more cleanup

.bazelrc

@@ -19,9 +19,9 @@ 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"
 
@@ -29,9 +29,6 @@ common --javacopt="-Xlint:-options"
 common --linkopt=-Wl
 common:macos --linkopt=-Wl,-no_warn_duplicate_libraries
 
-# Fix Xcode version caching issue - avoids need for `bazel clean --expunge` after Xcode updates
-common:macos --repo_env=DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
-
 common --java_language_version=17
 common --java_runtime_version=remotejdk_17
 common --tool_java_language_version=17

.clangd

@@ -1,3 +0,0 @@
-CompileFlags:
-  Add:
-    - "-std=c++23"

.gitattributes

@@ -6,7 +6,4 @@
 *.bytes filter=lfs diff=lfs merge=lfs -text
 *.psd filter=lfs diff=lfs merge=lfs -text
 *.ttf filter=lfs diff=lfs merge=lfs -text
-# Exclude pre-existing font files that were committed as blobs (not LFS pointers)
-src/main/csharp/**/GUI[[:space:]]Pro[[:space:]]Kit*/**/*.ttf !filter !diff !merge
-src/main/csharp/**/Modern[[:space:]]UI[[:space:]]Pack/**/*.ttf !filter !diff !merge
 *.herodata filter=lfs diff=lfs merge=lfs -text

.github/workflows/bazel_test.yml

@@ -34,54 +34,10 @@ jobs:
       with:
         lfs: false
     - name: Run tests
-      id: test
-      continue-on-error: true
       run: bazel test --build_event_json_file=test.json //src/test/... //src/main/go/...
-    - name: Collect failed test logs
-      if: always()
-      run: |
-        # Remove any existing failed_test_logs directory and create fresh
-        rm -rf failed_test_logs
-        mkdir -p failed_test_logs
-        # Extract failed test targets from test.json and copy their logs
-        # The test.json is in JSONL format - one JSON object per line
-        # We look for lines with testResult that have a status other than PASSED
-        if [ -f test.json ]; then
-          grep '"testResult"' test.json | \
-            grep '"status"' | \
-            grep -v '"status":"PASSED"' | \
-            grep -o '"label":"[^"]*"' | \
-            cut -d'"' -f4 | \
-            sort -u | \
-            while read target; do
-              # Convert target like //src/test/cpp/...:test_name to path
-              log_path=$(echo "$target" | sed 's|^//||' | sed 's|:|/|')
-              if [ -f "bazel-testlogs/$log_path/test.log" ]; then
-                log_name=$(echo "$log_path" | tr '/' '_')
-                if cp "bazel-testlogs/$log_path/test.log" "failed_test_logs/${log_name}.log"; then
-                  echo "Collected log for failed test: $target"
-                else
-                  echo "Error: Failed to copy log for $target"
-                fi
-              fi
-            done
-        fi
-        # List what we collected
-        echo "Collected logs:"
-        ls -lh failed_test_logs/ 2>/dev/null || echo "No logs collected"
     - name: Archive test results
-      if: always()
+      if: success() || failure()
       uses: actions/upload-artifact@v4
       with:
         name: test.json
         path: test.json
-    - name: Archive failed test logs
-      if: always()
-      uses: actions/upload-artifact@v4
-      with:
-        name: failed-test-logs
-        path: failed_test_logs/
-        if-no-files-found: ignore
-    - name: Fail if tests failed
-      if: steps.test.outcome == 'failure'
-      run: exit 1

.github/workflows/build_sysroot.yml

@@ -1,64 +0,0 @@
-name: Build Linux Sysroot
-
-on:
-  workflow_dispatch:
-    inputs:
-      version:
-        description: 'Sysroot version (e.g., v2, v3)'
-        required: true
-        default: 'v2'
-        type: string
-
-permissions:
-  contents: read
-
-jobs:
-  build-sysroot:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-
-      - name: Build sysroot
-        run: ./tools/sysroot/build_sysroot.sh
-
-      - name: Upload sysroot artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: ubuntu-noble-sysroot
-          path: tools/sysroot/output/
-
-      - name: Install AWS CLI
-        run: |
-          curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
-          unzip -q awscliv2.zip
-          sudo ./aws/install
-
-      - name: Upload to DigitalOcean Spaces
-        env:
-          AWS_ACCESS_KEY_ID: ${{ secrets.ACCESS_KEY_ID }}
-          AWS_SECRET_ACCESS_KEY: ${{ secrets.SECRET_KEY }}
-        run: |
-          # Upload sysroot tarball to DO Spaces
-          aws s3 cp tools/sysroot/output/ubuntu_noble_amd64_sysroot.tar.xz \
-            s3://eagle0/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz \
-            --endpoint-url https://sfo3.digitaloceanspaces.com \
-            --acl public-read
-
-          # Upload sha256 file
-          aws s3 cp tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256 \
-            s3://eagle0/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.sha256 \
-            --endpoint-url https://sfo3.digitaloceanspaces.com \
-            --acl public-read
-
-          echo ""
-          echo "=== Sysroot uploaded ==="
-          echo "URL: https://eagle0.sfo3.digitaloceanspaces.com/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz"
-          echo "SHA256: $(cat tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256)"
-          echo ""
-          echo "Update MODULE.bazel with:"
-          echo "sysroot("
-          echo "    name = \"linux_sysroot\","
-          echo "    sha256 = \"$(cat tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256)\","
-          echo "    urls = [\"https://eagle0.sfo3.digitaloceanspaces.com/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz\"],"
-          echo ")"

.github/workflows/docker_build.yml

@@ -1,72 +0,0 @@
-name: Docker Build and Push
-
-on:
-  push:
-    branches: [ "main" ]
-    paths:
-      - 'src/main/cpp/**'
-      - 'src/main/scala/**'
-      - 'src/main/protobuf/**'
-      - 'src/main/resources/**'
-      - 'ci/BUILD.bazel'
-      - 'MODULE.bazel'
-      - '.github/workflows/docker_build.yml'
-  workflow_dispatch:
-    inputs:
-      push_images:
-        description: 'Push images to container registry'
-        required: true
-        default: 'false'
-        type: boolean
-
-permissions:
-  contents: read
-
-jobs:
-  build-eagle:
-    runs-on: self-hosted
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          lfs: false
-
-      - name: Build Eagle Docker image
-        run: bazel build //ci:eagle_server_image
-
-      - name: Login to DigitalOcean Container Registry
-        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
-        env:
-          DO_TOKEN: ${{ secrets.DO_REGISTRY_TOKEN }}
-        run: |
-          mkdir -p ~/.docker
-          AUTH=$(echo -n "${DO_TOKEN}:${DO_TOKEN}" | base64)
-          echo "{\"auths\":{\"registry.digitalocean.com\":{\"auth\":\"${AUTH}\"}}}" > ~/.docker/config.json
-
-      - name: Push Eagle image to DO registry
-        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
-        run: bazel run //ci:eagle_server_push
-
-  build-shardok:
-    runs-on: self-hosted
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          lfs: false
-
-      - name: Build Shardok Docker image (cross-compile for Linux)
-        run: bazel build --platforms=//:linux_x86_64 //ci:shardok_server_image
-
-      - name: Login to DigitalOcean Container Registry
-        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
-        env:
-          DO_TOKEN: ${{ secrets.DO_REGISTRY_TOKEN }}
-        run: |
-          mkdir -p ~/.docker
-          AUTH=$(echo -n "${DO_TOKEN}:${DO_TOKEN}" | base64)
-          echo "{\"auths\":{\"registry.digitalocean.com\":{\"auth\":\"${AUTH}\"}}}" > ~/.docker/config.json
-
-      - name: Push Shardok image to DO registry
-        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
-        run: bazel run --platforms=//:linux_x86_64 //ci:shardok_server_push

.gitignore

@@ -20,7 +20,7 @@ project/boot/
 project/plugins/project/
 project/target/
 bazel-bin
-bazel-eagle0*
+bazel-eagle0
 bazel-out
 bazel-testlogs
 .ijwb
@@ -32,9 +32,9 @@ buildWin.sh
 __pycache__/
 scripts/refresh_name_layers/vendor/
 scripts/refresh_name_layers/refresh_name_layers.zip
+.pre-commit-config.yaml
 .bazelbsp
 .bsp
 .metals
 api_keys.txt
 
-src/main/csharp/net/eagle0/clients/unity/eagle0/ProjectSettings/Packages/com.unity.dedicated-server/

.pre-commit-config.yaml

@@ -1,44 +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: ./scripts/pre-commit-gazelle.sh
-        files: '(\.go|\.proto|BUILD\.bazel|BUILD|WORKSPACE|WORKSPACE\.bazel|\.bzl)$'
-        pass_filenames: false
--   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'

.scalafmt.conf

@@ -1,47 +1,6 @@
 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

BUILD.bazel

@@ -3,15 +3,6 @@ load("@io_bazel_rules_go//go:def.bzl", "nogo")
 
 package(default_visibility = ["//visibility:public"])
 
-# Platform for cross-compiling to Linux x86_64
-platform(
-    name = "linux_x86_64",
-    constraint_values = [
-        "@platforms//os:linux",
-        "@platforms//cpu:x86_64",
-    ],
-)
-
 gazelle(name = "gazelle")
 
 # gazelle:proto file

CLAUDE.md

@@ -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/...
@@ -79,24 +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
 ```
 
-### Pre-Commit Checklist
-
-**MANDATORY: Before running `git commit`, verify:**
-
-1. **If you modified any BUILD.bazel file:** Run `bazel run gazelle` and stage any changes it makes
-2. **If you modified C++ or C# files:** Run `clang-format -i` on the modified files
-3. **If you modified Scala files:** scalafmt will run automatically via pre-commit hook
-
-The pre-commit hook runs gazelle but only checks if it succeeds - it does NOT verify the BUILD files are in canonical format. The `gazelle_test` will fail if deps are not alphabetically sorted. **Always run gazelle manually after BUILD file changes.**
-
 ### Code Formatting
-
 ```bash
 # ALWAYS run clang-format after making any C++ or C# code changes
 clang-format -i <modified_files>
@@ -109,94 +85,35 @@ 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
+bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' <file_path> -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++20
 
