HPP
@@ -1,129 +0,0 @@
-//
-// Shared utilities for AI score calculators - implementation
-//
-
-#include "AIScoreCalculatorSharedUtilities.hpp"
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-
-namespace shardok {
-namespace score_calculator_internal {
-
-auto EffectiveDistanceCache::GetOrCompute(
-        const Unit* unit,
-        const Coords& target,
-        const ActionPointDistances* notBravingApd,
-        const ActionPointDistances* bravingApd,
-        const HexMap* hexMap) const -> DIST_T {
-    CacheKey key{unit->unit_id(), target};
-    auto it = cache.find(key);
-    if (it != cache.end()) { return it->second; }
-
-    CoordsSet targetSet(hexMap);
-    targetSet.Add(target);
-
-    DIST_T result = EffectiveDistance(unit, notBravingApd, bravingApd, targetSet);
-    cache[key] = result;
-    return result;
-}
-
-auto FleeStrategyScoreForState(const GameStateW& gameState, const PlayerId playerId) -> ScoreValue {
-    ScoreValue scoreValue = 0.0;
-
-    const auto* gameStatePtr = gameState.Get();
-    const auto* units = gameStatePtr->units();
-
-    for (const auto* unit : *units) {
-        if (unit->status() != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;
-
-        if (unit->player_id() == playerId &&
-            unit->battalion().type() != net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD) {
-            scoreValue += FLEE_UNIT_SCORE;
-
-            if (unit->has_attached_hero() &&
-                unit->attached_hero().control_info().controlled_unit_id() != -1) {
-                scoreValue += FLEE_CONTROLLING_UNIT_SCORE;
-            }
-        }
-    }
-
-    return scoreValue;
-}
-
-// Forward declaration for recursive helper
-static auto RecursiveAttackerMultiplierForTargetDistance(
-        const Unit* attackingUnit,
-        std::vector<TargetAndAttackLocations>::const_iterator& priorityListNext,
-        const std::vector<TargetAndAttackLocations>::const_iterator& priorityListEnd,
-        const std::vector<const Unit*>& occupants,
-        const HexMap* map,
-        const BattalionTypeSPtr& battType,
-        const ActionPointDistances* notBravingApd,
-        const ActionPointDistances* bravingApd,
-        bool isLateGame) -> double;
-
-static auto RecursiveAttackerMultiplierForTargetDistance(
-        const Unit* attackingUnit,
-        std::vector<TargetAndAttackLocations>::const_iterator& priorityListNext,
-        const std::vector<TargetAndAttackLocations>::const_iterator& priorityListEnd,
-        const std::vector<const Unit*>& occupants,
-        const HexMap* map,
-        const BattalionTypeSPtr& battType,
-        const ActionPointDistances* notBravingApd,
-        const ActionPointDistances* bravingApd,
-        const bool isLateGame) -> double {
-    if (priorityListNext == priorityListEnd) return 1.0;
-
-    const auto& [target, attackLocations] = *priorityListNext;
-    const Coords& topPriorityTarget = target;
-
-    // If the target is unoccupied or is occupied by this player, give the maximum multiplier, but
-    // also add the bonus for the next up in the priority list
-    if (const Unit* occupant = occupants
-                [topPriorityTarget.row() * map->column_count() + topPriorityTarget.column()];
-        !occupant || occupant->player_id() == attackingUnit->player_id()) {
-        return kMaxProximityBuf + RecursiveAttackerMultiplierForTargetDistance(
-                                          attackingUnit,
-                                          ++priorityListNext,
-                                          priorityListEnd,
-                                          occupants,
-                                          map,
-                                          battType,
-                                          notBravingApd,
-                                          bravingApd,
-                                          isLateGame);
-    }
-
-    // Use optimized EffectiveDistance with pre-computed ActionPointDistances
-    // attackLocations is already the CoordsSet of attack locations for this target
-    const DIST_T distance =
-            EffectiveDistance(attackingUnit, notBravingApd, bravingApd, attackLocations);
-
-    return kMaxProximityBuf / (1 + distance / kDistanceDebufRatio);
-}
-
-auto AttackerMultiplierForTargetDistance(
-        const Unit* attackingUnit,
-        const std::vector<TargetAndAttackLocations>& priorityList,
-        const std::vector<const Unit*>& occupants,
-        const HexMap* map,