 # 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
+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++20
 ```
 
-## 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)
@@ -205,7 +122,6 @@ 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
 
@@ -216,31 +132,6 @@ to be used for different players or game situations within the same server proce
 - Map validation tests ensure game content integrity
 - Use `GameSettings_test_utils.cpp` and `ShardokEngineBasedTestData.cpp` for C++ test helpers
 
-### Scala Testing Patterns
-
-**Use `inside()` instead of `asInstanceOf` for type matching in tests:**
-
-Never use `asInstanceOf` in tests. Instead, use ScalaTest's `inside()` pattern for safe type matching:
-
-```scala
-// BAD - don't do this
-val changedHero = result.changedHeroes.head.asInstanceOf[ChangedHeroC]
-changedHero.heroId shouldBe 19
-
-// GOOD - use inside() pattern
-import org.scalatest.Inside.inside
-
-inside(result.changedHeroes.head) { case changedHero: ChangedHeroC =>
-  changedHero.heroId shouldBe 19
-  changedHero.vigorChange shouldBe StatDelta(17.2)
-}
-```
-
-The `inside()` pattern:
-- Provides better error messages when the type doesn't match
-- Is idiomatic ScalaTest
-- Works with pattern matching for more complex assertions
-
 ## Performance Testing
 
 When making performance-related changes to the AI or engine:
@@ -272,38 +163,10 @@ 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.
-
-## Troubleshooting Scala Build Errors
-
-### MissingType Errors
-
-When you see errors like:
-```
-dotty.tools.dotc.core.MissingType: Cannot resolve reference to type net.eagle0.eagle.internal.game_state.type.GameState
-```
-
-**This is NOT a Scala compiler crash.** This is a missing dependency in BUILD.bazel.
-
-**How to fix:**
-1. Identify the missing type from the error message (e.g., `game_state.GameState`)
-2. Find the Bazel target that provides this type (e.g., `//src/main/protobuf/net/eagle0/eagle/internal:game_state_scala_proto`)
-3. Add it to the `deps` of the failing target
-4. If the type appears in a public method signature, also add it to `exports` so downstream targets can see it
-
-**Common pattern:** When adding a method to a class that takes or returns a proto type, the proto dependency often needs to be added to both `deps` AND `exports`.
-
-### Bazel Clean
-
-**NEVER run `bazel clean` without asking first.** It rarely fixes actual issues and wastes significant rebuild time. The issues that seem like they need `bazel clean` are usually:
-- Missing imports in Scala code
-- Missing dependencies in BUILD.bazel
-- Missing exports for types used in public signatures
+- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or behavior changes.
 
 ## Game Content
 

MODULE.bazel

@@ -26,76 +26,56 @@ 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 = "1.6.0")
+bazel_dep(name = "toolchains_llvm", version = "1.4.0")
 
 llvm = use_extension("@toolchains_llvm//toolchain/extensions:llvm.bzl", "llvm")
 
-# Native toolchain (macOS -> macOS, Linux -> Linux)
 llvm.toolchain(
     name = "llvm_toolchain",
     llvm_version = "20.1.2",
 )
 
-# Cross-compilation toolchain (macOS -> Linux x86_64)
-# Uses the same LLVM distribution but with a Linux sysroot
-llvm.toolchain(
-    name = "llvm_toolchain_linux",
-    llvm_version = "20.1.2",
-)
-
-# Linux sysroot for cross-compilation (Chromium's Debian sysroot)
-llvm.sysroot(
-    name = "llvm_toolchain_linux",
-    label = "@linux_sysroot//sysroot",
-    targets = ["linux-x86_64"],
-)
-
-use_repo(llvm, "llvm_toolchain", "llvm_toolchain_linux")
-
-# Download the Linux sysroot (Ubuntu 24.04 Noble for C++23 support)
-# Built by: .github/workflows/build_sysroot.yml
-# To rebuild: Run the "Build Linux Sysroot" workflow with a new version, then update sha256 and URL
-sysroot = use_repo_rule("@toolchains_llvm//toolchain:sysroot.bzl", "sysroot")
-sysroot(
-    name = "linux_sysroot",
-    # TODO: Update sha256 after running sysroot build workflow with version v2
-    sha256 = "PLACEHOLDER_RUN_SYSROOT_WORKFLOW_FIRST",
-    urls = ["https://eagle0.sfo3.digitaloceanspaces.com/sysroot/v2/ubuntu_noble_amd64_sysroot.tar.xz"],
-)
+use_repo(llvm, "llvm_toolchain")
 
 #
 # Language Support - Go
 #
 
-bazel_dep(name = "rules_go", version = "0.56.1", repo_name = "io_bazel_rules_go")
-bazel_dep(name = "gazelle", version = "0.45.0", repo_name = "bazel_gazelle")
+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")
 
 go_sdk = use_extension("@io_bazel_rules_go//go:extensions.bzl", "go_sdk")
+
 go_sdk.download(version = "1.23.3")
 
 go_deps = use_extension("@bazel_gazelle//:extensions.bzl", "go_deps")
+
 go_deps.from_file(go_mod = "//:go.mod")
+
 use_repo(
     go_deps,
     "com_github_aws_aws_sdk_go_v2",
     "com_github_aws_aws_sdk_go_v2_config",
     "com_github_aws_aws_sdk_go_v2_credentials",
     "com_github_aws_aws_sdk_go_v2_service_s3",
-    "org_golang_google_grpc",
     "org_golang_google_protobuf",
 )
 
@@ -103,15 +83,15 @@ use_repo(
 # Platform Support - Apple/iOS
 #
 
-bazel_dep(name = "apple_support", version = "1.21.1", repo_name = "build_bazel_apple_support")
-bazel_dep(name = "rules_apple", version = "3.16.1", repo_name = "build_bazel_rules_apple")
-bazel_dep(name = "rules_swift", version = "2.3.1", repo_name = "build_bazel_rules_swift")
+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")
 
 #
 # Protocol Buffers & RPC
 #
 
-bazel_dep(name = "protobuf", version = "29.2", repo_name = "com_google_protobuf")
+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")
@@ -122,32 +102,6 @@ bazel_dep(name = "flatbuffers", version = "25.2.10")
 
 bazel_dep(name = "googletest", version = "1.17.0")
 
-#
-# Container Images (OCI)
-#
-
-bazel_dep(name = "rules_oci", version = "2.2.6")
-bazel_dep(name = "aspect_bazel_lib", version = "2.16.0")
-
-oci = use_extension("@rules_oci//oci:extensions.bzl", "oci")
-
-# Base image for Eagle (Java 17)
-oci.pull(
-    name = "eclipse_temurin_17",
-    digest = "sha256:d286b5352d98777bbf727f54038b04f0145cd9b76ca83f38a67aa111d4303748",
-    image = "docker.io/library/eclipse-temurin",
-    platforms = ["linux/amd64"],
-)
-
-# Base image for Shardok (Ubuntu 24.04 for C++ runtime)
-oci.pull(
-    name = "ubuntu_24_04",
-    image = "docker.io/library/ubuntu",
-    platforms = ["linux/amd64"],
-    tag = "24.04",
-)
-use_repo(oci, "eclipse_temurin_17", "eclipse_temurin_17_linux_amd64", "ubuntu_24_04", "ubuntu_24_04_linux_amd64")
-
 #
 # Java/Scala Dependencies
 #
@@ -155,6 +109,7 @@ use_repo(oci, "eclipse_temurin_17", "eclipse_temurin_17_linux_amd64", "ubuntu_24
 bazel_dep(name = "rules_jvm_external", version = "6.3")
 
 maven = use_extension("@rules_jvm_external//:extensions.bzl", "maven")
+
 maven.install(
     artifacts = [
         # Netty
@@ -205,10 +160,6 @@ maven.install(
         # Other
         "org.reactivestreams:reactive-streams:1.0.4",
         "javax.xml.bind:jaxb-api:2.3.1",
-
-        # OkHttp (for SSE with read timeout support)
-        "com.squareup.okhttp3:okhttp:4.12.0",
-        "com.squareup.okhttp3:okhttp-sse:4.12.0",
     ],
     duplicate_version_warning = "error",
     fail_if_repin_required = True,
@@ -217,6 +168,7 @@ maven.install(
         "https://repo1.maven.org/maven2",
     ],
 )
+
 use_repo(maven, "maven", "unpinned_maven")
 
 #
@@ -264,6 +216,5 @@ register_toolchains(
 # Set dev_dependency so we can turn this off for swift MacOS builds
 register_toolchains(
     "@llvm_toolchain//:all",
-    "@llvm_toolchain_linux//:all",
     dev_dependency = True,
 )

MODULE.bazel.lock

@@ -26,11 +26,7 @@
     "https://bcr.bazel.build/modules/aspect_bazel_lib/1.38.0/MODULE.bazel": "6307fec451ba9962c1c969eb516ebfe1e46528f7fa92e1c9ac8646bef4cdaa3f",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/1.40.3/MODULE.bazel": "668e6bcb4d957fc0e284316dba546b705c8d43c857f87119619ee83c4555b859",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.11.0/MODULE.bazel": "cb1ba9f9999ed0bc08600c221f532c1ddd8d217686b32ba7d45b0713b5131452",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.14.0/MODULE.bazel": "2b31ffcc9bdc8295b2167e07a757dbbc9ac8906e7028e5170a3708cecaac119f",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.16.0/MODULE.bazel": "852f9ebbda017572a7c113a2434592dd3b2f55cd9a0faea3d4be5a09a59e4900",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.19.3/MODULE.bazel": "253d739ba126f62a5767d832765b12b59e9f8d2bc88cc1572f4a73e46eb298ca",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.19.3/source.json": "ffab9254c65ba945f8369297ad97ca0dec213d3adc6e07877e23a48624a8b456",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.7.2/MODULE.bazel": "780d1a6522b28f5edb7ea09630748720721dfe27690d65a2d33aa7509de77e07",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.11.0/source.json": "92494d5aa43b96665397dd13ee16023097470fa85e276b93674d62a244de47ee",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.7.7/MODULE.bazel": "491f8681205e31bb57892d67442ce448cda4f472a8e6b3dc062865e29a64f89c",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.8.1/MODULE.bazel": "812d2dd42f65dca362152101fbec418029cc8fd34cbad1a2fde905383d705838",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.9.3/MODULE.bazel": "66baf724dbae7aff4787bf2245cc188d50cb08e07789769730151c0943587c14",
@@ -55,11 +51,8 @@
     "https://bcr.bazel.build/modules/bazel_features/1.19.0/MODULE.bazel": "59adcdf28230d220f0067b1f435b8537dd033bfff8db21335ef9217919c7fb58",
     "https://bcr.bazel.build/modules/bazel_features/1.21.0/MODULE.bazel": "675642261665d8eea09989aa3b8afb5c37627f1be178382c320d1b46afba5e3b",
     "https://bcr.bazel.build/modules/bazel_features/1.27.0/MODULE.bazel": "621eeee06c4458a9121d1f104efb80f39d34deff4984e778359c60eaf1a8cb65",
-    "https://bcr.bazel.build/modules/bazel_features/1.28.0/MODULE.bazel": "4b4200e6cbf8fa335b2c3f43e1d6ef3e240319c33d43d60cc0fbd4b87ece299d",
+    "https://bcr.bazel.build/modules/bazel_features/1.27.0/source.json": "ed8cf0ef05c858dce3661689d0a2b110ff398e63994e178e4f1f7555a8067fed",
     "https://bcr.bazel.build/modules/bazel_features/1.3.0/MODULE.bazel": "cdcafe83ec318cda34e02948e81d790aab8df7a929cec6f6969f13a489ccecd9",
-    "https://bcr.bazel.build/modules/bazel_features/1.34.0/MODULE.bazel": "e8475ad7c8965542e0c7aac8af68eb48c4af904be3d614b6aa6274c092c2ea1e",
-    "https://bcr.bazel.build/modules/bazel_features/1.38.0/MODULE.bazel": "f9b8a9c890ebd216b4049fd12a31d3c2602e3403c7af636b04fbbd7453edc9c9",
-    "https://bcr.bazel.build/modules/bazel_features/1.38.0/source.json": "31ba776c122b54a2885e23651642e32f087a87bf025465f8040751894b571277",
     "https://bcr.bazel.build/modules/bazel_features/1.4.1/MODULE.bazel": "e45b6bb2350aff3e442ae1111c555e27eac1d915e77775f6fdc4b351b758b5d7",
     "https://bcr.bazel.build/modules/bazel_features/1.9.0/MODULE.bazel": "885151d58d90d8d9c811eb75e3288c11f850e1d6b481a8c9f766adee4712358b",
     "https://bcr.bazel.build/modules/bazel_features/1.9.1/MODULE.bazel": "8f679097876a9b609ad1f60249c49d68bfab783dd9be012faf9d82547b14815a",
@@ -76,8 +69,7 @@
     "https://bcr.bazel.build/modules/bazel_skylib/1.7.0/MODULE.bazel": "0db596f4563de7938de764cc8deeabec291f55e8ec15299718b93c4423e9796d",
     "https://bcr.bazel.build/modules/bazel_skylib/1.7.1/MODULE.bazel": "3120d80c5861aa616222ec015332e5f8d3171e062e3e804a2a0253e1be26e59b",
     "https://bcr.bazel.build/modules/bazel_skylib/1.8.1/MODULE.bazel": "88ade7293becda963e0e3ea33e7d54d3425127e0a326e0d17da085a5f1f03ff6",
-    "https://bcr.bazel.build/modules/bazel_skylib/1.8.2/MODULE.bazel": "69ad6927098316848b34a9142bcc975e018ba27f08c4ff403f50c1b6e646ca67",
-    "https://bcr.bazel.build/modules/bazel_skylib/1.8.2/source.json": "34a3c8bcf233b835eb74be9d628899bb32999d3e0eadef1947a0a562a2b16ffb",
+    "https://bcr.bazel.build/modules/bazel_skylib/1.8.1/source.json": "7ebaefba0b03efe59cac88ed5bbc67bcf59a3eff33af937345ede2a38b2d368a",
     "https://bcr.bazel.build/modules/bazel_worker_api/0.0.6/MODULE.bazel": "fd1f9432ca04c947e91b500df69ce7c5b6dbfe1bc45ab1820338205dae3383a6",
     "https://bcr.bazel.build/modules/bazel_worker_api/0.0.6/source.json": "5d68545f224904745a3cabd35aea6bc2b6cc5a78b7f49f3f69660eab2eeeb273",
     "https://bcr.bazel.build/modules/boringssl/0.0.0-20211025-d4f1ab9/MODULE.bazel": "6ee6353f8b1a701fe2178e1d925034294971350b6d3ac37e67e5a7d463267834",
@@ -106,8 +98,6 @@
     "https://bcr.bazel.build/modules/envoy_api/0.0.0-20250128-4de3c74/source.json": "028519164a2e24563f4b43d810fdedc702daed90e71e7042d45ba82ad807b46f",
     "https://bcr.bazel.build/modules/flatbuffers/25.2.10/MODULE.bazel": "dab15cafe8512d2c4a8daa44c2d7968c5c79f01e220d40076cdc260bf58605e2",
     "https://bcr.bazel.build/modules/flatbuffers/25.2.10/source.json": "7eae7ea3eb913b9802426e4d5df11d6c6072a3573a548f8cabf1e965f5cca4d0",
-    "https://bcr.bazel.build/modules/gawk/5.3.2.bcr.1/MODULE.bazel": "cdf8cbe5ee750db04b78878c9633cc76e80dcf4416cbe982ac3a9222f80713c8",
-    "https://bcr.bazel.build/modules/gawk/5.3.2.bcr.1/source.json": "fa7b512dfcb5eafd90ce3959cf42a2a6fe96144ebbb4b3b3928054895f2afac2",
     "https://bcr.bazel.build/modules/gazelle/0.27.0/MODULE.bazel": "3446abd608295de6d90b4a8a118ed64a9ce11dcb3dda2dc3290a22056bd20996",
     "https://bcr.bazel.build/modules/gazelle/0.30.0/MODULE.bazel": "f888a1effe338491f35f0e0e85003b47bb9d8295ccba73c37e07702d8d31c65b",
     "https://bcr.bazel.build/modules/gazelle/0.32.0/MODULE.bazel": "b499f58a5d0d3537f3cf5b76d8ada18242f64ec474d8391247438bf04f58c7b8",
@@ -147,10 +137,6 @@
     "https://bcr.bazel.build/modules/grpc/1.70.1/MODULE.bazel": "b800cd8e3e7555c1e61cba2e02d3a2fcf0e91f66e800db286d965d3b7a6a721a",
     "https://bcr.bazel.build/modules/grpc/1.71.0/MODULE.bazel": "7fcab2c05530373f1a442c362b17740dd0c75b6a2a975eec8f5bf4c70a37928a",
     "https://bcr.bazel.build/modules/grpc/1.71.0/source.json": "60ef8c4c72c8280ae94c05b4f38bf67785acb25477ab8dbac096a9604449ff90",
-    "https://bcr.bazel.build/modules/helly25_bzl/0.3.1/MODULE.bazel": "3a4be20f6fc13be32ad44643b8252ef5af09eee936f1d943cd4fd7867fa92826",
-    "https://bcr.bazel.build/modules/helly25_bzl/0.3.1/source.json": "b129ab1828492de2c163785bbeb4065c166de52d932524b4317beb5b7f917994",
-    "https://bcr.bazel.build/modules/jq.bzl/0.1.0/MODULE.bazel": "2ce69b1af49952cd4121a9c3055faa679e748ce774c7f1fda9657f936cae902f",
-    "https://bcr.bazel.build/modules/jq.bzl/0.1.0/source.json": "746bf13cac0860f091df5e4911d0c593971cd8796b5ad4e809b2f8e133eee3d5",
     "https://bcr.bazel.build/modules/jsoncpp/1.9.5/MODULE.bazel": "31271aedc59e815656f5736f282bb7509a97c7ecb43e927ac1a37966e0578075",
     "https://bcr.bazel.build/modules/jsoncpp/1.9.5/source.json": "4108ee5085dd2885a341c7fab149429db457b3169b86eb081fa245eadf69169d",
     "https://bcr.bazel.build/modules/libpfm/4.11.0/MODULE.bazel": "45061ff025b301940f1e30d2c16bea596c25b176c8b6b3087e92615adbd52902",
@@ -175,7 +161,6 @@
     "https://bcr.bazel.build/modules/opentelemetry-proto/1.5.0/source.json": "046b721ce203e88cdaad44d7dd17a86b7200eab9388b663b234e72e13ff7b143",
     "https://bcr.bazel.build/modules/opentracing-cpp/1.6.0/MODULE.bazel": "b3925269f63561b8b880ae7cf62ccf81f6ece55b62cd791eda9925147ae116ec",
     "https://bcr.bazel.build/modules/opentracing-cpp/1.6.0/source.json": "da1cb1add160f5e5074b7272e9db6fd8f1b3336c15032cd0a653af9d2f484aed",
-    "https://bcr.bazel.build/modules/package_metadata/0.0.2/MODULE.bazel": "fb8d25550742674d63d7b250063d4580ca530499f045d70748b1b142081ebb92",
     "https://bcr.bazel.build/modules/package_metadata/0.0.5/MODULE.bazel": "ef4f9439e3270fdd6b9fd4dbc3d2f29d13888e44c529a1b243f7a31dfbc2e8e4",
     "https://bcr.bazel.build/modules/package_metadata/0.0.5/source.json": "2326db2f6592578177751c3e1f74786b79382cd6008834c9d01ec865b9126a85",
     "https://bcr.bazel.build/modules/platforms/0.0.10/MODULE.bazel": "8cb8efaf200bdeb2150d93e162c40f388529a25852b332cec879373771e48ed5",
@@ -240,14 +225,12 @@
     "https://bcr.bazel.build/modules/rules_cc/0.0.15/MODULE.bazel": "6704c35f7b4a72502ee81f61bf88706b54f06b3cbe5558ac17e2e14666cd5dcc",
     "https://bcr.bazel.build/modules/rules_cc/0.0.16/MODULE.bazel": "7661303b8fc1b4d7f532e54e9d6565771fea666fbdf839e0a86affcd02defe87",
     "https://bcr.bazel.build/modules/rules_cc/0.0.17/MODULE.bazel": "2ae1d8f4238ec67d7185d8861cb0a2cdf4bc608697c331b95bf990e69b62e64a",
+    "https://bcr.bazel.build/modules/rules_cc/0.0.17/source.json": "4db99b3f55c90ab28d14552aa0632533e3e8e5e9aea0f5c24ac0014282c2a7c5",
     "https://bcr.bazel.build/modules/rules_cc/0.0.2/MODULE.bazel": "6915987c90970493ab97393024c156ea8fb9f3bea953b2f3ec05c34f19b5695c",
     "https://bcr.bazel.build/modules/rules_cc/0.0.5/MODULE.bazel": "be41f87587998fe8890cd82ea4e848ed8eb799e053c224f78f3ff7fe1a1d9b74",
     "https://bcr.bazel.build/modules/rules_cc/0.0.6/MODULE.bazel": "abf360251023dfe3efcef65ab9d56beefa8394d4176dd29529750e1c57eaa33f",
     "https://bcr.bazel.build/modules/rules_cc/0.0.8/MODULE.bazel": "964c85c82cfeb6f3855e6a07054fdb159aced38e99a5eecf7bce9d53990afa3e",
     "https://bcr.bazel.build/modules/rules_cc/0.0.9/MODULE.bazel": "836e76439f354b89afe6a911a7adf59a6b2518fafb174483ad78a2a2fde7b1c5",
-    "https://bcr.bazel.build/modules/rules_cc/0.1.1/MODULE.bazel": "2f0222a6f229f0bf44cd711dc13c858dad98c62d52bd51d8fc3a764a83125513",
-    "https://bcr.bazel.build/modules/rules_cc/0.2.14/MODULE.bazel": "353c99ed148887ee89c54a17d4100ae7e7e436593d104b668476019023b58df8",
-    "https://bcr.bazel.build/modules/rules_cc/0.2.14/source.json": "55d0a4587c5592fad350f6e698530f4faf0e7dd15e69d43f8d87e220c78bea54",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.10.1/MODULE.bazel": "b9527010e5fef060af92b6724edb3691970a5b1f76f74b21d39f7d433641be60",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.10.1/source.json": "9300e71df0cdde0952f10afff1401fa664e9fc5d9ae6204660ba1b158d90d6a6",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.9.0/MODULE.bazel": "c9e8c682bf75b0e7c704166d79b599f93b72cfca5ad7477df596947891feeef6",
@@ -306,8 +289,6 @@
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.0/MODULE.bazel": "45345e4aba35dd6e4701c1eebf5a4e67af4ed708def9ebcdc6027585b34ee52d",
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.3/MODULE.bazel": "b66eadebd10f1f1b25f52f95ab5213a57e82c37c3f656fcd9a57ad04d2264ce7",
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.3/source.json": "45bd343155bdfed2543f0e39b80ff3f6840efc31975da4b5795797f4c94147ad",
-    "https://bcr.bazel.build/modules/rules_oci/2.2.6/MODULE.bazel": "2ba6ddd679269e00aeffe9ca04faa2d0ca4129650982c9246d0d459fe2da47d9",
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@@ -340,8 +321,7 @@
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+    "https://bcr.bazel.build/modules/rules_shell/0.3.0/source.json": "c55ed591aa5009401ddf80ded9762ac32c358d2517ee7820be981e2de9756cf3",
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@@ -359,19 +339,14 @@
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@@ -413,7 +388,7 @@
     },
     "@@aspect_rules_esbuild~//esbuild:extensions.bzl%esbuild": {
       "general": {
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@@ -1290,247 +1265,6 @@
         "recordedRepoMappingEntries": []
       }
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-        "recordedDirentsInputs": {},
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-            "ruleClassName": "oci_pull",
-            "attributes": {
-              "www_authenticate_challenges": {},
-              "scheme": "https",
-              "registry": "index.docker.io",
-              "repository": "library/eclipse-temurin",
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-              "bazel_tags": []
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-              "identifier": "sha256:d286b5352d98777bbf727f54038b04f0145cd9b76ca83f38a67aa111d4303748",
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-              "reproducible": true
-            }
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-            "ruleClassName": "oci_pull",
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-              "scheme": "https",
-              "registry": "index.docker.io",
-              "repository": "library/ubuntu",
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-              "scheme": "https",
-              "registry": "index.docker.io",
-              "repository": "library/ubuntu",
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-            "ruleClassName": "crane_repositories",
-            "attributes": {
-              "platform": "linux_armv6",
-              "crane_version": "v0.18.0"
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-          },
-          "oci_crane_linux_i386": {
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-            "ruleClassName": "crane_repositories",
-            "attributes": {
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-              "crane_version": "v0.18.0"
-            }
-          },
-          "oci_crane_linux_s390x": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "crane_repositories",
-            "attributes": {
-              "platform": "linux_s390x",
-              "crane_version": "v0.18.0"
-            }
-          },
-          "oci_crane_linux_amd64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "crane_repositories",
-            "attributes": {
-              "platform": "linux_amd64",
-              "crane_version": "v0.18.0"
-            }
-          },
-          "oci_crane_windows_armv6": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "crane_repositories",
-            "attributes": {
-              "platform": "windows_armv6",
-              "crane_version": "v0.18.0"
-            }
-          },
-          "oci_crane_windows_amd64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "crane_repositories",
-            "attributes": {
-              "platform": "windows_amd64",
-              "crane_version": "v0.18.0"
-            }
-          },
-          "oci_crane_toolchains": {
-            "bzlFile": "@@rules_oci~//oci/private:toolchains_repo.bzl",
-            "ruleClassName": "toolchains_repo",
-            "attributes": {
-              "toolchain_type": "@rules_oci//oci:crane_toolchain_type",
-              "toolchain": "@oci_crane_{platform}//:crane_toolchain"
-            }
-          },
-          "oci_regctl_darwin_amd64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "darwin_amd64"
-            }
-          },
-          "oci_regctl_darwin_arm64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "darwin_arm64"
-            }
-          },
-          "oci_regctl_linux_arm64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "linux_arm64"
-            }
-          },
-          "oci_regctl_linux_s390x": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "linux_s390x"
-            }
-          },
-          "oci_regctl_linux_amd64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "linux_amd64"
-            }
-          },
-          "oci_regctl_windows_amd64": {
-            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
-            "ruleClassName": "regctl_repositories",
-            "attributes": {
-              "platform": "windows_amd64"
-            }
-          },
-          "oci_regctl_toolchains": {
-            "bzlFile": "@@rules_oci~//oci/private:toolchains_repo.bzl",
-            "ruleClassName": "toolchains_repo",
-            "attributes": {
-              "toolchain_type": "@rules_oci//oci:regctl_toolchain_type",
-              "toolchain": "@oci_regctl_{platform}//:regctl_toolchain"
-            }
-          }
-        },
-        "moduleExtensionMetadata": {
-          "explicitRootModuleDirectDeps": [
-            "eclipse_temurin_17",
-            "eclipse_temurin_17_linux_amd64",
-            "ubuntu_24_04",
-            "ubuntu_24_04_linux_amd64"
-          ],
-          "explicitRootModuleDirectDevDeps": [],
-          "useAllRepos": "NO",
-          "reproducible": false
-        },
-        "recordedRepoMappingEntries": [
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-            "aspect_bazel_lib~",
-            "bazel_tools",
-            "bazel_tools"
-          ],
-          [
-            "bazel_features~",
-            "bazel_tools",
-            "bazel_tools"
-          ],
-          [
-            "rules_oci~",
-            "aspect_bazel_lib",
-            "aspect_bazel_lib~"
-          ],
-          [
-            "rules_oci~",
-            "bazel_features",
-            "bazel_features~"
-          ],
-          [
-            "rules_oci~",
-            "bazel_skylib",
-            "bazel_skylib~"
-          ]
-        ]
-      }
-    },
     "@@rules_scala~//scala/extensions:config.bzl%scala_config": {
       "general": {
         "bzlTransitiveDigest": "TdBxhkZTM7VU6teIFS+KoonKU7wmb5BL7leCWWx7yX8=",
@@ -1559,7 +1293,7 @@
     },
     "@@rules_scala~//scala/extensions:deps.bzl%scala_deps": {
       "general": {
-        "bzlTransitiveDigest": "5SDZrXQHW6tI/VEw+La2OPOK4ZWm0LGTxnChXOXBCag=",
+        "bzlTransitiveDigest": "F2PMm61fmZ/IE+VSw1rigJ71hBDD7k3vqyYR1/GgXeA=",
         "usagesDigest": "kwo8oolISmSSITnit4b4S0vBiUtHlHK0WLDUwScxmOg=",
         "recordedFileInputs": {},
         "recordedDirentsInputs": {},
@@ -5170,6 +4904,85 @@
           ]
         ]
       }
+    },
+    "@@toolchains_llvm~//toolchain/extensions:llvm.bzl%llvm": {
+      "general": {
+        "bzlTransitiveDigest": "afRF0aFOIUrkYl3o040WQ606ep1qciEXzjnAxT3Kek8=",
+        "usagesDigest": "sYVuhiCAQehFTnGTv0bNtTBR4WorebpWBNxF0mRusyw=",
+        "recordedFileInputs": {},
+        "recordedDirentsInputs": {},
+        "envVariables": {},
+        "generatedRepoSpecs": {
+          "llvm_toolchain_llvm": {
+            "bzlFile": "@@toolchains_llvm~//toolchain:rules.bzl",
+            "ruleClassName": "llvm",
+            "attributes": {
+              "alternative_llvm_sources": [],
+              "auth_patterns": {},
+              "distribution": "auto",
+              "exec_arch": "",
+              "exec_os": "",
+              "libclang_rt": {},
+              "llvm_mirror": "",
+              "llvm_version": "20.1.2",
+              "llvm_versions": {},
+              "netrc": "",
+              "sha256": {},
+              "strip_prefix": {},
+              "urls": {}
+            }
+          },
+          "llvm_toolchain": {
+            "bzlFile": "@@toolchains_llvm~//toolchain:rules.bzl",
+            "ruleClassName": "toolchain",
+            "attributes": {
+              "absolute_paths": false,
+              "archive_flags": {},
+              "compile_flags": {},
+              "conly_flags": {},
+              "coverage_compile_flags": {},
+              "coverage_link_flags": {},
+              "cxx_builtin_include_directories": {},
+              "cxx_flags": {},
+              "cxx_standard": {},
+              "dbg_compile_flags": {},
+              "exec_arch": "",
+              "exec_os": "",
+              "extra_exec_compatible_with": {},
+              "extra_target_compatible_with": {},
+              "link_flags": {},
+              "link_libs": {},
+              "llvm_versions": {
+                "": "20.1.2"
+              },
+              "opt_compile_flags": {},
+              "opt_link_flags": {},
+              "stdlib": {},
+              "target_settings": {},
+              "unfiltered_compile_flags": {},
+              "toolchain_roots": {},
+              "sysroot": {}
+            }
+          }
+        },
+        "recordedRepoMappingEntries": [
+          [
+            "toolchains_llvm~",
+            "bazel_skylib",
+            "bazel_skylib~"
+          ],
+          [
+            "toolchains_llvm~",
+            "bazel_tools",
+            "bazel_tools"
+          ],
+          [
+            "toolchains_llvm~",
+            "toolchains_llvm",
+            "toolchains_llvm~"
+          ]
+        ]
+      }
     }
   }
 }

actions-model-usage-analysis.md

@@ -9,16 +9,15 @@ This document analyzes all actions and commands in `src/main/scala/net/eagle0/ea
 
 ## Summary
 
-Based on BUILD.bazel dependency analysis (2025-09-16, updated 2025-09-17):
+Based on BUILD.bazel dependency analysis (2025-09-16):
 - **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 Fully Migrated (No Protobuf):** 4 (8.3%)
+- **Actions Partially Migrated:** 20 (41.7%)
 - **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
 
@@ -94,7 +93,6 @@ 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 |
@@ -117,7 +115,7 @@ These actions use protoless base classes but still have some protobuf dependenci
 | 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) |
+| ProvinceConqueredAction.scala | ProtolessSimpleAction | Depends on `common_unit_scala_proto` |
 | SafePassageArmiesProceedAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
 | ShipmentArrivedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
 | TruceTurnBackPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
@@ -248,30 +246,21 @@ Based on the BUILD.bazel dependency analysis, here are the key findings and reco
 ### 🎯 Action Migration Progress
 
 **Migration Statistics:**
-- 5/48 Actions fully migrated (10.4%)
+- 4/48 Actions fully migrated (8.3%)
 - 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
+2. **ProvinceHeldAction** - Component-based design pattern (gameId, currentRoundId, specific models)
+3. **UnaffiliatedHeroAppearedAction** - Hero appearance with name generation
+4. **WithdrawnArmiesReturnHomeAction** - Army withdrawal mechanics
 
 **Key Migration Patterns:**
-- ✅ Use specific components instead of full GameState (see ProvinceHeldAction, ProvinceConqueredAction)
+- ✅ Use specific components instead of full GameState (see ProvinceHeldAction)
 - ✅ 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
@@ -301,5 +290,4 @@ Based on the BUILD.bazel dependency analysis, here are the key findings and reco
 
 ---
 
-*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*
+*Updated on 2025-09-16 - Analysis based on BUILD.bazel dependencies and code review*

ci/BUILD.bazel

@@ -1,128 +0,0 @@
-load("@rules_oci//oci:defs.bzl", "oci_image", "oci_load", "oci_push")
-load("@rules_pkg//pkg:tar.bzl", "pkg_tar")
-
-#
-# Eagle Server Docker Image
-#
-# Build: bazel build //ci:eagle_server_image
-# Load:  bazel run //ci:eagle_server_load
-# Push:  bazel run //ci:eagle_server_push
-#
-
-# Package the deploy JAR
-pkg_tar(
-    name = "eagle_server_jar_layer",
-    srcs = ["//src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar"],
-    package_dir = "/app",
-)
-
-# Package the game resources needed at runtime
-pkg_tar(
-    name = "eagle_resources_layer",
-    srcs = [
-        "//src/main/resources/net/eagle0/eagle:beasts",
-        "//src/main/resources/net/eagle0/eagle:game_parameters",
-        "//src/main/resources/net/eagle0/eagle:headshots",
-        "//src/main/resources/net/eagle0/eagle:heroes",
-        "//src/main/resources/net/eagle0/eagle:province_map",
-        "//src/main/resources/net/eagle0/eagle:settings",
-    ],
-    package_dir = "/app/resources",
-)
-
-oci_image(
-    name = "eagle_server_image",
-    base = "@eclipse_temurin_17_linux_amd64",
-    entrypoint = [
-        "java",
-        "-Xmx4g",
-        "-XX:+UseG1GC",
-        "-jar",
-        "/app/eagle_server_deploy.jar",
-    ],
-    env = {
-        "JAVA_OPTS": "-Xmx4g -XX:+UseG1GC",
-    },
-    exposed_ports = ["40032/tcp"],
-    tars = [
-        ":eagle_server_jar_layer",
-        ":eagle_resources_layer",
-    ],
-    workdir = "/app",
-)
-
-# Load into Docker locally: bazel run //ci:eagle_server_load
-oci_load(
-    name = "eagle_server_load",
-    image = ":eagle_server_image",
-    repo_tags = ["eagle0/eagle-server:latest"],
-)
-
-# Push to DigitalOcean Container Registry
-oci_push(
-    name = "eagle_server_push",
-    image = ":eagle_server_image",
-    repository = "registry.digitalocean.com/eagle0/eagle-server",
-)
-
-#
-# Shardok Server Docker Image
-#
-# Build: bazel build //ci:shardok_server_image
-# Load:  bazel run //ci:shardok_server_load
-# Push:  bazel run //ci:shardok_server_push
-#
-
-# Package the Shardok binary
-pkg_tar(
-    name = "shardok_binary_layer",
-    srcs = ["//src/main/cpp/net/eagle0/shardok:shardok-server"],
-    package_dir = "/app",
-)
-
-# Package the Shardok resources (battalion types, settings)
-pkg_tar(
-    name = "shardok_resources_layer",
-    srcs = [
-        "//src/main/resources/net/eagle0/shardok:battalion_types",
-        "//src/main/resources/net/eagle0/shardok:settings",
-    ],
-    package_dir = "/app/resources",
-)
-
-# Package the converted maps
-pkg_tar(
-    name = "shardok_maps_layer",
-    srcs = ["//src/main/resources/net/eagle0/shardok/maps"],
-    package_dir = "/app/resources/maps",
-)
-
-oci_image(
-    name = "shardok_server_image",
-    base = "@ubuntu_24_04_linux_amd64",
-    entrypoint = ["/app/shardok-server"],
-    exposed_ports = [
-        "40042/tcp",
-        "40052/tcp",
-    ],
-    tars = [
-        ":shardok_binary_layer",
-        ":shardok_resources_layer",
-        ":shardok_maps_layer",
-    ],
-    workdir = "/app",
-)
-
-# Load into Docker locally: bazel run //ci:shardok_server_load
-oci_load(
-    name = "shardok_server_load",
-    image = ":shardok_server_image",
-    repo_tags = ["eagle0/shardok-server:latest"],
-)
-
-# Push to DigitalOcean Container Registry
-oci_push(
-    name = "shardok_server_push",
-    image = ":shardok_server_image",
-    repository = "registry.digitalocean.com/eagle0/shardok-server",
-)

ci/unity_version.sh

@@ -1 +1,2 @@
-UNITY_VERSION='6000.3.0f1'
+
+UNITY_VERSION='6000.1.11f1'

docker-compose.prod.yml

@@ -1,47 +0,0 @@
-# Docker Compose for local testing of production images
-# Build images: bazel run //ci:eagle_server_load && bazel run //ci:shardok_server_load
-# Run: docker compose -f docker-compose.prod.yml up
-
-services:
-  eagle:
-    image: eagle0/eagle-server:latest
-    container_name: eagle-server
-    ports:
-      - "40032:40032"
-    environment:
-      # Eagle server configuration
-      EAGLE_GRPC_PORT: "40032"
-      SHARDOK_HOST: "shardok"
-      SHARDOK_PORT: "40042"
-      # Resource paths (relative to /app in container)
-      EAGLE_RESOURCES_PATH: "/app/resources"
-    volumes:
-      # Mount saves directory for persistence
-      - ./saves:/app/saves
-    depends_on:
-      - shardok
-    restart: unless-stopped
-    healthcheck:
-      test: ["CMD", "nc", "-z", "localhost", "40032"]
-      interval: 30s
-      timeout: 10s
-      retries: 3
-      start_period: 30s
-
-  shardok:
-    image: eagle0/shardok-server:latest
-    container_name: shardok-server
-    ports:
-      - "40042:40042"
-      - "40052:40052"
-    environment:
-      # Shardok server configuration
-      SHARDOK_RESOURCES_PATH: "/app/resources"
-      SHARDOK_MAPS_PATH: "/app/resources/maps"
-    restart: unless-stopped
-    healthcheck:
-      test: ["CMD", "nc", "-z", "localhost", "40042"]
-      interval: 30s
-      timeout: 10s
-      retries: 3
-      start_period: 10s

docs/COMMAND_PROTO_USAGE_ANALYSIS.md

@@ -1,280 +0,0 @@
-# CommandProto Usage Analysis in shardok/ai
-
-This document analyzes all remaining usages of `CommandProto` (protocol buffer representation) in the AI code and identifies opportunities to eliminate proto conversion by using `ShardokCommand` directly.
-
-## Summary
-
-**Total CommandProto usages found:** 42 locations across 9 files
-
-**Eliminated:** 6 usages (14%) - ✅ **Phase 1 Complete**
-**Can be eliminated:** ~14 usages (33%)
-**Must keep (for now):** ~22 usages (53%)
-
----
-
-## Files with CommandProto Usage
-
-### 1. AICommandFilter.cpp (6 usages) - ✅ **COMPLETED** (PR #4505)
-**Location:** Lines 146, 189, 252, 356, 387, 428
-
-**Original usage:**
-```cpp
-const auto cmdProto = cmd.GetCommandProto();
-if (!cmdProto.has_target()) { ... }
-const auto& targetCoords = cmdProto.target();
-if (!cmdProto.has_actor()) { ... }
-const auto unitId = cmdProto.actor().value();
-```
-
-**Replaced with:**
-```cpp
-const int targetRow = cmd.GetTargetRow();
-const int targetCol = cmd.GetTargetColumn();
-if (targetRow < 0 || targetCol < 0) {
-    throw ShardokInternalErrorException("Command missing required target");
-}
-const Coords targetCoords(targetRow, targetCol);
-
-const int actorId = cmd.GetActorUnitId();
-if (actorId < 0) {
-    throw ShardokInternalErrorException("Command missing required actor");
-}
-```
-
-**Status:** ✅ **ELIMINATED** - Replaced with direct accessors + exception handling
-**Impact:** Eliminated 6 proto conversions in hot path (command filtering)
-**Completed:** Phase 1, PR #4505
-
----
-
-### 2. ShardokAIClient.cpp (8 usages)
-**Location:** Lines 83, 86, 87, 102, 105, 237, 261, 311, 356
-
-**Usage breakdown:**
-
-#### a) Command validation (lines 83-87)
-```cpp
-void CheckCommand(const CommandProto &realDescriptor, const CommandProto &guessedDescriptor) {
-    differencer.IgnoreField(CommandProto::descriptor()->FindFieldByNumber(
-            CommandProto::kFollowUpCommandTypesFieldNumber));
-```
-**Status:** ❌ **MUST KEEP** - Uses protobuf reflection for comparison
-**Reason:** Comparing proto messages for correctness checking requires proto API
-
-#### b) GetAvailableCommandProtos calls (lines 105, 356)
-```cpp
-const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
-if (const auto &availableCommands = engine.GetAvailableCommandProtos(playerId, false);
-```
-**Status:** ✅ **CAN REPLACE** - Should use `GetAvailableCommandsForAIPlayer()` instead
-**Impact:** This is a major conversion point - converts entire command list to protos
-**Priority:** HIGH (converts all commands to proto unnecessarily)
-
-#### c) Strategy selector methods (lines 102, 237, 261, 311)
-```cpp
-const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults
-```
-**Status:** ✅ **CAN REPLACE** - Depends on fixing strategy selector signatures
-**Priority:** MEDIUM (depends on other refactors)
-
----
-
-### 3. IterativeDeepeningAI.cpp/hpp (4 usages)
-**Location:** Lines 41, 272 (cpp), 73, 96 (hpp)
-
-**Current usage:**
-```cpp
-const std::vector<CommandProto>& commands,
-```
-
-**Status:** ✅ **CAN REPLACE** - These methods should accept `CommandListSPtr` instead
-**Impact:** Major - this is the main AI search algorithm
-**Priority:** HIGH (core AI algorithm)
-
-**Note:** IterativeDeepeningAI already receives commands as proto vectors. The conversion happens upstream at the entry point. Need to trace back to find where `GetAvailableCommandProtos` is called.
-
----
-
-### 4. AIFleeDecisionCalculator.cpp/hpp (6 usages)
-**Location:** Lines 17, 38, 39, 62, 63 (hpp), 18, 19, 137, 138 (cpp)
-
-**Current usage:**
-```cpp
-const vector<CommandProto>& availableCommands,
-const vector<CommandProto>::const_iterator& fleeCommand,
-```
-
-**Status:** ✅ **CAN REPLACE** - Should use `CommandListSPtr` and indices instead
-**Impact:** Flee decision logic could avoid proto conversion
-**Priority:** MEDIUM
-
----
-
-### 5. AIAttackerStrategySelector.cpp/hpp (2 usages)
-**Location:** Line 30 in both files
-
-**Current usage:**
-```cpp
-const vector<CommandProto>& availableCommands) -> AIStrategy
-```
-
-**Status:** ⚠️ **PARTIALLY REPLACEABLE** - Currently doesn't use the commands parameter
-**Current implementation:**
-```cpp
-const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
-    // Parameter is commented out - not used!
-    return AIStrategy::DEFAULT;
-}
-```
-**Priority:** LOW (parameter unused, but signature should be consistent)
-
----
-
-### 6. AICommandEvaluator.hpp (1 usage)
-**Location:** Line 27
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
----
-
-### 7. AIScoreCalculator.hpp (1 usage)
-**Location:** Line 24
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
----
-
-### 8. AIWaterCrossingCommandChooser.hpp (1 usage)
-**Location:** Line 20
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
----
-
-## Key Conversion Points (Entry Points)
-
-### ShardokEngine::GetAvailableCommandProtos()
-This method converts the entire command list from `CommandListSPtr` to `vector<CommandProto>`.
-
-**Current flow:**
-```
-ShardokEngine::GetAvailableCommandsForAIPlayer() → CommandListSPtr
-                ↓ (conversion)
-ShardokEngine::GetAvailableCommandProtos() → vector<CommandProto>
-                ↓
-AI algorithms (IterativeDeepeningAI, etc.)
-```
-
-**Desired flow:**
-```
-ShardokEngine::GetAvailableCommandsForAIPlayer() → CommandListSPtr
-                ↓ (no conversion!)
-AI algorithms use CommandSPtr directly
-```
-
----
-
-## Recommendations by Priority
-
-### HIGH Priority (Performance-critical hot paths)
-
-1. **AICommandFilter.cpp (6 usages)**
-   - Replace `cmd.GetCommandProto()` with direct accessor methods
-   - Use `GetActorUnitId()`, `GetTargetRow()`, `GetTargetColumn()`
-   - Impact: Eliminates 6 proto conversions per filtered command
-
-2. **ShardokAIClient.cpp - GetAvailableCommandProtos calls**
-   - Replace calls to `GetAvailableCommandProtos()` with `GetAvailableCommandsForAIPlayer()`
-   - Impact: Eliminates conversion of entire command list
-
-3. **IterativeDeepeningAI**
-   - Change signature from `vector<CommandProto>` to `CommandListSPtr`
-   - Impact: Main AI search algorithm avoids proto conversion
-
-### MEDIUM Priority
-
-4. **AIFleeDecisionCalculator**
-   - Change to use `CommandListSPtr` and indices
-   - Impact: Flee decision logic avoids proto
-
-5. **ShardokAIClient strategy methods**