-        const BattalionTypeSPtr& battType,
-        const ActionPointDistances* notBravingApd,
-        const ActionPointDistances* bravingApd,
-        const bool isLateGame) -> double {
-    auto iter = std::begin(priorityList);
-    return RecursiveAttackerMultiplierForTargetDistance(
-            attackingUnit,
-            iter,
-            std::end(priorityList),
-            occupants,
-            map,
-            battType,
-            notBravingApd,
-            bravingApd,
-            isLateGame);
-}
-
-}  // namespace score_calculator_internal
-}  // namespace shardok
@@ -1,95 +0,0 @@
-//
-// Shared utilities for AI score calculators
-// This file is private to the ai/score package
-//
-
-#ifndef EAGLE0_AI_SCORE_CALCULATOR_SHARED_UTILITIES_HPP
-#define EAGLE0_AI_SCORE_CALCULATOR_SHARED_UTILITIES_HPP
-
-#include <vector>
-
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wthread-safety-analysis"
-#pragma GCC diagnostic ignored "-Wunused-result"
-#include <gtl/phmap.hpp>
-#pragma GCC diagnostic pop
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
-#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state_generated.h"
-#include "src/main/flatbuffer/net/eagle0/shardok/storage/hex_map_generated.h"
-#include "src/main/flatbuffer/net/eagle0/shardok/storage/unit_generated.h"
-
-namespace shardok {
-namespace score_calculator_internal {
-
-using HexMap = net::eagle0::shardok::storage::fb::HexMap;
-using Unit = net::eagle0::shardok::storage::fb::Unit;
-
-// Scoring constants shared across all calculators
-constexpr double UNITS_BASE_MULTIPLIER = 0.05;
-constexpr double FLEE_UNIT_SCORE = -10000;
-constexpr double FLEE_CONTROLLING_UNIT_SCORE = -10000;
-constexpr double CAPTURED_UNIT_SCORE = -10000;
-constexpr double CAPTURED_VIP_SCORE = -25000;
-constexpr double kMaxProximityBuf = 1.5;
-constexpr double kDistanceDebufRatio = 8.0;
-
-/// Structure to hold separated attacker/defender unit scores
-/// Used by NormalizedAIScoreCalculator to apply asymmetric normalization
-struct UnitsScoreComponents {
-    double attackerUnitsValue;
-    double defenderUnitsValue;
-};
-
-/// Memoization cache for EffectiveDistance calls
-struct EffectiveDistanceCache {
-    struct CacheKey {
-        UnitId unitId;
-        Coords target;
-        bool operator==(const CacheKey& other) const {
-            return unitId == other.unitId && target == other.target;
-        }
-    };
-
-    struct CacheKeyHash {
-        size_t operator()(const CacheKey& key) const {
-            return std::hash<UnitId>{}(key.unitId) ^ (std::hash<int>{}(key.target.row()) << 1) ^
-                   (std::hash<int>{}(key.target.column()) << 2);
-        }
-    };
-
-    mutable gtl::flat_hash_map<CacheKey, DIST_T, CacheKeyHash> cache;
-
-    DIST_T GetOrCompute(
-            const Unit* unit,
-            const Coords& target,
-            const ActionPointDistances* notBravingApd,
-            const ActionPointDistances* bravingApd,
-            const HexMap* hexMap) const;
-};
-
-/// Calculate score for FLEE strategy
-/// Returns negative score based on fleeing units
-auto FleeStrategyScoreForState(const GameStateW& gameState, PlayerId playerId) -> ScoreValue;
-
-/// Calculate attacker multiplier based on distance to priority targets
-/// This is used to weight attacker units by their proximity to objectives
-auto AttackerMultiplierForTargetDistance(
-        const Unit* attackingUnit,
-        const std::vector<TargetAndAttackLocations>& priorityList,
-        const std::vector<const Unit*>& occupants,
-        const HexMap* map,
-        const BattalionTypeSPtr& battType,
-        const ActionPointDistances* notBravingApd,
-        const ActionPointDistances* bravingApd,
-        bool isLateGame) -> double;
-
-}  // namespace score_calculator_internal
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_SCORE_CALCULATOR_SHARED_UTILITIES_HPP
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
admin	72ba7949f6	it's too much	2025-07-31 22:24:41 -07:00
admin	8d37c07f24	two still failing	2025-07-31 22:12:25 -07:00
admin	44b3467306	a little cleanup	2025-07-31 21:35:01 -07:00
admin	5d66603e1b	another test	2025-07-31 21:29:24 -07:00
admin	96798a6ad5	another test	2025-07-31 21:29:24 -07:00
admin	9273fb0134	one more passing	2025-07-31 21:29:23 -07:00
admin	a874e973e2	progress	2025-07-31 21:29:23 -07:00
admin	46a88d17c1	more tests	2025-07-31 21:29:23 -07:00
admin	c391ce0a4b	handle province stats in client and fix some tests	2025-07-31 21:29:23 -07:00