-   - Update signatures to use `CommandListSPtr`
-   - Cascades to strategy selectors
-
-### LOW Priority
-
-6. **Type aliases**
-   - Remove unused `using CommandProto` declarations
-   - Clean up imports
-
----
-
-## Migration Strategy
-
-### Phase 1: Low-hanging fruit (AICommandFilter) - ✅ **COMPLETED** (PR #4505)
-- ✅ Replaced 6 proto conversions with direct accessor calls
-- ✅ Added exception handling for missing actor/target data
-- ✅ No signature changes needed
-- ✅ Immediate performance benefit
-- **PR:** #4505
-
-### Phase 2: Entry point (ShardokAIClient)
-- Replace `GetAvailableCommandProtos()` calls with `GetAvailableCommandsForAIPlayer()`
-- Update method signatures in ShardokAIClient
-
-### Phase 3: Core AI (IterativeDeepeningAI)
-- Change IterativeDeepeningAI to accept `CommandListSPtr`
-- This is the biggest change but has highest impact
-
-### Phase 4: Supporting systems
-- Update AIFleeDecisionCalculator
-- Update strategy selectors
-- Clean up type aliases
-
-### Phase 5: Validation code
-- Keep proto-based validation as-is (uses reflection)
-- Consider if validation is still needed in production
-
----
-
-## Notes
-
-- **MCTS already converted**: The MCTS code path already uses `CommandListSPtr` directly
-- **Proto still needed**: For serialization/network communication (not in AI hot path)
-- **Validation**: Proto comparison in CheckCommand() should remain (uses proto reflection)
-
----
-
-## Estimated Impact
-
-**Proto conversions eliminated:** ~20-25 per command choice
-**Performance gain:** Eliminates hundreds of allocations per AI decision
-**Code simplification:** Removes proto conversion layer from AI
-
-**Before:**
-```
-Command → Proto → AI Decision
-```
-
-**After:**
-```
-Command → AI Decision (direct)
-```

docs/DEPROTO_PLAN.md

@@ -1,334 +0,0 @@
-# Deproto Migration Plan
-
-## Vision
-
-**Protocol buffers should only be used at the edges** — for network serialization (gRPC) and disk persistence. Inside the Eagle game engine, all logic should operate on native Scala models.
-
-```
-┌─────────────────────────────────────────────────────────────────────┐
-│                         GRPC BOUNDARY                               │
-│  EagleServiceImpl.scala  ←→  Proto Messages  ←→  Unity Client       │
-└─────────────────────────────────────────────────────────────────────┘
-                                   ↓
-                          GameStateConverter
-                                   ↓
-┌─────────────────────────────────────────────────────────────────────┐
-│                         SCALA ENGINE                                │
-│                                                                     │
-│   GameStateC ───→ Actions ───→ ActionResultT ───→ New GameStateC   │
-│       ↑                                                   │        │
-│       │               (Pure Scala models)                 │        │
-│       └───────────────────────────────────────────────────┘        │
-│                                                                     │
-│   HeroC, FactionC, ProvinceC, BattalionC, ArmyC, etc.              │
-└─────────────────────────────────────────────────────────────────────┘
-                                   ↓
-                          GameStateConverter
-                                   ↓
-┌─────────────────────────────────────────────────────────────────────┐
-│                      PERSISTENCE BOUNDARY                           │
-│  GameHistory.scala  ←→  Proto Messages  ←→  File/Database          │
-└─────────────────────────────────────────────────────────────────────┘
-```
-
----
-
-## Current State
-
-### Completed Phases
-
-| Phase | Status | Summary |
-|-------|--------|---------|
-| Phase 1: GameStateC | **Complete** | Scala `GameState` model with 22 fields |
-| Phase 2: EngineImpl | **Complete** | Holds Scala `GameState` internally |
-| Phase 3: GameHistory | **Complete** | `stateAfter` returns Scala GameState |
-| Phase 4: ActionResultT | **Complete** | All 59 actions return `ActionResultT` |
-| Phase 5: Action Base Classes | **Complete** | All `RandomSequentialResultsAction` and `DeterministicSingleResultAction` converted to T-type base classes |
-| Phase 5b: Base Class Cleanup | **Complete** | `RandomSequentialResultsAction` and `DeterministicSingleResultAction` deleted |
-| Phase 5c: RoundPhaseAdvancer Actions | **Complete** | All actions called by RoundPhaseAdvancer accept Scala GameState |
-| Phase 5d: RoundPhaseAdvancer Itself | **Complete** | RoundPhaseAdvancer.checkForPhaseAdvancement takes Scala GameState |
-
-### Phase 5c/5d Progress (Complete)
-
-`RoundPhaseAdvancer.checkForPhaseAdvancement` now accepts Scala `GameState` and `ActionResultApplier` directly (PR #4677).
-
-| Action | PR | Status |
-|--------|-----|--------|
-| `PrisonerExchangeAction` | #4670 | ✅ Merged |
-| `PerformForcedTurnBackAction` | #4671 | ✅ Merged |
-| `PerformHeroDeparturesAction` | #4672 | ✅ Merged |
-| `RequestFreeForAllBattlesAction` | #4673 | ✅ Merged |
-| `EndPlayerCommandsPhaseAction` | #4674 | ✅ Merged |
-| `EndDiplomacyResolutionPhaseAction` | #4675 | ✅ Merged |
-| `RoundPhaseAdvancer` itself | #4677 | ✅ Merged |
-
-### EngineImpl Progress
-
-| Change | PR | Status |
-|--------|-----|--------|
-| `recursiveTransform` deleted | #4677 | ✅ Merged |
-| `recursiveTransformT` uses `RandomStateTSequencer` | #4677 | ✅ Merged |
-
-### Current Architecture
-
-**ActionResultT Production (100% Complete):**
-- All actions produce `ActionResultT`
-- Conversion to `ActionResultProto` happens via `ActionResultProtoConverter.toProto()`
-- No direct `ActionResultProto` construction outside the converter
-
-**ActionResultProto Consumption (Next Target):**
-- `ActionResultProtoApplierImpl` - applies proto results to proto GameState
-- `RoundPhaseAdvancer` - calls converter, passes protos to applier
-- `InMemoryHistory` / `PersistedHistory` - stores proto results
-- Service layer (`GameController`, `GamesManager`, etc.) - uses proto for client communication
-
----
-
-## Phase 6: Migrate to ActionResultT Consumers
-
-### Objective
-
-Eliminate internal consumption of `ActionResultProto`. Everything inside the engine should work with `ActionResultT`.
-
-### Current Flow (Proto-Heavy)
-```
-Action.execute()
-    → ActionResultT
-    → ActionResultProtoConverter.toProto()
-    → ActionResultProto
-    → ActionResultProtoApplierImpl.applyActionResults()
-    → GameStateProto
-    → GameStateConverter.fromProto()
-    → GameStateC
-```
-
-### Target Flow (T-Types Throughout)
-```
-Action.execute()
-    → ActionResultT
-    → ActionResultApplier.applyActionResults()
-    → GameStateC
-
-    (Proto conversion only at boundaries)
-```
-
-### Key Files to Convert
-
-**Tier 1 - Core Applier:** ✅ **Complete**
-```
-src/main/scala/net/eagle0/eagle/library/actions/applier/ActionResultApplierImpl.scala
-```
-`ActionResultApplier` applies `ActionResultT` directly to Scala `GameState`. The legacy `ActionResultTApplierImpl` wraps it and converts to/from proto for callers that still need proto types.
-
-**Tier 2 - RoundPhaseAdvancer:** ✅ **Complete**
-```
-src/main/scala/net/eagle0/eagle/library/RoundPhaseAdvancer.scala
-```
-Now accepts Scala `GameState` and `ActionResultApplier`. Only converts to proto lazily for `AvailableCommandsFactory` calls.
-
-**Tier 3 - Sequencers:**
-```
-src/main/scala/net/eagle0/eagle/library/actions/impl/common/RandomStateTSequencer.scala
-src/main/scala/net/eagle0/eagle/library/actions/impl/common/RandomStateProtoSequencer.scala
-```
-Modify `RandomStateTSequencer` to thread Scala `GameState` throughout (currently converts to proto internally). Then evaluate whether `RandomStateProtoSequencer` is still needed at all.
-
-**Current State**: `RandomStateTSequencer` accepts Scala `GameState` via its `apply()` method but internally converts to proto. All callback methods (`withRandomActionResult`, `withActionResults`, etc.) pass `GameStateProto` to callers, forcing actions that use the sequencer to work with proto types internally.
-
-**Target State**: Create a fully protoless sequencer where:
-1. `lastState` returns Scala `GameState` (not `lastStateProto`)
-2. All callback methods pass Scala `GameState` to callers
-3. Actions using the sequencer can be fully protoless
-
-**Migration Path**:
-1. Add `lastState: GameState` method alongside `lastStateProto` (non-breaking)
-2. Add parallel callback methods that pass Scala GameState (e.g., `withScalaActionResult`)
-3. Migrate actions one by one to use the new Scala-based callbacks
-4. Once all actions migrated, deprecate/remove proto-based callbacks
-5. Remove `lastStateProto` once no longer used
-
-**RandomStateSequencer Migration Progress** (PR #4679 introduced protoless `RandomStateSequencer`):
-
-| Action | Status |
-|--------|--------|
-| `TruceTurnBackPhaseAction` | ✅ Migrated (PR #4680) |
-| `EndHandleRiotsPhaseAction` | ✅ Migrated (PR #4684) |
-| `PerformVassalCommandsPhaseAction` | ✅ Migrated |
-| `PerformVassalDefenseDecisionsAction` | ✅ Migrated |
-| `EndVassalCommandsPhaseAction` | ✅ Migrated |
-| `PerformReconResolutionAction` | ✅ Migrated |
-| `NewRoundAction` | ✅ Migrated (PR #4698) |
-| `EndBattleAftermathPhaseAction` | ✅ Migrated (PR #4699) |
-| `EndDiplomacyResolutionPhaseAction` | ✅ Migrated |
-| `PerformUnaffiliatedHeroesAction` | ✅ Migrated |
-| `EngineImpl.recursiveTransformT` | ✅ Migrated (PR #4704) |
-| `ProtolessSequentialResultsActionWrapper` | ✅ Migrated (PR #4705) |
-| `LegacyRandomStateTSequencer` | ✅ **Deleted** (PR #4705) |
-
-**TCommandFactory Extraction** (PR #4684):
-
-To enable lightweight mocking of command creation in tests, `TCommandFactory` trait was extracted from `CommandFactory`. This allows tests to mock just the `makeTCommand` method without pulling in all 40+ command dependencies that `CommandFactory` requires.
-
-- `TCommandFactory` - lightweight trait with just `makeTCommand`
-- `CommandFactory extends TCommandFactory` - maintains backward compatibility
-- Actions accepting command factories now use `TCommandFactory` type for better testability
-
-**Tier 4 - History APIs:**
-```
-src/main/scala/net/eagle0/eagle/service/InMemoryHistory.scala
-src/main/scala/net/eagle0/eagle/service/PersistedHistory.scala
-```
-Change APIs to vend Scala `GameState` and `ActionResultT` instead of proto versions. `PersistedHistory` converts to proto internally for disk persistence; `InMemoryHistory` doesn't need proto at all.
-
-### ActionResultProto Consumer Inventory
-
-| File | Usage | Status |
-|------|-------|--------|
-| `ActionResultApplierImpl.scala` | Applies ActionResultT to Scala GameState | ✅ **Complete** |
-| `ActionResultTApplierImpl.scala` | Legacy wrapper - converts to/from proto | Keep until all callers migrated |
-| `RoundPhaseAdvancer.scala` | Uses Scala GameState | ✅ **Complete** |
-| `RandomStateSequencer.scala` | Threads Scala GameState | ✅ **Complete** |
-| `VigorXPApplier.scala` | Has both proto and Scala methods | Scala method exists, delete proto method when unused |
-| `PerformForcedTurnBackAction.scala` | Fully protoless | ✅ **Complete** |
-| `ResolveBattleAction.scala` | Heavy proto usage | Blocked by proto dependencies |
-| `InMemoryHistory.scala` | Stores proto results | Pending - vend Scala types |
-| `PersistedHistory.scala` | Stores proto results | Pending - vend Scala types, convert for disk |
-| `GameController.scala` | Uses proto for client communication | Keep proto (gRPC boundary) |
-
-### Remaining Proto Usage in Actions
-
-**Progress: 46 of 52 action files (88%) are fully protoless.**
-
-The following 6 actions still have proto usage:
-
-| Action | Proto Usages | Blocker | Effort |
-|--------|--------------|---------|--------|
-| `ResolveBattleAction` | 24 | Shardok interface, complex battle logic | High |
-| `PerformVassalCommandsPhaseAction` | 3 | `CommandChoiceHelpers` takes proto GameState | Medium |
-| `EndHandleRiotsPhaseAction` | 2 | `CommandChoiceHelpers` takes proto GameState | Medium |
-| `PerformVassalDefenseDecisionsAction` | 2 | `CommandChoiceHelpers` takes proto GameState | Medium |
-| `EndVassalCommandsPhaseAction` | 1 | `CommandChoiceHelpers` takes proto GameState | Medium |
-| `NewRoundAction` | 1 | `ChronicleEventGenerator` returns proto | Medium |
-
-**Deleted Dead Code:**
-- `UnaffiliatedHeroMovedAction` - Was never called; `PerformUnaffiliatedHeroesAction.heroMovedResult` constructs `ActionResultC` directly
-- `HeroBackstoryUpdateActionGenerator.fromGameState` - Dead method that converted proto to Scala; only `apply(GameState)` is used
-
-**Note**: `PerformReconResolutionAction` and `EndBattleAftermathPhaseAction` are now fully protoless after:
-1. Migrating `FactionT.reconnedProvinces` and `ChangedFactionC.updatedReconnedProvinces` to use Scala `ProvinceView`
-2. Adding Scala overload of `ProvinceViewFilter.withdrawnFromProvinceView`
-
-### Estimated Effort (Remaining)
-
-| Component | Lines | Complexity | Blocks |
-|-----------|-------|------------|--------|
-| `CommandChoiceHelpers` to Scala | ~2000 | High | 4 vassal actions |
-| `ResolveBattleAction` refactor | ~500 | High | 1 action (complex) |
-| `ChronicleEventGenerator` to Scala | ~400 | Medium | 1 action |
-| History API updates | ~100 | Low | - |
-| **Total Remaining** | **~3000** | | |
-
-### Progress Summary
-
-| Metric | Value |
-|--------|-------|
-| Action files fully protoless | 46 / 52 (88%) |
-| Proto usages in remaining actions | 33 total |
-| Biggest blocker | `ResolveBattleAction` (24 usages) |
-| Second biggest blocker | `CommandChoiceHelpers` (blocks 4 actions) |
-
-### Validation
-- [x] `ActionResultApplier` created and tested
-- [x] `RandomStateSequencer` threads Scala GameState throughout
-- [x] `RoundPhaseAdvancer` uses T-types internally
-- [x] `ProvinceViewFilter` has Scala overload for server-side use (PR #4752)
-- [x] `FactionT.reconnedProvinces` and `ChangedFactionC.updatedReconnedProvinces` use Scala `ProvinceView`
-- [x] `ProvinceViewFilter.withdrawnFromProvinceView` has Scala overload
-- [ ] `ProvinceViewFilter` faction-filtered views use Scala types
-- [ ] `CommandChoiceHelpers` uses Scala types
-- [ ] History APIs vend Scala types
-- [ ] No `ActionResultProtoConverter.toProto()` calls except at persistence/gRPC boundaries
-- [ ] All tests pass
-
----
-
-## Phase 7: Clean Up Legacy Utilities
-
-### Objective
-Remove remaining direct proto imports from utility classes.
-
-### Files to Modify
-
-| File | Status |
-|------|--------|
-| `CommandChoiceHelpers.scala` | Accepts proto `GameState`; blocks full deproto of `PerformVassalCommandsPhaseAction` and `PerformVassalDefenseDecisionsAction` |
-| `LegacyProvinceUtils.scala` | Replace with `ProvinceUtils.scala` - `hasImminentRiot` added (PR #4683) |
-| `LegacyFactionUtils.scala` | Replace proto imports with `FactionT` |
-| `LegacyUnaffiliatedHeroUtils.scala` | Replace proto imports with Scala models |
-| `BattalionTypeLoader.scala` | Keep proto for file loading, convert immediately after |
-| `BeastUtils.scala` | **Complete** - now uses Scala `BeastInfo` only |
-
-### View Filters (Partially Complete)
-
-The view filter utilities now have Scala overloads for server-side use:
-
-| File | Status | Notes |
-|------|--------|-------|
-| `ProvinceViewFilter.scala` | **Partial** | `filteredProvinceView(ProvinceT, ScalaGameState)` added (PR #4752) |
-| `ArmyFilter.scala` | **Partial** | `filterArmy(ScalaArmy, Map[BattalionId, BattalionT], Option[FactionId])` added |
-| `BattalionViewFilter.scala` | **Complete** | Uses Scala `BattalionT` throughout |
-| `GameStateViewFilter.scala` | Pending | Uses proto types throughout |
-| `GameStateViewDiffer.scala` | Pending | Works with view protos |
-
-**Unblocked Actions** (PR #4752):
-- `EndBattleAftermathPhaseAction` - can now use `filteredProvinceView(province, scalaGameState)`
-- `PerformReconResolutionAction` - can now use Scala overload
-- `GameStateFactionExtensions` - can now use `updatedReconnedProvinces` with Scala types
-
-**Remaining Work**:
-- Faction-filtered `filteredProvinceView(Province, GameState, FactionId)` still uses proto types
-- `withdrawnFromProvinceView` still uses proto types
-- These are needed for client-facing views with visibility restrictions
-
----
-
-## Phase 8: Verify Boundaries
-
-### Objective
-Confirm protos are used correctly at boundaries — and ONLY there.
-
-### Expected Proto Usage (Keep)
-- `EagleServiceImpl.scala` - gRPC boundary
-- `InMemoryHistory.scala` / `PersistedHistory.scala` - Persistence boundary
-- `*Converter.scala` - Explicit conversion utilities
-- `*Loader.scala` - File loading utilities
-
-### Expected No Proto Usage (Verify)
-- `/library/actions/impl/` - Pure Scala models
-- `/library/util/` - Pure Scala models (except loaders)
-- `/model/state/` - Pure Scala models
-
----
-
-## Open Questions
-
-1. **Persistence Format**: Currently game state is persisted as proto. Should we keep proto for persistence (good for schema evolution) or switch to a different format?
-
-2. **Shardok Integration**: `ResolveBattleAction` communicates with Shardok. Should the Shardok interface use protos (external service) or Scala models?
-
-3. **View Generation**: `GameStateViewDiffer` works with view protos for client updates. Views need Scala models (`ProvinceViewT`, etc.) to allow actions like `EndBattleAftermathPhaseAction` to be fully protoless. The Scala views would be converted to proto only at the gRPC boundary when sending updates to clients.
-
----
-
-## Success Criteria
-
-### Code Quality
-- [ ] Zero proto imports in `/library/actions/` (except boundaries)
-- [ ] Zero proto imports in `/library/` utilities (except loaders)
-- [ ] `GameStateT` used throughout engine internals
-- [ ] Proto usage limited to: `EagleServiceImpl`, loaders, converters, persistence
-
-### Architecture
-- [ ] Clear separation: Scala models (internal) vs Proto (boundaries)
-- [ ] Converters as the only bridge between domains
-- [ ] No "proto creep" into business logic

docs/PRODUCTIONIZATION.md

@@ -1,940 +0,0 @@
-# Eagle0 Productionization Plan
-
-## Executive Summary
-
-This document outlines a plan to move Eagle0's Eagle and Shardok servers from a home Mac to cloud infrastructure while maintaining a QA environment on the Mac. The architecture uses DigitalOcean (already integrated via Spaces) with containerized deployments and GitHub Actions CI/CD.
-
-## Current Architecture
-
-```
-Unity Client
-     │
-     │ gRPC/TLS (eagle0.net:443)
-     ▼
-nginx (home Mac, via router port forward)
-     │
-     ├─► Eagle Server (Scala/JVM, port 40032)
-     │        │
-     │        │ internal gRPC (port 40042)
-     │        ▼
-     └─► Shardok Server (C++, port 40042/40052)
-
-Storage: DigitalOcean Spaces (sfo3.digitaloceanspaces.com)
-DNS: eagle0.net → home IP
-```
-
-**Key observations:**
-- Already using DigitalOcean Spaces for S3-compatible storage
-- Eagle server is a deployable JAR (`eagle_server_deploy.jar`)
-- Shardok server is a native C++ binary
-- nginx handles TLS termination and gRPC routing
-- Self-hosted GitHub Actions runner on Mac
-
----
-
-## Target Architecture
-
-### Production Environment (DigitalOcean)
-
-```
-Unity Client
-     │
-     ├─► eagle0.net (Production)
-     │        │
-     │        ▼
-     │   DigitalOcean Load Balancer (TLS termination)
-     │        │
-     │        ▼
-     │   ┌─────────────────────────────────────┐
-     │   │     DigitalOcean Droplet(s)         │
-     │   │  ┌─────────────┬─────────────────┐  │
-     │   │  │   Eagle     │    Shardok      │  │
-     │   │  │   (Docker)  │    (Docker)     │  │
-     │   │  │   :40032    │    :40042       │  │
-     │   │  └─────────────┴─────────────────┘  │
-     │   └─────────────────────────────────────┘
-     │
-     └─► qa.eagle0.net (QA - home Mac, unchanged)
-              │
-              ▼
-         nginx → Eagle/Shardok (current setup)
-```
-
-### Environment Switching
-
-The Unity client already supports configurable server URLs via the connection screen:
-- **Production:** `eagle0.net` (default)
-- **QA:** `qa.eagle0.net`
-
-No client code changes needed - users can simply type the desired URL.
-
----
-
-## Cloud Provider: DigitalOcean
-
-### Why DigitalOcean
-
-1. **Already integrated** - S3 Spaces storage at `sfo3.digitaloceanspaces.com` with credentials configured
-2. **Simple pricing** - Predictable monthly costs, no surprise bills
-3. **Good performance** - SFO3 datacenter is geographically close
-4. **Managed services** - Load balancers, managed databases if needed later
-5. **Not AWS/GCP** - Per your requirements
-
-### Alternative Considered: Hetzner
-
-- Cheaper for compute ($3.29/mo for 2 vCPU/4GB vs DO's $24/mo)
-- Good EU presence but less US coverage
-- No managed load balancer (need to run HAProxy/nginx yourself)
-- **Recommendation:** Start with DigitalOcean for simplicity; migrate to Hetzner later if cost becomes a concern
-
----
-
-## Infrastructure Components
-
-### 1. Compute: DigitalOcean Droplets
-
-#### Resource Characteristics
-
-- **Eagle server:** CPU-light, possibly RAM-heavy (JVM). Should be always available.
-- **Shardok server:** Very CPU-heavy (AI algorithms). Only needed during tactical battles. Startup time <1 second.
-
-#### Recommended: On-Demand Shardok (Same Droplet)
-
-For current low player count, optimize for cost while maintaining availability:
-
-| Component | Config | Monthly Cost |
-|-----------|--------|--------------|
-| Droplet | s-2vcpu-4gb | $24/mo |
-| Eagle | Always running | - |
-| Shardok | Started on-demand by Eagle, stopped after idle | - |
-
-**How it works:**
-1. Eagle server runs 24/7 - game is always available
-2. When battle starts, Eagle launches Shardok container/process (<1s startup)
-3. After battle ends, idle timer starts (e.g., 5 minutes)
-4. On timeout, Eagle stops Shardok to free CPU
-5. If new battle starts during idle period, Shardok is already warm
-
-**Shardok lifecycle management** (implement in Eagle):
-```scala
-// Pseudocode for Eagle's Shardok management
-object ShardokManager {
-  private var process: Option[Process] = None
-  private var idleTimer: Option[Timer] = None
-
-  def ensureRunning(): Unit = {
-    cancelIdleTimer()
-    if (process.isEmpty) {
-      process = Some(startShardokProcess())
-      waitForHealthCheck()
-    }
-  }
-
-  def onBattleEnd(): Unit = {
-    idleTimer = Some(scheduleShutdown(5.minutes))
-  }
-
-  private def shutdown(): Unit = {
-    process.foreach(_.destroy())
-    process = None
-  }
-}
-```
-
-#### Future Scaling Options
-
-As player count grows and Shardok needs more CPU:
-
-**Option A: Upgrade Droplet (Simplest)**
-
-| Droplet | vCPU | RAM | Cost | Use Case |
-|---------|------|-----|------|----------|
-| s-2vcpu-4gb | 2 shared | 4 GB | $24/mo | Current (few players) |
-| s-4vcpu-8gb | 4 shared | 8 GB | $48/mo | Moderate usage |
-| c-4 | 4 dedicated | 8 GB | $84/mo | CPU-intensive battles |
-| c-8 | 8 dedicated | 16 GB | $168/mo | Multiple concurrent battles |
-
-**Option B: Separate Shardok Droplet (API-driven)**
-
-For heavy Shardok usage with cost optimization:
-
-- **Eagle droplet:** s-1vcpu-2gb ($12/mo) - always on
-- **Shardok droplet:** Created on-demand via DigitalOcean API
-  - c-4 CPU-optimized: $0.125/hour
-  - c-8 CPU-optimized: $0.25/hour
-  - Created when battle starts, destroyed after idle
-  - 30-60s droplet creation time (acceptable if battles are requested in advance)
-
-**Option C: Fly.io for Shardok (Scale-to-Zero)**
-
-For true pay-per-use with fast cold starts:
-
-- **Eagle:** DigitalOcean or Fly.io (~$10/mo)
-- **Shardok:** Fly.io with auto-scaling
-  - Performance VMs: ~$0.0000022/second when running
-  - Cold start: 2-5 seconds
-  - Scales to zero when idle
-
-Requires learning Fly.io but offers best cost efficiency for sporadic usage.
-
-**Option D: Multiple Shardok Instances (High Scale)**
-
-For many concurrent battles:
-
-- **Eagle:** Dedicated droplet with more RAM
-- **Shardok pool:** Multiple Shardok containers/droplets
-- Eagle routes battles to available Shardok instances
-- Could use Kubernetes or Docker Swarm for orchestration
-
-This is overkill for now but documented for future reference.
-
-### 2. Load Balancer
-
-**DigitalOcean Load Balancer:** $12/mo
-
-- TLS termination with Let's Encrypt
-- Health checks
-- Sticky sessions (if needed)
-- Can add more droplets later for HA
-
-**Alternative:** Run nginx on the droplet for $0 extra, but lose automatic failover.
-
-### 3. Storage
-
-**Already configured:** DigitalOcean Spaces
-- Bucket: `eagle0`
-- Region: `sfo3`
-- Used for game saves and assets
-- Cost: $5/mo base + $0.02/GB storage + $0.01/GB transfer
-
-### 4. DNS
-
-**Option A: DigitalOcean DNS (Recommended)**
-- Free with droplets
-- Easy integration
-- API for automated updates
-
-**Option B: Keep current DNS provider**
-- Update A records manually or via script
-
-**DNS Records:**
-```
-eagle0.net          A     <DO Load Balancer IP>
-qa.eagle0.net       A     <Home IP> (unchanged)
-*.eagle0.net        A     <DO Load Balancer IP> (wildcard for future)
-```
-
-### 5. Firewall
-
-**DigitalOcean Cloud Firewall:** Free
-
-```
-Inbound Rules:
-- TCP 443 (HTTPS/gRPC) from anywhere → Load Balancer
-- TCP 22 (SSH) from your IP only → Droplets
-- TCP 40032 (Eagle) from Load Balancer only
-- TCP 40042 (Shardok) from Load Balancer only
-
-Outbound Rules:
-- All traffic allowed (for external APIs, Spaces, etc.)
-```
-
----
-
-## Container Strategy
-
-### Dockerfiles
-
-**Eagle Server** (`ci/eagle_run.Dockerfile` - already exists, needs enhancement):
-
-```dockerfile
-FROM eclipse-temurin:17-jre-alpine
-
-# Add non-root user
-RUN addgroup -S eagle && adduser -S eagle -G eagle
-
-WORKDIR /app
-
-# Copy the deploy JAR
-COPY --chown=eagle:eagle deploy/eagle_server_deploy.jar ./
-
-# Copy game resources
-COPY --chown=eagle:eagle src/main/resources/net/eagle0/eagle/ ./resources/
-
-USER eagle
-
-# Health check
-HEALTHCHECK --interval=30s --timeout=10s --retries=3 \
-  CMD wget -q --spider http://localhost:40032/health || exit 1
-
-EXPOSE 40032
-
-ENTRYPOINT ["java", "-Xmx4g", "-jar", "eagle_server_deploy.jar"]
-CMD ["--eagle-grpc-port", "40032", "--shardok-interface-remote-address", "shardok:40042", "--gpt-model-name", "gpt-4"]
-```
-
-**Shardok Server** (new: `ci/shardok_run.Dockerfile`):
-
-```dockerfile
-FROM ubuntu:22.04
-
-# Install runtime dependencies
-RUN apt-get update && apt-get install -y \
-    libstdc++6 \
-    ca-certificates \
-    && rm -rf /var/lib/apt/lists/*
-
-# Add non-root user
-RUN useradd -r -s /bin/false shardok
-
-WORKDIR /app
-
-# Copy the Shardok binary and dependencies
-COPY --chown=shardok:shardok bazel-bin/src/main/cpp/net/eagle0/shardok/shardok-server ./
-COPY --chown=shardok:shardok src/main/resources/net/eagle0/shardok/maps/ ./maps/
-
-USER shardok
-
-# Health check (need to implement gRPC health endpoint)
-HEALTHCHECK --interval=30s --timeout=10s --retries=3 \
-  CMD ./shardok-server --health-check || exit 1
-
-EXPOSE 40042 40052
-
-ENTRYPOINT ["./shardok-server"]
-```
-
-**Docker Compose** (new: `docker-compose.prod.yml`):
-
-```yaml
-version: '3.8'
-
-services:
-  eagle:
-    build:
-      context: .
-      dockerfile: ci/eagle_run.Dockerfile
-    image: eagle0/eagle-server:${VERSION:-latest}
-    ports:
-      - "40032:40032"
-    environment:
-      - SHARDOK_ADDRESS=shardok:40042
-      - GPT_MODEL_NAME=${GPT_MODEL_NAME:-gpt-4}
-      - JAVA_OPTS=-Xmx4g -XX:+UseG1GC
-    depends_on:
-      - shardok
-    restart: unless-stopped
-    logging:
-      driver: "json-file"
-      options:
-        max-size: "100m"
-        max-file: "5"
-
-  shardok:
-    build:
-      context: .
-      dockerfile: ci/shardok_run.Dockerfile
-    image: eagle0/shardok-server:${VERSION:-latest}
-    ports:
-      - "40042:40042"
-      - "40052:40052"
-    restart: unless-stopped
-    logging:
-      driver: "json-file"
-      options:
-        max-size: "100m"
-        max-file: "5"
-```
-
----
-
-## Build Pipeline
-
-### Build Artifacts
-
-The build process produces:
-1. **Eagle JAR:** `bazel-bin/src/main/scala/net/eagle0/eagle/eagle_server_deploy.jar`
-2. **Shardok binary:** `bazel-bin/src/main/cpp/net/eagle0/shardok/shardok-server`
-
-### Cross-Compilation for Linux
-
-Current builds target macOS (self-hosted runner). For production Linux deployment:
-
-**Option A: Build in Docker (Recommended)**
-```bash
-# Build Eagle (JVM - platform independent)
-bazel build //src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar
-
-# Build Shardok in Linux container
-docker run --rm -v $(pwd):/workspace -w /workspace \
-  ubuntu:22.04 \
-  bash -c "apt-get update && apt-get install -y build-essential && bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server"
-```
-
-**Option B: Use GitHub-hosted Linux runner**
-- Add `runs-on: ubuntu-latest` workflow
-- Builds directly on Linux
-- May need to cache Bazel to avoid long build times
-
-**Option C: Cross-compile on Mac**
-- Configure Bazel for Linux cross-compilation
-- More complex setup but faster iteration
-
-**Recommendation:** Option A (Docker build) for Shardok, since Eagle's JAR is platform-independent.
-
----
-
-## CI/CD Pipeline
-
-### GitHub Actions Workflows
-
-**New workflow:** `.github/workflows/deploy_production.yml`
-
-```yaml
-name: Deploy to Production
-
-on:
-  push:
-    branches: [main]
-    paths:
-      - 'src/main/scala/**'
-      - 'src/main/cpp/**'
-      - 'src/main/protobuf/**'
-      - 'ci/*.Dockerfile'
-      - 'docker-compose.prod.yml'
-  workflow_dispatch:
-    inputs:
-      environment:
-        description: 'Deployment environment'
-        required: true
-        default: 'production'
-        type: choice
-        options:
-          - production
-          - staging
-
-env:
-  REGISTRY: registry.digitalocean.com
-  EAGLE_IMAGE: eagle0/eagle-server
-  SHARDOK_IMAGE: eagle0/shardok-server
-
-jobs:
-  build-eagle:
-    runs-on: self-hosted
-    outputs:
-      version: ${{ steps.version.outputs.version }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          lfs: false
-
-      - name: Set version
-        id: version
-        run: echo "version=$(git rev-parse --short HEAD)" >> $GITHUB_OUTPUT
-
-      - name: Build Eagle server JAR
-        run: bazel build //src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar
-
-      - name: Copy artifacts
-        run: |
-          mkdir -p deploy
-          cp bazel-bin/src/main/scala/net/eagle0/eagle/eagle_server_deploy.jar deploy/
-
-      - name: Build Docker image
-        run: |
-          docker build -f ci/eagle_run.Dockerfile -t ${{ env.REGISTRY }}/${{ env.EAGLE_IMAGE }}:${{ steps.version.outputs.version }} .
-          docker tag ${{ env.REGISTRY }}/${{ env.EAGLE_IMAGE }}:${{ steps.version.outputs.version }} ${{ env.REGISTRY }}/${{ env.EAGLE_IMAGE }}:latest
-
-      - name: Push to registry
-        run: |
-          echo "${{ secrets.DO_REGISTRY_TOKEN }}" | docker login ${{ env.REGISTRY }} -u ${{ secrets.DO_REGISTRY_TOKEN }} --password-stdin
-          docker push ${{ env.REGISTRY }}/${{ env.EAGLE_IMAGE }}:${{ steps.version.outputs.version }}
-          docker push ${{ env.REGISTRY }}/${{ env.EAGLE_IMAGE }}:latest
-
-  build-shardok:
-    runs-on: ubuntu-latest
-    needs: []
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          lfs: false
-
-      - name: Set version
-        id: version
-        run: echo "version=$(git rev-parse --short HEAD)" >> $GITHUB_OUTPUT
-
-      - name: Set up Bazel
-        uses: bazelbuild/setup-bazelisk@v2
-
-      - name: Cache Bazel
-        uses: actions/cache@v3
-        with:
-          path: ~/.cache/bazel
-          key: bazel-linux-${{ hashFiles('MODULE.bazel', 'WORKSPACE') }}
-
-      - name: Build Shardok server
-        run: bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server
-
-      - name: Build Docker image
-        run: |
-          mkdir -p bazel-bin/src/main/cpp/net/eagle0/shardok/
-          cp bazel-bin/src/main/cpp/net/eagle0/shardok/shardok-server bazel-bin/src/main/cpp/net/eagle0/shardok/
-          docker build -f ci/shardok_run.Dockerfile -t ${{ env.REGISTRY }}/${{ env.SHARDOK_IMAGE }}:${{ steps.version.outputs.version }} .
-          docker tag ${{ env.REGISTRY }}/${{ env.SHARDOK_IMAGE }}:${{ steps.version.outputs.version }} ${{ env.REGISTRY }}/${{ env.SHARDOK_IMAGE }}:latest
-
-      - name: Push to registry
-        run: |
-          echo "${{ secrets.DO_REGISTRY_TOKEN }}" | docker login ${{ env.REGISTRY }} -u ${{ secrets.DO_REGISTRY_TOKEN }} --password-stdin
-          docker push ${{ env.REGISTRY }}/${{ env.SHARDOK_IMAGE }}:${{ steps.version.outputs.version }}
-          docker push ${{ env.REGISTRY }}/${{ env.SHARDOK_IMAGE }}:latest
-
-  deploy:
-    runs-on: ubuntu-latest
-    needs: [build-eagle, build-shardok]
-    environment: production
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Deploy to DigitalOcean
-        uses: appleboy/ssh-action@v1.0.0
-        with:
-          host: ${{ secrets.DO_DROPLET_IP }}
-          username: deploy
-          key: ${{ secrets.DO_SSH_KEY }}
-          script: |
-            cd /opt/eagle0
-
-            # Pull latest images
-            docker-compose -f docker-compose.prod.yml pull
-
-            # Rolling restart (zero-downtime if load balancer configured)
-            docker-compose -f docker-compose.prod.yml up -d --remove-orphans
-
-            # Wait for health checks
-            sleep 30
-            docker-compose -f docker-compose.prod.yml ps
-
-            # Cleanup old images
-            docker image prune -f
-
-      - name: Verify deployment
-        run: |
-          # Health check endpoint
-          curl -f https://eagle0.net/health || exit 1
-
-      - name: Notify on failure
-        if: failure()
-        run: |
-          # Add Slack/Discord notification here
-          echo "Deployment failed!"
-```
-
-### Deployment Steps
-
-1. **On push to main:**
-   - Build Eagle JAR (self-hosted Mac runner - for consistency)
-   - Build Shardok binary (GitHub-hosted Ubuntu runner)
-   - Build Docker images
-   - Push to DigitalOcean Container Registry
-
-2. **Deploy to droplet:**
-   - SSH to production server
-   - Pull new images
-   - `docker-compose up -d` (rolling update)
-   - Verify health checks
-
-3. **Rollback:**
-   ```bash
-   # On server
-   docker-compose -f docker-compose.prod.yml down
-   docker-compose -f docker-compose.prod.yml pull eagle0/eagle-server:<previous-version>
-   docker-compose -f docker-compose.prod.yml up -d
-   ```
-
----
-
-## Server Setup
-
-### Initial Droplet Setup
-
-```bash
-#!/bin/bash
-# Run on fresh DigitalOcean droplet (Ubuntu 22.04)
-
-# Update system
-apt-get update && apt-get upgrade -y
-
-# Install Docker
-curl -fsSL https://get.docker.com | sh
-systemctl enable docker
-systemctl start docker
-
-# Install Docker Compose
-apt-get install -y docker-compose-plugin
-
-# Create deploy user
-useradd -m -s /bin/bash -G docker deploy
-mkdir -p /home/deploy/.ssh
-# Add your SSH public key to /home/deploy/.ssh/authorized_keys
-
-# Create app directory
-mkdir -p /opt/eagle0
-chown deploy:deploy /opt/eagle0
-
-# Configure Docker to use DigitalOcean Container Registry
-docker login registry.digitalocean.com
-
-# Create systemd service for auto-start
-cat > /etc/systemd/system/eagle0.service << 'EOF'
-[Unit]
-Description=Eagle0 Game Servers
-Requires=docker.service
-After=docker.service
-
-[Service]
-Type=oneshot
-RemainAfterExit=yes
-WorkingDirectory=/opt/eagle0
-ExecStart=/usr/bin/docker compose -f docker-compose.prod.yml up -d
-ExecStop=/usr/bin/docker compose -f docker-compose.prod.yml down
-User=deploy
-Group=deploy
-
-[Install]
-WantedBy=multi-user.target
-EOF
-
-systemctl enable eagle0
-```
-
-### Load Balancer Configuration
-
-**DigitalOcean Load Balancer settings:**
-
-- **Forwarding Rules:**
-  - HTTPS 443 → HTTP 40032 (Eagle)
-  - gRPC is HTTP/2, handled automatically
-
-- **Health Checks:**
-  - Protocol: HTTP
-  - Port: 40032
-  - Path: `/health` (need to implement)
-
-- **SSL:**
-  - Let's Encrypt certificate for `eagle0.net`
-
-- **Settings:**
-  - Sticky sessions: Disabled (gRPC streams handle this)
-  - Proxy protocol: Disabled
-
-### nginx on Droplet (Alternative to LB)
-
-If using nginx instead of managed LB:
-
-```nginx
-# /etc/nginx/sites-available/eagle0
-upstream eagle_backend {
-    server 127.0.0.1:40032;
-    keepalive 100;
-}
-
-server {
-    listen 443 ssl http2;
-    server_name eagle0.net;
-
-    ssl_certificate /etc/letsencrypt/live/eagle0.net/fullchain.pem;
-    ssl_certificate_key /etc/letsencrypt/live/eagle0.net/privkey.pem;
-
-    # gRPC settings
-    location /net.eagle0.eagle.api.Eagle {
-        grpc_pass grpc://eagle_backend;
-        grpc_read_timeout 1200s;
-        grpc_send_timeout 1200s;
-        grpc_socket_keepalive on;
-
-        # Rate limiting
-        limit_req zone=eagle burst=50 nodelay;
-    }
-
-    # Health check endpoint
-    location /health {
-        proxy_pass http://127.0.0.1:40032/health;
-    }
-}
-
-# Rate limit zone
-limit_req_zone $binary_remote_addr zone=eagle:10m rate=100r/s;
-```
-
----
-
-## Environment Configuration
-
-### Secrets Management
-
-**GitHub Secrets (for CI/CD):**
-- `DO_REGISTRY_TOKEN` - DigitalOcean Container Registry token
-- `DO_DROPLET_IP` - Production server IP
-- `DO_SSH_KEY` - SSH private key for deployment
-- `OPENAI_API_KEY` - For LLM integration (if used in production)
-- `DO_SPACES_KEY` - Already exists for S3
-
-**On Server (environment variables):**
-```bash
-# /opt/eagle0/.env
-GPT_MODEL_NAME=gpt-4
-OPENAI_API_KEY=sk-...
-DO_SPACES_KEY=...
-DO_SPACES_SECRET=...
-JAVA_OPTS=-Xmx4g -XX:+UseG1GC -XX:MaxGCPauseMillis=200
-```
-
-### Configuration Files
-
-**Production config** (`/opt/eagle0/config/eagle0.conf`):
-```
-monteCarloIterations = 150000
-monteCarloThreads = 4
-grpcAddress = 0.0.0.0:40042
-```
-
----
-
-## Monitoring & Observability
-
-### Logging
-
-**Docker logging driver:** json-file with rotation
-- Logs stored in `/var/lib/docker/containers/<id>/`
-- Max 5 files of 100MB each
-
-**Log aggregation options:**
-1. **DigitalOcean Logs** - $0 for basic, integrates with Droplets
-2. **Papertrail** - $7/mo for 1GB, good search
-3. **Self-hosted Loki** - Free, more complex
-
-### Metrics
-
-**Prometheus + Grafana** (optional, for advanced monitoring):
-```yaml
-# Add to docker-compose.prod.yml
-  prometheus:
-    image: prom/prometheus
-    volumes:
-      - ./prometheus.yml:/etc/prometheus/prometheus.yml
-    ports:
-      - "9090:9090"
-
-  grafana:
-    image: grafana/grafana
-    ports:
-      - "3000:3000"
-    environment:
-      - GF_SECURITY_ADMIN_PASSWORD=${GRAFANA_PASSWORD}
-```
-
-**Key metrics to track:**
-- Connection count
-- Request latency (p50, p95, p99)
-- Error rate
-- CPU/memory usage
-- Shardok AI search depth/time
-
-### Alerting
-
-**DigitalOcean Monitoring Alerts:**
-- CPU > 80% for 5 minutes
-- Memory > 90%
-- Disk > 85%
-- Droplet unreachable
-
-**Uptime monitoring:**
-- Use UptimeRobot (free tier) or Better Uptime
-- Check `https://eagle0.net/health` every minute
-
----
-
-## Cost Estimate
-
-### Recommended Starting Configuration
-
-| Component | Monthly Cost | Notes |
-|-----------|-------------|-------|
-| Droplet (s-2vcpu-4gb) | $24 | Eagle always-on, Shardok on-demand |
-| Spaces | ~$5 | Already paying |
-| Container Registry | $5 | For Docker images |
-| DNS | $0 | Included |
-| Bandwidth | ~$0 | 1TB free, then $0.01/GB |
-| **Total** | **~$34/mo** | |
-
-### Optional Add-ons
-
-| Component | Monthly Cost | Notes |
-|-----------|-------------|-------|
-| Load Balancer | +$12 | Only if need HA/failover |
-| Monitoring (Papertrail) | +$7 | Better log search |
-
-### Scaling Costs
-
-| Scenario | Droplet | Monthly Cost |
-|----------|---------|--------------|
-| Current (few players) | s-2vcpu-4gb | $24 |
-| Growing usage | s-4vcpu-8gb | $48 |
-| CPU-intensive battles | c-4 (dedicated) | $84 |
-| High concurrency | c-8 (dedicated) | $168 |
-| Separate Shardok (on-demand) | s-1vcpu-2gb + c-4 hourly | $12 + usage |
-
----
-
-## Migration Plan
-
-### Phase 1: Infrastructure Setup (Day 1)
-
-1. Create DigitalOcean resources:
-   - Droplet in SFO3 region
-   - Container Registry
-   - (Optional) Load Balancer
-
-2. Configure DNS:
-   - Point `eagle0.net` to new infrastructure
-   - Keep `qa.eagle0.net` pointing to home IP
-
-3. Set up server:
-   - Run initial setup script
-   - Configure Docker and docker-compose
-   - Test SSH access
-
-### Phase 2: Build Pipeline (Day 2)
-
-1. Create Dockerfiles:
-   - Enhance `ci/eagle_run.Dockerfile`
-   - Create `ci/shardok_run.Dockerfile`
-
-2. Create `docker-compose.prod.yml`
-
-3. Set up GitHub Actions:
-   - Add deployment workflow
-   - Configure secrets
-   - Test build pipeline
-
-### Phase 3: Deployment (Day 3)
-
-1. Deploy to production:
-   - Push first images
-   - Start containers
-   - Verify health checks
-
-2. Configure TLS:
-   - Set up Let's Encrypt
-   - Update nginx/LB configuration
-
-3. Update DNS:
-   - Switch `eagle0.net` to production
-   - Verify client can connect
-
-### Phase 4: Validation (Day 4)
-
-1. Test gameplay:
-   - Connect from Unity client
-   - Play through Eagle gameplay
-   - Test Shardok combat
-
-2. Monitor:
-   - Check logs for errors
-   - Verify resource usage
-   - Test reconnection behavior
-
-3. Document:
-   - Update runbooks
-   - Document rollback procedures
-
-### Phase 5: QA Environment (Day 5)
-
-1. Configure `qa.eagle0.net`:
-   - Keep pointing to home Mac
-   - Ensure nginx routes correctly
-
-2. Test environment switching:
-   - Connect to production
-   - Switch to QA
-   - Verify different game states
-
----
-
-## Rollback Procedure
-
-### Quick Rollback (< 5 minutes)
-
-```bash
-# SSH to production server
-ssh deploy@<droplet-ip>
-
-# Roll back to previous version
-cd /opt/eagle0
-docker-compose -f docker-compose.prod.yml down
-docker pull registry.digitalocean.com/eagle0/eagle-server:<previous-tag>
-docker pull registry.digitalocean.com/eagle0/shardok-server:<previous-tag>
-VERSION=<previous-tag> docker-compose -f docker-compose.prod.yml up -d
-```
-
-### Full Rollback to Home Mac
-
-1. Update DNS: Point `eagle0.net` back to home IP
-2. Ensure home Mac servers are running
-3. Wait for DNS propagation (5-30 minutes)
-
----
-
-## Security Checklist
-
-- [ ] SSH key authentication only (disable password)
-- [ ] Firewall configured (only 443, 22 from trusted IPs)
-- [ ] TLS 1.3 enforced
-- [ ] Secrets in environment variables, not in code
-- [ ] Container runs as non-root user
-- [ ] Rate limiting on gRPC endpoints
-- [ ] Regular security updates (`unattended-upgrades`)
-- [ ] Remove Shardok internal interface from public nginx (per CONNECTION_ARCHITECTURE.md)
-
----
-
-## Resolved Questions
-
-1. **Game state migration:** No migration needed. Saves are currently local only. The codebase has a `Persister` pattern (with existing AWS support) that could be adapted to save to DO Spaces in the future.
-
-2. **LLM API keys:** Yes, OpenAI API keys are needed on the Eagle server. Add `OPENAI_API_KEY` to the `.env` file on the production droplet.
-
-3. **Multiple regions:** Not needed for now. Single SFO3 region is sufficient.
-
-## Remaining Open Questions
-
-1. **Backup strategy:** Should we add automated backups for local persistence, or migrate to DO Spaces persistence first?
-
-2. **Autoscaling:** Is traffic predictable enough to use fixed instance, or need autoscaling later?
-
----
-
-## Next Steps
-
-### Phase 1: Infrastructure
-1. **Approve this plan** - Review and discuss any changes
-2. **Create DigitalOcean resources** - Droplet (s-2vcpu-4gb), Container Registry
-3. **Set up droplet** - Docker, deploy user, firewall, nginx with TLS
-
-### Phase 2: Containerization
-4. **Implement Dockerfiles** - Eagle and Shardok containers
-5. **Implement Shardok lifecycle management** - Eagle starts/stops Shardok on-demand
-   - Add `ShardokProcessManager` to Eagle server
-   - Start Shardok when battle requested
-   - Stop after idle timeout (5 min)
-   - Health check before routing traffic
-
-### Phase 3: CI/CD
-6. **Set up GitHub Actions** - Build and push Docker images
-7. **Add deployment workflow** - SSH deploy to droplet
-
-### Phase 4: Migration
-8. **Deploy to production** - Push images, start services
-9. **Update DNS** - Point eagle0.net to droplet
-10. **Validate** - Test gameplay, monitor logs
-11. **Configure QA** - Ensure qa.eagle0.net still works (home Mac)

go.mod

@@ -9,7 +9,6 @@ require (
 	github.com/aws/aws-sdk-go-v2/config v1.28.10
 	github.com/aws/aws-sdk-go-v2/credentials v1.17.51
 	github.com/aws/aws-sdk-go-v2/service/s3 v1.72.2
-	google.golang.org/grpc v1.68.0
 	google.golang.org/protobuf v1.36.3
 )
 

go.sum

@@ -40,8 +40,6 @@ github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/
 golang.org/x/text v0.25.0 h1:qVyWApTSYLk/drJRO5mDlNYskwQznZmkpV2c8q9zls4=
 golang.org/x/text v0.25.0/go.mod h1:WEdwpYrmk1qmdHvhkSTNPm3app7v4rsT8F2UD6+VHIA=
 golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
-google.golang.org/grpc v1.68.0 h1:aHQeeJbo8zAkAa3pRzrVjZlbz6uSfeOXlJNQM0RAbz0=
-google.golang.org/grpc v1.68.0/go.mod h1:fmSPC5AsjSBCK54MyHRx48kpOti1/jRfOlwEWywNjWA=
 google.golang.org/protobuf v1.26.0-rc.1 h1:7QnIQpGRHE5RnLKnESfDoxm2dTapTZua5a0kS0A+VXQ=
 google.golang.org/protobuf v1.26.0-rc.1/go.mod h1:jlhhOSvTdKEhbULTjvd4ARK9grFBp09yW+WbY/TyQbw=
 google.golang.org/protobuf v1.36.3 h1:82DV7MYdb8anAVi3qge1wSnMDrnKK7ebr+I0hHRN1BU=

maven_install.json

@@ -1,10 +1,9 @@
 {
   "__AUTOGENERATED_FILE_DO_NOT_MODIFY_THIS_FILE_MANUALLY": "THERE_IS_NO_DATA_ONLY_ZUUL",
-  "__INPUT_ARTIFACTS_HASH": 289080209,
-  "__RESOLVED_ARTIFACTS_HASH": -131178107,
+  "__INPUT_ARTIFACTS_HASH": 571423113,
+  "__RESOLVED_ARTIFACTS_HASH": 438039003,
   "conflict_resolution": {
     "com.google.guava:failureaccess:1.0.1": "com.google.guava:failureaccess:1.0.2",
-    "com.squareup.okio:okio:2.10.0": "com.squareup.okio:okio:3.6.0",
     "io.netty:netty-buffer:4.1.110.Final": "io.netty:netty-buffer:4.1.112.Final",
     "io.netty:netty-codec-http2:4.1.110.Final": "io.netty:netty-codec-http2:4.1.112.Final",
     "io.netty:netty-codec-http:4.1.110.Final": "io.netty:netty-codec-http:4.1.112.Final",
@@ -156,18 +155,6 @@
       },
       "version": "1.4.2"
     },
-    "com.squareup.okhttp3:okhttp": {
-      "shasums": {
-        "jar": "b1050081b14bb7a3a7e55a4d3ef01b5dcfabc453b4573a4fc019767191d5f4e0"
-      },
-      "version": "4.12.0"
-    },
-    "com.squareup.okhttp3:okhttp-sse": {
-      "shasums": {
-        "jar": "bff4fbcaef7aac2d910d4ff46dafaa4e6d15da127df6bac97216da46943a7d4c"
-      },
-      "version": "4.12.0"
-    },
     "com.squareup.okhttp:okhttp": {
       "shasums": {
         "jar": "88ac9fd1bb51f82bcc664cc1eb9c225c90dc4389d660231b4cc737bebfe7d0aa"
@@ -176,15 +163,9 @@
     },
     "com.squareup.okio:okio": {
       "shasums": {
-        "jar": "8e63292e5c53bb93c4a6b0c213e79f15990fed250c1340f1c343880e1c9c39b5"
+        "jar": "a27f091d34aa452e37227e2cfa85809f29012a8ef2501a9b5a125a978e4fcbc1"
       },
-      "version": "3.6.0"
-    },
-    "com.squareup.okio:okio-jvm": {
-      "shasums": {
-        "jar": "67543f0736fc422ae927ed0e504b98bc5e269fda0d3500579337cb713da28412"
-      },
-      "version": "3.6.0"
+      "version": "2.10.0"
     },
     "com.thesamet.scalapb:compilerplugin_3": {
       "shasums": {
@@ -463,27 +444,15 @@
     },
     "org.jetbrains.kotlin:kotlin-stdlib": {
       "shasums": {
-        "jar": "55e989c512b80907799f854309f3bc7782c5b3d13932442d0379d5c472711504"
+        "jar": "b8ab1da5cdc89cb084d41e1f28f20a42bd431538642a5741c52bbfae3fa3e656"
       },
-      "version": "1.9.10"
+      "version": "1.4.20"
     },
     "org.jetbrains.kotlin:kotlin-stdlib-common": {
       "shasums": {
-        "jar": "cde3341ba18a2ba262b0b7cf6c55b20c90e8d434e42c9a13e6a3f770db965a88"
+        "jar": "a7112c9b3cefee418286c9c9372f7af992bd1e6e030691d52f60cb36dbec8320"
       },
-      "version": "1.9.10"
-    },
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk7": {
-      "shasums": {
-        "jar": "ac6361bf9ad1ed382c2103d9712c47cdec166232b4903ed596e8876b0681c9b7"
-      },
-      "version": "1.9.10"
-    },
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk8": {
-      "shasums": {
-        "jar": "a4c74d94d64ce1abe53760fe0389dd941f6fc558d0dab35e47c085a11ec80f28"
-      },
-      "version": "1.9.10"
+      "version": "1.4.20"
     },
     "org.jetbrains:annotations": {
       "shasums": {
@@ -810,23 +779,12 @@
       "org.checkerframework:checker-qual",
       "org.ow2.asm:asm"
     ],
-    "com.squareup.okhttp3:okhttp": [
-      "com.squareup.okio:okio",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
-    ],
-    "com.squareup.okhttp3:okhttp-sse": [
-      "com.squareup.okhttp3:okhttp",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
-    ],
     "com.squareup.okhttp:okhttp": [
       "com.squareup.okio:okio"
     ],
     "com.squareup.okio:okio": [
-      "com.squareup.okio:okio-jvm"
-    ],
-    "com.squareup.okio:okio-jvm": [
-      "org.jetbrains.kotlin:kotlin-stdlib-common",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
+      "org.jetbrains.kotlin:kotlin-stdlib",
+      "org.jetbrains.kotlin:kotlin-stdlib-common"
     ],
     "com.thesamet.scalapb:compilerplugin_3": [
       "com.google.protobuf:protobuf-java",
@@ -1034,13 +992,6 @@
       "org.jetbrains.kotlin:kotlin-stdlib-common",
       "org.jetbrains:annotations"
     ],
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk7": [
-      "org.jetbrains.kotlin:kotlin-stdlib"
-    ],
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk8": [
-      "org.jetbrains.kotlin:kotlin-stdlib",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk7"
-    ],
     "org.json4s:json4s-ast_3": [
       "org.scala-lang:scala3-library_3"
     ],
@@ -1500,29 +1451,6 @@
     "com.google.truth:truth": [
       "com.google.common.truth"
     ],
-    "com.squareup.okhttp3:okhttp": [
-      "okhttp3",
-      "okhttp3.internal",
-      "okhttp3.internal.authenticator",
-      "okhttp3.internal.cache",
-      "okhttp3.internal.cache2",
-      "okhttp3.internal.concurrent",
-      "okhttp3.internal.connection",
-      "okhttp3.internal.http",
-      "okhttp3.internal.http1",
-      "okhttp3.internal.http2",
-      "okhttp3.internal.io",
-      "okhttp3.internal.platform",
-      "okhttp3.internal.platform.android",
-      "okhttp3.internal.proxy",
-      "okhttp3.internal.publicsuffix",
-      "okhttp3.internal.tls",
-      "okhttp3.internal.ws"
-    ],
-    "com.squareup.okhttp3:okhttp-sse": [
-      "okhttp3.internal.sse",
-      "okhttp3.sse"
-    ],
     "com.squareup.okhttp:okhttp": [
       "com.squareup.okhttp",
       "com.squareup.okhttp.internal",
@@ -1531,7 +1459,7 @@
       "com.squareup.okhttp.internal.io",
       "com.squareup.okhttp.internal.tls"
     ],
-    "com.squareup.okio:okio-jvm": [
+    "com.squareup.okio:okio": [
       "okio",
       "okio.internal"
     ],
@@ -1886,7 +1814,6 @@
       "kotlin.annotation",
       "kotlin.collections",
       "kotlin.collections.builders",
-      "kotlin.collections.jdk8",
       "kotlin.collections.unsigned",
       "kotlin.comparisons",
       "kotlin.concurrent",
@@ -1895,36 +1822,24 @@
       "kotlin.coroutines.cancellation",
       "kotlin.coroutines.intrinsics",
       "kotlin.coroutines.jvm.internal",
-      "kotlin.enums",
       "kotlin.experimental",
       "kotlin.internal",
-      "kotlin.internal.jdk7",
-      "kotlin.internal.jdk8",
       "kotlin.io",
-      "kotlin.io.encoding",
-      "kotlin.io.path",
-      "kotlin.jdk7",
       "kotlin.js",
       "kotlin.jvm",
       "kotlin.jvm.functions",
       "kotlin.jvm.internal",
       "kotlin.jvm.internal.markers",
       "kotlin.jvm.internal.unsafe",
-      "kotlin.jvm.jdk8",
-      "kotlin.jvm.optionals",
       "kotlin.math",
       "kotlin.properties",
       "kotlin.random",
-      "kotlin.random.jdk8",
       "kotlin.ranges",
       "kotlin.reflect",
       "kotlin.sequences",
-      "kotlin.streams.jdk8",
       "kotlin.system",
       "kotlin.text",
-      "kotlin.text.jdk8",
-      "kotlin.time",
-      "kotlin.time.jdk8"
+      "kotlin.time"
     ],
     "org.jetbrains:annotations": [
       "org.intellij.lang.annotations",
@@ -2355,11 +2270,8 @@
       "com.google.protobuf:protobuf-java",
       "com.google.re2j:re2j",
       "com.google.truth:truth",
-      "com.squareup.okhttp3:okhttp",
-      "com.squareup.okhttp3:okhttp-sse",
       "com.squareup.okhttp:okhttp",
       "com.squareup.okio:okio",
-      "com.squareup.okio:okio-jvm",
       "com.thesamet.scalapb:compilerplugin_3",
       "com.thesamet.scalapb:lenses_3",
       "com.thesamet.scalapb:protoc-bridge_2.13",
@@ -2412,8 +2324,6 @@
       "org.hamcrest:hamcrest-core",
       "org.jetbrains.kotlin:kotlin-stdlib",
       "org.jetbrains.kotlin:kotlin-stdlib-common",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk7",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8",
       "org.jetbrains:annotations",
       "org.json4s:json4s-ast_3",
       "org.json4s:json4s-core_3",

scripts/build_mac_plugin.sh

@@ -3,8 +3,7 @@
 set -euxo pipefail
 
 /bin/echo "building darwin bundle"
-bazel build --config=mactools @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
-ZIP_LOCATION=$(bazel cquery --config=mactools --output=files @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle 2>/dev/null)
-/usr/bin/unzip -o $ZIP_LOCATION -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
+bazel build --noincompatible_enable_cc_toolchain_resolution @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
+/usr/bin/unzip -o bazel-bin/external/net_eagle0_unity_godice/darwin/framework/DarwinGodiceBundle.zip -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
 
 /usr/bin/plutil -convert xml1 src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/DarwinGodiceBundle.bundle/Contents/Info.plist

scripts/build_plugins.sh

@@ -5,9 +5,8 @@ set -euxo pipefail
 /bin/echo "build plugins"
 
 /bin/echo "building darwin bundle"
-bazel build --config=mactools @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
-ZIP_LOCATION=$(bazel cquery --config=mactools --output=files @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle 2>/dev/null)
-/usr/bin/unzip -o $ZIP_LOCATION -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
+bazel build --noincompatible_enable_cc_toolchain_resolution @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
+/usr/bin/unzip -o bazel-bin/external/net_eagle0_unity_godice/darwin/framework/DarwinGodiceBundle.zip -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
 
 /usr/bin/plutil -convert xml1 src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/DarwinGodiceBundle.bundle/Contents/Info.plist
 

scripts/dlSettings.sh

@@ -1,10 +1,8 @@
 #!/usr/bin/env bash
 
-curl -L "https://docs.google.com/spreadsheets/d/1pv-WMXReccddPwev_YG9IXEGznuGHrYjNNEZ0Rb-ZhM/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/shardok/settings.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1p6I5nUMcoAPHIcqikVgbBCFVnqN9dpOEVClbS_wOI7M/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/settings.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1pv-WMXReccddPwev_YG9IXEGznuGHrYjNNEZ0Rb-ZhM/export?gid=0&format=tsv" > src/main/resources/net/eagle0/shardok/settings.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1p6I5nUMcoAPHIcqikVgbBCFVnqN9dpOEVClbS_wOI7M/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/settings.tsv
 
 bazel run //src/main/go/net/eagle0/build/settings_generator:settings_generator -- \
     ${PWD}/src/main/resources/net/eagle0/eagle/settings.tsv \
     ${PWD}/src/main/scala/net/eagle0/eagle/library/settings/
-bazel run gazelle
-

scripts/downloadTsvs.sh

@@ -1,11 +1,11 @@
 #!/usr/bin/env bash
 
-curl -L "https://docs.google.com/spreadsheets/d/1DHEsiv4cY4gE6AX3sVH82K__mpBD1aznIYCQwQxA_F0/export?gid=0&format=tsv" | tr -d '\r' > /tmp/names.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1DHEsiv4cY4gE6AX3sVH82K__mpBD1aznIYCQwQxA_F0/export?gid=0&format=tsv" > /tmp/names.tsv
 bazel run //src/main/scala/net/eagle0/util:name_list_checker -- /tmp/names.tsv > src/main/resources/net/eagle0/names.tsv
 bazel run //src/main/scala/net/eagle0/util:name_list_json_maker -- /tmp/names.tsv > src/main/resources/net/eagle0/names.json
-curl -L "https://docs.google.com/spreadsheets/d/1NhvG73HKyVE36yGpkV2oJiSIXoNqQOYTr5ArLnucYL0/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/shardok/battalionTypes.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1pNWiyxIks2wJ1v7jRLFD24zrKHG2AfhC-nkWmQKQGN4/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/heroes.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1RUguq5eAQprsZwOOqiCc-1dg4Urc_6iJ6awZsFU4MeI/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/beasts.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1NhvG73HKyVE36yGpkV2oJiSIXoNqQOYTr5ArLnucYL0/export?gid=0&format=tsv" > src/main/resources/net/eagle0/shardok/battalionTypes.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1pNWiyxIks2wJ1v7jRLFD24zrKHG2AfhC-nkWmQKQGN4/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/heroes.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1RUguq5eAQprsZwOOqiCc-1dg4Urc_6iJ6awZsFU4MeI/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/beasts.tsv
 #curl -L "https://docs.google.com/spreadsheets/d/1Z-60cJ_N1IasvqpVb5awKEkIYznEeR2IZSdli47oW88/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/province_map.tsv
 
 ${PWD}/scripts/dlSettings.sh

scripts/generate_changelog.sh

@@ -1,473 +0,0 @@
-#!/bin/bash
-#
-# generate_changelog.sh
-#
-# Generates a weekly changelog from merged PRs, uses Claude to create a synopsis,
-# and sends an HTML email via Fastmail JMAP API.
-#
-# Usage: ./scripts/generate_changelog.sh [--dry-run]
-#
-# Configuration files (in ~/.config/eagle0/):
-#   fastmail_token      - API token (required)
-#   changelog_recipient - Email addresses, one per line (optional, defaults to sender)
-#
-# To set up:
-#   mkdir -p ~/.config/eagle0
-#   echo 'your-token' > ~/.config/eagle0/fastmail_token
-#   chmod 600 ~/.config/eagle0/fastmail_token
-#
-#   # Optional: configure recipients (one per line, # for comments)
-#   cat > ~/.config/eagle0/changelog_recipient << EOF
-#   alice@example.com
-#   bob@example.com
-#   EOF
-#
-# The script tracks its last run using a git tag 'changelog-last-run'.
-# On first run (no tag), it defaults to the previous Friday at 4pm.
-
-set -euo pipefail
-
-# Ensure homebrew binaries are in PATH
-export PATH="/opt/homebrew/bin:$PATH"
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-REPO_ROOT="$(cd "$SCRIPT_DIR/.." && pwd)"
-TAG_NAME="changelog-last-run"
-DRY_RUN=false
-FASTMAIL_API="https://api.fastmail.com/jmap/api/"
-CONFIG_DIR="$HOME/.config/eagle0"
-TOKEN_FILE="$CONFIG_DIR/fastmail_token"
-RECIPIENT_FILE="$CONFIG_DIR/changelog_recipient"
-
-# Load API token from file or environment
-load_api_token() {
-    # Environment variable takes precedence
-    if [[ -n "${FASTMAIL_API_TOKEN:-}" ]]; then
-        return 0
-    fi
-
-    # Try loading from config file
-    if [[ -f "$TOKEN_FILE" ]]; then
-        FASTMAIL_API_TOKEN=$(cat "$TOKEN_FILE" | tr -d '[:space:]')
-        if [[ -n "$FASTMAIL_API_TOKEN" ]]; then
-            echo "Loaded API token from $TOKEN_FILE"
-            export FASTMAIL_API_TOKEN
-            return 0
-        fi
-    fi
-
-    return 1
-}
-
-# Load recipient emails from config file (one per line)
-# Returns JSON array fragment like: {"email": "a@b.com"}, {"email": "c@d.com"}
-load_recipients_json() {
-    local recipients=""
-    if [[ -f "$RECIPIENT_FILE" ]]; then
-        while IFS= read -r line || [[ -n "$line" ]]; do
-            # Skip empty lines and comments
-            line=$(echo "$line" | tr -d '[:space:]')
-            [[ -z "$line" || "$line" == \#* ]] && continue
-
-            if [[ -n "$recipients" ]]; then
-                recipients="$recipients, "
-            fi
-            recipients="$recipients{\"email\": \"$line\"}"
-        done < "$RECIPIENT_FILE"
-    fi
-    echo "$recipients"
-}
-
-# Get human-readable list of recipients
-load_recipients_display() {
-    if [[ -f "$RECIPIENT_FILE" ]]; then
-        grep -v '^#' "$RECIPIENT_FILE" | grep -v '^[[:space:]]*$' | tr '\n' ', ' | sed 's/, $//'
-    fi
-}
-
-# Parse arguments
-while [[ $# -gt 0 ]]; do
-    case $1 in
-        --dry-run)
-            DRY_RUN=true
-            shift
-            ;;
-        *)
-            echo "Unknown option: $1"
-            echo "Usage: $0 [--dry-run]"
-            exit 1
-            ;;
-    esac
-done
-
-cd "$REPO_ROOT"
-
-# Get the cutoff date - either from tag or previous Friday 4pm
-get_cutoff_date() {
-    # Try to get the date from the tag
-    if git rev-parse "$TAG_NAME" >/dev/null 2>&1; then
-        # Get the commit date of the tagged commit
-        git log -1 --format="%aI" "$TAG_NAME"
-    else
-        # Calculate previous Friday at 4pm
-        # Get current day of week (1=Monday, 7=Sunday)
-        local dow=$(date +%u)
-        local days_since_friday
-
-        if [[ $dow -ge 5 ]]; then
-            # Friday (5), Saturday (6), or Sunday (7)
-            days_since_friday=$((dow - 5))
-        else
-            # Monday (1) through Thursday (4)
-            days_since_friday=$((dow + 2))
-        fi
-
-        # Get previous Friday at 4pm in ISO format
-        if [[ "$(uname)" == "Darwin" ]]; then
-            date -v-"${days_since_friday}d" -v16H -v0M -v0S +"%Y-%m-%dT%H:%M:%S%z"
-        else
-            date -d "$days_since_friday days ago 16:00:00" --iso-8601=seconds
-        fi
-    fi
-}
-
-# Fetch merged PRs since the cutoff date
-fetch_merged_prs() {
-    local since_date="$1"
-    local output_file="$2"
-
-    echo "Fetching PRs merged since: $since_date"
-
-    # Use gh to search for merged PRs
-    gh pr list \
-        --state merged \
-        --base main \
-        --json number,title,body,mergedAt,author \
-        --jq ".[] | select(.mergedAt >= \"$since_date\")" \
-        > "$output_file.json"
-
-    # Format the output nicely
-    echo "# Merged PRs since $since_date" > "$output_file"
-    echo "" >> "$output_file"
-
-    # Process each PR
-    jq -r '
-        "## PR #\(.number): \(.title)\n" +
-        "Author: \(.author.login)\n" +
-        "Merged: \(.mergedAt)\n\n" +
-        "### Description\n" +
-        (.body // "(No description)") +
-        "\n\n---\n"
-    ' "$output_file.json" >> "$output_file"
-
-    # Count PRs
-    local pr_count=$(jq -s 'length' "$output_file.json")
-    echo "Found $pr_count merged PRs"
-
-    rm -f "$output_file.json"
-
-    if [[ $pr_count -eq 0 ]]; then
-        echo "No PRs found since $since_date"
-        return 1
-    fi
-
-    return 0
-}
-
-# Generate synopsis using Claude
-generate_synopsis() {
-    local input_file="$1"
-    local output_file="$2"
-
-    echo "Generating synopsis with Claude..."
-
-    # Create a prompt file to avoid shell escaping issues
-    local prompt_file="/tmp/eagle0_prompt_$$.txt"
-    # Get repo URL for PR links
-    local repo_url=$(gh repo view --json url -q '.url')
-
-    cat > "$prompt_file" <<PROMPT_HEADER
-You are summarizing changes for a weekly engineering update email.
-
-Read the following list of merged PRs and create a concise synopsis grouped by theme/feature/area of the codebase.
-
-Structure:
-1. <h1> title (e.g., "Eagle0 Weekly Update")
-2. <h2>BLUF</h2> (Bottom Line Up Front) - A short prose paragraph (2-4 sentences) highlighting the 1-3 most important changes this week and what to look for when testing. This should be conversational and help readers quickly understand what matters most.
-3. Synopsis sections (<h2> headings with bullet point summaries)
-4. <hr> divider
-5. <h2>PR Details</h2> with the same groupings, but smaller (<h3> headings) and listing PR links
-   - Format each PR as: <a href="${repo_url}/pull/NUMBER">#NUMBER</a>: Title
-
-Guidelines for the SYNOPSIS sections:
-- Group related changes together under clear headings (use <h2> tags)
-- Use bullet points (<ul><li>) for individual changes
-- Highlight any significant new features, breaking changes, or important fixes
-- Keep the tone professional but accessible
-- Don't include PR numbers in the synopsis - focus on what changed and why it matters
-
-IMPORTANT: Output valid HTML that can be used directly in an email body. Do NOT wrap in \`\`\`html code blocks - just output the raw HTML.
-
-Here are the merged PRs:
-
-PROMPT_HEADER
-
-    cat "$input_file" >> "$prompt_file"
-    echo "" >> "$prompt_file"
-    echo "Generate the synopsis now:" >> "$prompt_file"
-
-    # Use Claude CLI to generate the synopsis, wrapped in proper HTML with charset
-    local raw_output="/tmp/eagle0_raw_$$.html"
-    cat "$prompt_file" | claude --print > "$raw_output"
-
-    # Wrap in HTML document with UTF-8 charset
-    cat > "$output_file" <<'HTML_HEAD'
-<!DOCTYPE html>
-<html>
-<head>
-<meta charset="utf-8">
-</head>
-<body>
-HTML_HEAD
-    cat "$raw_output" >> "$output_file"
-    echo "</body></html>" >> "$output_file"
-
-    rm -f "$prompt_file" "$raw_output"
-    echo "Synopsis generated at: $output_file"
-}
-
-# Get Fastmail session info (account ID, identity ID, drafts mailbox ID)
-get_fastmail_session() {
-    echo "Fetching Fastmail session info..." >&2
-
-    # Get session
-    local session=$(curl -s \
-        -H "Authorization: Bearer $FASTMAIL_API_TOKEN" \
-        "https://api.fastmail.com/jmap/session")
-
-    # Extract account ID (first account)
-    FASTMAIL_ACCOUNT_ID=$(echo "$session" | jq -r '.primaryAccounts["urn:ietf:params:jmap:mail"]')
-
-    if [[ -z "$FASTMAIL_ACCOUNT_ID" || "$FASTMAIL_ACCOUNT_ID" == "null" ]]; then
-        echo "Error: Could not get Fastmail account ID. Check your API token." >&2
-        return 1
-    fi
-    echo "Account ID: $FASTMAIL_ACCOUNT_ID" >&2
-
-    # Get identity ID
-    local identity_response=$(curl -s \
-        -H "Authorization: Bearer $FASTMAIL_API_TOKEN" \
-        -H "Content-Type: application/json" \
-        -X POST \
-        -d "{
-            \"using\": [\"urn:ietf:params:jmap:core\", \"urn:ietf:params:jmap:mail\", \"urn:ietf:params:jmap:submission\"],
-            \"methodCalls\": [
-                [\"Identity/get\", {\"accountId\": \"$FASTMAIL_ACCOUNT_ID\"}, \"0\"]
-            ]
-        }" \
-        "$FASTMAIL_API")
-
-    FASTMAIL_IDENTITY_ID=$(echo "$identity_response" | jq -r '.methodResponses[0][1].list[0].id')
-    FASTMAIL_FROM_EMAIL=$(echo "$identity_response" | jq -r '.methodResponses[0][1].list[0].email')
-
-    if [[ -z "$FASTMAIL_IDENTITY_ID" || "$FASTMAIL_IDENTITY_ID" == "null" ]]; then
-        echo "Error: Could not get Fastmail identity ID." >&2
-        return 1
-    fi
-    echo "Identity ID: $FASTMAIL_IDENTITY_ID (${FASTMAIL_FROM_EMAIL})" >&2
-
-    # Get drafts mailbox ID
-    local mailbox_response=$(curl -s \
-        -H "Authorization: Bearer $FASTMAIL_API_TOKEN" \
-        -H "Content-Type: application/json" \
-        -X POST \
-        -d "{
-            \"using\": [\"urn:ietf:params:jmap:core\", \"urn:ietf:params:jmap:mail\"],
-            \"methodCalls\": [
-                [\"Mailbox/query\", {\"accountId\": \"$FASTMAIL_ACCOUNT_ID\", \"filter\": {\"role\": \"drafts\"}}, \"0\"]
-            ]
-        }" \
-        "$FASTMAIL_API")
-
-    FASTMAIL_DRAFTS_ID=$(echo "$mailbox_response" | jq -r '.methodResponses[0][1].ids[0]')
-
-    if [[ -z "$FASTMAIL_DRAFTS_ID" || "$FASTMAIL_DRAFTS_ID" == "null" ]]; then
-        echo "Error: Could not get Fastmail drafts mailbox ID." >&2
-        return 1
-    fi
-    echo "Drafts mailbox ID: $FASTMAIL_DRAFTS_ID" >&2
-
-    return 0
-}
-
-# Send email via Fastmail JMAP API
-send_email_fastmail() {
-    local synopsis_file="$1"
-    local recipients_json="$2"  # JSON array fragment: {"email": "a@b.com"}, {"email": "c@d.com"}
-
-    local subject="Eagle0 Weekly Changelog - $(date +%Y-%m-%d)"
-    local html_body=$(cat "$synopsis_file" | jq -Rs .)
-
-    echo "Sending email via Fastmail JMAP API..."
-
-    # Create the email and send it in one request
-    local response=$(curl -s \
-        -H "Authorization: Bearer $FASTMAIL_API_TOKEN" \
-        -H "Content-Type: application/json" \
-        -X POST \
-        -d "{
-            \"using\": [
-                \"urn:ietf:params:jmap:core\",
-                \"urn:ietf:params:jmap:mail\",
-                \"urn:ietf:params:jmap:submission\"
-            ],
-            \"methodCalls\": [
-                [\"Email/set\", {
-                    \"accountId\": \"$FASTMAIL_ACCOUNT_ID\",
-                    \"create\": {
-                        \"draft\": {
-                            \"from\": [{\"email\": \"$FASTMAIL_FROM_EMAIL\"}],
-                            \"to\": [$recipients_json],
-                            \"subject\": \"$subject\",
-                            \"mailboxIds\": {\"$FASTMAIL_DRAFTS_ID\": true},
-                            \"keywords\": {\"\$draft\": true},
-                            \"htmlBody\": [{\"partId\": \"body\", \"type\": \"text/html\"}],
-                            \"bodyValues\": {
-                                \"body\": {
-                                    \"charset\": \"utf-8\",
-                                    \"value\": $html_body
-                                }
-                            }
-                        }
-                    }
-                }, \"0\"],
-                [\"EmailSubmission/set\", {
-                    \"accountId\": \"$FASTMAIL_ACCOUNT_ID\",
-                    \"onSuccessDestroyEmail\": [\"#sendIt\"],
-                    \"create\": {
-                        \"sendIt\": {
-                            \"emailId\": \"#draft\",
-                            \"identityId\": \"$FASTMAIL_IDENTITY_ID\"
-                        }
-                    }
-                }, \"1\"]
-            ]
-        }" \
-        "$FASTMAIL_API")
-
-    # Check for errors
-    local error=$(echo "$response" | jq -r '.methodResponses[0][1].notCreated.draft.description // empty')
-    if [[ -n "$error" ]]; then
-        echo "Error creating email: $error" >&2
-        echo "Full response: $response" >&2
-        return 1
-    fi
-
-    local send_error=$(echo "$response" | jq -r '.methodResponses[1][1].notCreated.sendIt.description // empty')
-    if [[ -n "$send_error" ]]; then
-        echo "Error sending email: $send_error" >&2
-        echo "Full response: $response" >&2
-        return 1
-    fi
-
-    echo "Email sent successfully"
-}
-
-# Update the tag to mark this run
-update_tag() {
-    echo "Updating $TAG_NAME tag..."
-
-    # Delete existing tag if present
-    git tag -d "$TAG_NAME" 2>/dev/null || true
-    git push origin --delete "$TAG_NAME" 2>/dev/null || true
-
-    # Create new tag at HEAD
-    git tag "$TAG_NAME"
-    git push origin "$TAG_NAME"
-
-    echo "Tag updated to current HEAD"
-}
-
-# Main
-main() {
-    echo "=== Eagle0 Weekly Changelog Generator ==="
-    echo ""
-
-    # Load API token (only required for actual send)
-    if [[ "$DRY_RUN" != "true" ]]; then
-        if ! load_api_token; then
-            echo "Error: No Fastmail API token found."
-            echo ""
-            echo "To create a token:"
-            echo "1. Go to Fastmail Settings -> Password & Security -> API tokens"
-            echo "2. Create a new token with 'Email submission' scope"
-            echo "3. Save it using one of these methods:"
-            echo ""
-            echo "   Option A (recommended): Store in config file"
-            echo "     mkdir -p ~/.config/eagle0"
-            echo "     echo 'your-token' > ~/.config/eagle0/fastmail_token"
-            echo "     chmod 600 ~/.config/eagle0/fastmail_token"
-            echo ""
-            echo "   Option B: Set environment variable"
-            echo "     export FASTMAIL_API_TOKEN='your-token'"
-            exit 1
-        fi
-    fi
-
-    # Get cutoff date
-    local cutoff_date=$(get_cutoff_date)
-    echo "Cutoff date: $cutoff_date"
-
-    # Create temp files
-    local pr_file="/tmp/eagle0_prs_$(date +%s).md"
-    local synopsis_file="/tmp/eagle0_synopsis_$(date +%s).html"
-
-    # Fetch PRs
-    if ! fetch_merged_prs "$cutoff_date" "$pr_file"; then
-        echo "No changes to report. Exiting."
-        exit 0
-    fi
-
-    echo ""
-    echo "PR details saved to: $pr_file"
-
-    # Generate synopsis
-    generate_synopsis "$pr_file" "$synopsis_file"
-
-    if [[ "$DRY_RUN" == "true" ]]; then
-        echo ""
-        echo "=== DRY RUN - Synopsis content ==="
-        cat "$synopsis_file"
-        echo ""
-        echo "=== DRY RUN - Skipping email send and tag update ==="
-    else
-        # Get Fastmail session info
-        if ! get_fastmail_session; then
-            echo "Failed to get Fastmail session info. Exiting."
-            exit 1
-        fi
-
-        # Determine recipients (from config file, or default to sender)
-        local recipients_json=$(load_recipients_json)
-        if [[ -z "$recipients_json" ]]; then
-            recipients_json="{\"email\": \"$FASTMAIL_FROM_EMAIL\"}"
-            echo "No recipients configured, sending to self ($FASTMAIL_FROM_EMAIL)"
-        else
-            local recipients_display=$(load_recipients_display)
-            echo "Sending to: $recipients_display"
-        fi
-
-        # Send email
-        send_email_fastmail "$synopsis_file" "$recipients_json"
-
-        # Update tag for next run
-        update_tag
-    fi
-
-    echo ""
-    echo "Done!"
-    echo "PR details: $pr_file"
-    echo "Synopsis: $synopsis_file"
-}
-
-main

scripts/pre-commit-gazelle.sh

@@ -1,19 +0,0 @@
-#!/bin/bash
-# Pre-commit hook wrapper for gazelle that fails if files are modified.
-# This ensures BUILD files are in canonical format before committing.
-
-set -e
-
-# Run gazelle
-bazel run //:gazelle 2>/dev/null
-
-# Check if any BUILD files were modified
-if ! git diff --quiet -- '*.bazel' '**/BUILD' 'WORKSPACE*'; then
-    echo ""
-    echo "ERROR: gazelle modified BUILD files. Please stage the changes and retry:"
-    echo ""
-    git diff --name-only -- '*.bazel' '**/BUILD' 'WORKSPACE*'
-    echo ""
-    echo "Run: git add -u && git commit"
-    exit 1
-fi

src/main/cpp/net/eagle0/common/ByteHasher.hpp

@@ -18,31 +18,11 @@ static inline auto MixIn(uint64_t& hash, const uint8_t byte) {
 }
 
 // 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;
+    if (data != nullptr) {
+        for (size_t i = 0; i < size; ++i) { MixIn(hash, data[i]); }
     }
-
-    // Process remaining bytes
-    while (data < end) {
-        hash ^= static_cast<uint64_t>(*data);
-        hash *= FNV_PRIME;
-        data++;
-    }
-
     return hash;
 }
 

src/main/cpp/net/eagle0/common/FilesystemUtils.cpp

@@ -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;
     }
 

src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp

@@ -14,14 +14,6 @@
 
 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
 
-// A deterministic random generator that returns values from a fixed sequence.
-// Used for testing and MCTS simulation where we want specific, predictable outcomes.
-//
-// Values in the sequence are treated as [0, 1] probabilities that are returned
-// by DoubleZeroToOne(). The normal percentile methods (including open-ended
-// variants) work as usual, so callers must provide appropriate sequences.
-// For example, to get an open-ended low result of -50, provide [0.02, 0.52]
-// which produces: initial=2 (triggers open-ended), accumulated=52, final=2-52=-50
 class SequenceRandomGenerator : public ::RandomGenerator {
 private:
     const std::vector<double> sequence;

src/main/cpp/net/eagle0/common/mcts/README.md

@@ -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.

src/main/cpp/net/eagle0/common/mcts/abstract/AbstractMCTSAI.hpp

@@ -1,106 +0,0 @@
-//
-// Abstract MCTS AI implementation - game agnostic
-//
-
-#ifndef EAGLE0_ABSTRACT_MCTSAI_HPP
-#define EAGLE0_ABSTRACT_MCTSAI_HPP
-
-#include <chrono>
-#include <memory>
-#include <unordered_map>
-#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_;
-
-    // Transposition table: maps state hash -> minimum depth at which state was reached
-    // Used to detect and penalize longer paths to the same game state
-    // Cleared at the start of each Search() call
-    mutable std::unordered_map<uint64_t, int> transpositionTable_;
-
-    // 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;
-
-    // Debug tree dumping
-    static auto DumpTreeToFile(const MCTSNode* root, const std::string& filepath) -> void;
-
-private:
-    static auto
-    DumpNodeRecursive(const MCTSNode* node, std::ostream& out, int indentLevel, bool isLastChild)
-            -> void;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_ABSTRACT_MCTSAI_HPP

src/main/cpp/net/eagle0/common/mcts/abstract/BUILD.bazel

@@ -1,94 +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",
-        "//src/main/cpp/net/eagle0/common/mcts/util:tree_indent_util",
-    ],
-)
-
-# Individual targets are exposed above - no need for a catch-all target
-# Each component should be imported explicitly by its consumers

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSAction.hpp

@@ -1,40 +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;
-
-    // Check if this action requires a chance node (binary success/failure outcome)
-    // Examples: START_FIRE, RAISE_DEAD, EXTINGUISH_FIRE
-    // If true, the game engine should provide outcome probabilities
-    [[nodiscard]] virtual bool requiresChanceNode() const = 0;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_ACTION_HPP

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameEngine.cpp

@@ -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

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameEngine.hpp

@@ -1,161 +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 {
-
-// Information about chance outcomes (supports both binary and multi-outcome)
-struct ChanceOutcomeInfo {
-    std::vector<double> probabilities;  // Probability of each outcome (must sum to 1.0)
-    std::vector<double> rolls;          // Roll values for each outcome
-
-    // Factory for binary success/failure outcomes (e.g., START_FIRE)
-    [[nodiscard]] static ChanceOutcomeInfo binary(double successProbability) {
-        // -100: triggers open-ended low sequence, succeeds against any threshold
-        // 150: triggers open-ended high sequence, fails against any threshold
-        return {{successProbability, 1.0 - successProbability}, {-100.0, 150.0}};
-    }
-
-    // Factory for multi-outcome with fixed seeds (e.g., END_TURN)
-    // Uses uniformly distributed roll values to sample different random outcomes
-    [[nodiscard]] static ChanceOutcomeInfo multiOutcome(int numOutcomes) {
-        std::vector<double> probs(numOutcomes, 1.0 / numOutcomes);
-        std::vector<double> rollValues;
-        rollValues.reserve(numOutcomes);
-        // Spread rolls across the percentile range: 10, 30, 50, 70, 90 for 5 outcomes
-        for (int i = 0; i < numOutcomes; ++i) {
-            rollValues.push_back(10.0 + (80.0 * i) / (numOutcomes - 1));
-        }
-        return {probs, rollValues};
-    }
-
-    [[nodiscard]] const std::vector<double>& getRepresentativeRolls() const { return rolls; }
-
-    [[nodiscard]] const std::vector<double>& getProbabilities() const { return probabilities; }
-};
-
-// Backward compatibility alias
-using BinaryOutcomeInfo = ChanceOutcomeInfo;
-
-// Abstract interface for game engines
-class MCTSGameEngine {
-public:
-    virtual ~MCTSGameEngine() = default;
-
-    // Apply an action to a state and return the resulting state
-    // If deterministicRoll is provided (0.0-100.0), use that for any random outcomes
-    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> applyAction(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            double deterministicRoll = -1.0) 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;
-    }
-
-    // Get binary outcome information for an action that requires a chance node
-    // Only called for actions where action.requiresChanceNode() returns true
-    // Returns success probability for binary success/failure actions
-    [[nodiscard]] virtual BinaryOutcomeInfo getBinaryOutcomeInfo(
-            const MCTSGameState& state,
-            const MCTSAction& action) const = 0;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_GAME_ENGINE_HPP

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameState.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

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSNode.hpp

@@ -1,277 +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 {
-
-// Node type for MCTS tree
-enum class NodeType {
-    DECISION,  // Player chooses an action (standard MCTS node)
-    CHANCE     // Nature determines outcome (for probabilistic actions)
-};
-
-// Abstract MCTS Node structure
-struct MCTSNode {
-    // Node type
-    NodeType nodeType = NodeType::DECISION;
-    // 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;
-
-    // Chance node specific fields (only used when nodeType == CHANCE)
-    std::vector<double> outcomeProbabilities;  // Probability of each outcome
-    std::vector<double> outcomeRolls;          // Representative roll for each outcome
-
-    // 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; }
-
-    // Check if this is a chance node
-    [[nodiscard]] bool IsChanceNode() const { return nodeType == NodeType::CHANCE; }
-
-    // Check if this is a decision node
-    [[nodiscard]] bool IsDecisionNode() const { return nodeType == NodeType::DECISION; }
-
-    // Get best child from chance node (probability-weighted selection)
-    // For chance nodes, we want to explore outcomes proportionally to their probability
-    [[nodiscard]] MCTSNode* GetBestChanceChild() const {
-        if (children.empty() || !IsChanceNode()) return nullptr;
-
-        // Find the outcome that is most under-explored relative to its probability
-        // Expected visits for outcome i: total_visits * probability[i]
-        // Actual visits: child[i]->visitCount
-        // Deficit: expected - actual
-        size_t bestIndex = 0;
-        double bestDeficit = -std::numeric_limits<double>::max();
-
-        for (size_t i = 0; i < children.size(); i++) {
-            if (!children[i] || children[i]->isRedundant) continue;
-
-            const double expectedVisits = visitCount * outcomeProbabilities[i];
-            const double actualVisits = static_cast<double>(children[i]->visitCount);
-            const double deficit = expectedVisits - actualVisits;
-
-            if (deficit > bestDeficit) {
-                bestDeficit = deficit;
-                bestIndex = i;
-            }
-        }
-
-        return children[bestIndex].get();
-    }
-
-    // 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

src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp

@@ -1,60 +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 for tree expansion
-                                     // (0 = expand through current player's turn only,
-                                     //  1 = expand through opponent's first response, etc.)
-    int maxSimulationFlips = 0;      // Maximum player flips for leaf evaluation
-                                     // When evaluating a leaf at playerFlips < maxSimulationFlips,
-                                     // simulate forward to this phase for fair comparison
-                                     // (default 0 = evaluate leaves as-is, backward compatible)
-    std::string debugDumpPath = "";  // If non-empty, dump MCTS tree to this file path
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_TYPES_HPP

src/main/cpp/net/eagle0/common/mcts/util/BUILD.bazel

@@ -1,8 +0,0 @@
-load("@rules_cc//cc:defs.bzl", "cc_library")
-
-cc_library(
-    name = "tree_indent_util",
-    srcs = ["TreeIndentUtil.cpp"],
-    hdrs = ["TreeIndentUtil.hpp"],
-    visibility = ["//visibility:public"],
-)

src/main/cpp/net/eagle0/common/mcts/util/TreeIndentUtil.cpp

@@ -1,53 +0,0 @@
-//
-// Utility functions for processing tree indentation with UTF-8 box drawing characters
-//
-
-#include "TreeIndentUtil.hpp"
-
-namespace mcts::util {
-
-namespace {
-// Box drawing characters for tree visualization
-constexpr const char* kBranch = "\xE2\x94\x9C";      // ├
-constexpr const char* kCorner = "\xE2\x94\x94";      // └
-constexpr const char* kVertical = "\xE2\x94\x82";    // │
-constexpr const char* kHorizontal = "\xE2\x94\x80";  // ─
-}  // namespace
-
-std::string BuildTreeIndent(int indentLevel, bool isLastChild) {
-    std::string indent;
-
-    for (int i = 0; i < indentLevel; ++i) {
-        if (i == indentLevel - 1) {
-            indent += isLastChild ? kCorner : kBranch;
-            indent += kHorizontal;
-            indent += " ";
-        } else {
-            indent += "   ";
-        }
-    }
-
-    return indent;
-}
-
-std::string ConvertBranchToContinuation(const std::string& indent) {
-    std::string result = indent;
-
-    const std::string replacement = std::string(kVertical) + "  ";
-
-    // Replace ├ and └ with │
-    size_t pos = 0;
-    while ((pos = result.find(kBranch, pos)) != std::string::npos) {
-        result.replace(pos, 3, replacement);  // UTF-8 chars are 3 bytes
-        pos += replacement.size();
-    }
-    pos = 0;
-    while ((pos = result.find(kCorner, pos)) != std::string::npos) {
-        result.replace(pos, 3, replacement);
-        pos += replacement.size();
-    }
-
-    return result;
-}
-
-}  // namespace mcts::util

src/main/cpp/net/eagle0/common/mcts/util/TreeIndentUtil.hpp

@@ -1,22 +0,0 @@
-//
-// Utility functions for processing tree indentation with UTF-8 box drawing characters
-//
-
-#ifndef EAGLE0_TREE_INDENT_UTIL_HPP
-#define EAGLE0_TREE_INDENT_UTIL_HPP
-
-#include <string>
-
-namespace mcts::util {
-
-// Builds tree indentation string for a node at a given depth
-// Returns string like "   ├─ " or "   └─ " with proper spacing
-std::string BuildTreeIndent(int indentLevel, bool isLastChild);
-
-// Converts tree branch characters (├ and └) to continuation lines (│) for sub-content
-// This preserves the tree structure when displaying additional info below a node
-std::string ConvertBranchToContinuation(const std::string& indent);
-
-}  // namespace mcts::util
-
-#endif  // EAGLE0_TREE_INDENT_UTIL_HPP

src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.cpp

@@ -9,6 +9,7 @@
 #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 +76,30 @@ 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 +132,12 @@ 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 +161,7 @@ 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) {

src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp

@@ -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

src/main/cpp/net/eagle0/shardok/ai/AIAttackerStrategySelector.cpp

@@ -4,7 +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"
@@ -21,13 +20,11 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
         const PlayerId attackerPid,
         const GameStateW& gameState,
         const CoordsSet& criticalTileCoords,
-        int maxRounds,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
         const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-        const CommandListSPtr& /*availableCommands*/) -> AIStrategy {
+        const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
     uint32_t attackerUnitCount = 0;
     int defenderOccupiedCriticalTileCount = 0;
     bool canFlee = false;
@@ -66,14 +63,12 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
     if (canFlee && AIFleeDecisionCalculator::ShouldConsiderFleeing(
                            attackerPid,
                            gameState,
-                           maxRounds,
+                           settings,
                            FLEE_CONSIDERATION_THRESHOLD)) {
         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 +83,8 @@ 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 +100,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                 attackerUnits,
                 apdCache,
                 alCache,
-                battalionTypeGetter,
-                braveWaterCost));
+                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
+                settings));
     } else {
         chosenStrategy = HoldCastlesStrategy;
     }

src/main/cpp/net/eagle0/shardok/ai/AIAttackerStrategySelector.hpp

@@ -6,12 +6,9 @@
 #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/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"
 
 namespace shardok {
@@ -22,13 +19,11 @@ public:
             PlayerId attackerPid,
             const GameStateW& gameState,
             const CoordsSet& criticalTileCoords,
-            int maxRounds,
             const APDCache& apdCache,
             const ALCache& alCache,
-            const BattalionTypeGetter& battalionTypeGetter,
-            ActionPoints braveWaterCost,
+            const SettingsGetter& settings,
             const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-            const CommandListSPtr& availableCommands) -> AIStrategy;
+            const vector<CommandProto>& availableCommands) -> AIStrategy;
 };
 
 }  // namespace shardok

src/main/cpp/net/eagle0/shardok/ai/AICommandEvaluator.cpp

@@ -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

src/main/cpp/net/eagle0/shardok/ai/AICommandEvaluator.hpp

@@ -1,110 +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/common/command_type.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-class ShardokEngine;
-
-using ScoreValue = double;
-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

src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.cpp

@@ -7,7 +7,6 @@
 #include <algorithm>
 
 #include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexCubeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
@@ -37,8 +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());
 
@@ -67,8 +66,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                     pid,
                     isDefender,
                     gameState,
+                    settings,
                     apdCache,
-                    battalionTypeGetter,
                     enemyLocations,
                     castleLocations,
                     minDistToEnemies)) {
@@ -81,22 +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;
         }
 
@@ -111,8 +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) {
@@ -144,16 +137,15 @@ bool AICommandFilter::IsWastefulAction(
 
             if (!isDefender) {
                 // Attackers: Only allow fire if the target location is on or adjacent to an enemy
-                const int targetRow = cmd.GetTargetRow();
-                const int targetCol = cmd.GetTargetColumn();
-                if (targetRow < 0 || targetCol < 0) {
-                    throw ShardokInternalErrorException(
-                            "START_FIRE_COMMAND missing required target information");
+                const auto cmdProto = cmd.GetCommandProto();
+                if (!cmdProto.has_target()) {
+                    return true;  // Can't analyze without target info
                 }
 
-                const Coords fireLocation(
-                        static_cast<int8_t>(targetRow),
-                        static_cast<int8_t>(targetCol));
+                const auto& targetCoords = cmdProto.target();
+                const Coords fireLocation{
+                        static_cast<int8_t>(targetCoords.row()),
+                        static_cast<int8_t>(targetCoords.column())};
 
                 // Check if any enemy is on the fire location or adjacent to it
                 bool enemyNearFireLocation = false;
@@ -188,12 +180,13 @@ bool AICommandFilter::IsWastefulAction(
 
             if (!isDefender) {
                 // Attackers: Only allow fortify if within 3 hexes of enemies or castles
-                const int unitId = cmd.GetActorUnitId();
-                if (unitId < 0) {
-                    throw ShardokInternalErrorException(
-                            "FORTIFY_COMMAND missing required actor information");
+                const auto cmdProto = cmd.GetCommandProto();
+                if (!cmdProto.has_actor()) {
+                    return true;  // Can't analyze without actor info
                 }
 
+                const auto unitId = cmdProto.actor().value();
+
                 // Get the acting unit directly by ID
                 const Unit* actingUnit = gameState->units()->Get(unitId);
                 // verify the unit is still active
@@ -250,18 +243,16 @@ bool AICommandFilter::IsWastefulAction(
             // These actions can fail, so we need high confidence of benefit (8+ action points
             // saved)
 
-            const int unitId = cmd.GetActorUnitId();
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (unitId < 0 || targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "BUILD_BRIDGE/FREEZE_WATER_COMMAND missing required actor or target "
-                        "information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_actor() || !cmdProto.has_target()) {
+                return true;  // Can't analyze without full command info
             }
 
-            const Coords waterLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto unitId = cmdProto.actor().value();
+            const auto& targetCoords = cmdProto.target();
+            const Coords waterLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};
 
             // Get the acting unit directly by ID
             const Unit* actingUnit = gameState->units()->Get(unitId);
@@ -278,7 +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()),
@@ -356,16 +347,15 @@ bool AICommandFilter::IsWastefulAction(
         case CommandType::REPAIR_COMMAND: {
             // Repair filtering - filter repairs with high integrity targets
             // Note: RepairCommandFactory already filters enemy-occupied targets
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "REPAIR_COMMAND missing required target information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_target()) {
+                return true;  // Can't analyze without target info
             }
 
-            const Coords repairLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto& targetCoords = cmdProto.target();
+            const Coords repairLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};
 
             // Check terrain modifiers at target location
             const auto* terrain = GetTerrain(gameState->hex_map(), repairLocation);
@@ -388,16 +378,15 @@ bool AICommandFilter::IsWastefulAction(
 
         case CommandType::EXTINGUISH_FIRE_COMMAND: {
             // Extinguish fire filtering - don't extinguish fires on enemy-occupied tiles
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "EXTINGUISH_FIRE_COMMAND missing required target information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_target()) {
+                return true;  // Can't analyze without target info
             }
 
-            const Coords fireLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto& targetCoords = cmdProto.target();
+            const Coords fireLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};
 
             // Check if any enemy occupies the fire location - let them burn!
             std::vector<PlayerId> allyPids;  // Empty for now - assume 2-player game
@@ -418,8 +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; }
@@ -429,17 +418,17 @@ bool AICommandFilter::IsWastefulMovement(
         return false;  // Don't filter defender movement or when close to enemies
     }
 
-    // Get unit and target information directly from command
-    const int unitId = cmd.GetActorUnitId();
-    const int targetRow = cmd.GetTargetRow();
-    const int targetCol = cmd.GetTargetColumn();
+    // Get the command proto to access unit and target information
+    const auto cmdProto = cmd.GetCommandProto();
 
     // Check if we have the required information
-    if (unitId < 0 || targetRow < 0 || targetCol < 0) {
-        throw ShardokInternalErrorException(
-                "MOVE_COMMAND missing required actor or target information");
+    if (!cmdProto.has_actor() || !cmdProto.has_target()) {
+        return false;  // Can't analyze without unit and target info
     }
 
+    const auto unitId = cmdProto.actor().value();
+    const auto& targetCoords = cmdProto.target();
+
     // Get the acting unit directly by ID
     const Unit* actingUnit = gameState->units()->Get(unitId);
     // Verify the unit is still active
@@ -455,10 +444,12 @@ bool AICommandFilter::IsWastefulMovement(
     }
 
     const auto& currentCoords = actingUnit->location();
-    const Coords targetCoordsFlat(static_cast<int8_t>(targetRow), static_cast<int8_t>(targetCol));
+    const Coords targetCoordsFlat{
+            static_cast<int8_t>(targetCoords.row()),
+            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()),
@@ -499,8 +490,7 @@ bool AICommandFilter::IsStrategicBlunder(
         PlayerId /*pid*/,
         bool /*isDefender*/,
         const GameStateW& /*gameState*/,
-        const APDCache& /*apdCache*/,
-        const BattalionTypeGetter& /*battalionTypeGetter*/,
+        const SettingsGetter& /*settings*/,
         double /*minDistToEnemies*/) {
     // Simplified strategic blunder detection for now
     // TODO: Implement proper castle abandonment detection

src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp

@@ -8,12 +8,12 @@
 #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"
 #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"
 
 namespace shardok {
 
@@ -32,8 +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(
@@ -41,8 +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
@@ -54,8 +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);
@@ -66,8 +66,8 @@ private:
             PlayerId pid,
             bool isDefender,
             const GameStateW& gameState,
+            const SettingsGetter& settings,
             const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
             const CoordsSet& enemyLocations,
             double minDistToEnemies);
 
@@ -77,8 +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

src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp

@@ -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

src/main/cpp/net/eagle0/shardok/ai/AIConfig.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

src/main/cpp/net/eagle0/shardok/ai/AIDefenderStrategySelector.cpp

@@ -7,10 +7,8 @@
 #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 {
@@ -21,9 +19,8 @@ constexpr double MINIMUM_RATIO_FOR_DEFENDER_TO_HOLD = 0.60;
 auto AIDefenderStrategySelector::BestDefenderStrategy(
         const GameStateW& 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 +36,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                     player->player_id(),
                     criticalTileCoords,
                     apdCache,
-                    battalionTypeGetter);
+                    settings);
             attackerUnitIdsRequiringWaterCrossing.insert(
                     attackerUnitIdsRequiringWaterCrossing.end(),
                     unitIdsRequiringWaterCrossing.begin(),
@@ -74,7 +71,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
         }
     }
 
-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining = 32 - gameState->current_round();
     AIStrategy chosenStrategy;
 
     // Defender will flee if

src/main/cpp/net/eagle0/shardok/ai/AIDefenderStrategySelector.hpp

@@ -6,23 +6,19 @@
 #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 {
 public:
     static auto BestDefenderStrategy(
             const GameStateW& gameState,
             const CoordsSet& criticalTileCoords,
-            int maxRounds,
             const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy;
+            const SettingsGetter& settings) -> AIStrategy;
 };
 }  // namespace shardok
 

src/main/cpp/net/eagle0/shardok/ai/AIDistanceDebuf.cpp

@@ -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);
         }
     }
 

src/main/cpp/net/eagle0/shardok/ai/AIDistanceDebuf.hpp

@@ -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;
 

src/main/cpp/net/eagle0/shardok/ai/AIFleeDecisionCalculator.cpp

@@ -15,15 +15,15 @@
 namespace shardok {
 
 auto AIFleeDecisionCalculator::GetFleeCommandIndex(
-        const CommandList::const_iterator& fleeCommand,
-        const CommandListSPtr& availableCommands) -> size_t {
-    return static_cast<size_t>(std::distance(availableCommands->begin(), fleeCommand));
+        const vector<CommandProto>::const_iterator& fleeCommand,
+        const vector<CommandProto>& availableCommands) -> size_t {
+    return static_cast<size_t>(std::distance(availableCommands.begin(), fleeCommand));
 }
 
 auto AIFleeDecisionCalculator::EstimateCombatSuccess(
         PlayerId attackerPlayerId,
         const GameStateW& gameState,
-        int maxRounds) -> double {
+        const SettingsGetter& settings) -> double {
     if (gameState->status() == nullptr ||
         gameState->status()->state() !=
                 net::eagle0::shardok::storage::fb::GameStatus_::State_GAME_RUNNING) {
@@ -68,7 +68,7 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(
         }
     }
 
-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining = settings.Backing().max_rounds() - gameState->current_round();
 
     // Special case: Attacker has no heroes - automatic loss
     if (attackerHeroes == 0) {
@@ -133,15 +133,17 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(
 
 auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
         PlayerId playerId,
+        const SettingsGetter& settingsGetter,
         const GameStateW& guessedState,
-        const CommandListSPtr& availableCommands,
-        const CommandList::const_iterator& fleeCommand,
-        int maxRounds,
-        int minimumFleeOddsThreshold,
-        int desperateFleeThreshold,
+        const vector<CommandProto>& availableCommands,
+        const vector<CommandProto>::const_iterator& fleeCommand,
         bool enableDebugLogging) -> FleeDecision {
     // Get flee success odds
-    const int fleeSuccessChance = (*fleeCommand)->GetOddsPercentile();
+    const int fleeSuccessChance = fleeCommand->odds().success_chance();
+
+    // Get thresholds from settings
+    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);
@@ -161,7 +163,7 @@ 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, settingsGetter);
 
     // If combat situation is hopeless, even bad flee odds are better than certain death
     if (combatWinChance <= 0.05 && fleeSuccessChance >= desperateFleeThreshold) {
@@ -213,11 +215,11 @@ auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
 auto AIFleeDecisionCalculator::ShouldConsiderFleeing(
         PlayerId attackerPlayerId,
         const GameStateW& guessedState,
-        int maxRounds,
+        const SettingsGetter& settings,
         double fleeConsiderationThreshold) -> bool {
     // Get combat success probability
     const double combatSuccessChance =
-            EstimateCombatSuccess(attackerPlayerId, guessedState, maxRounds);
+            EstimateCombatSuccess(attackerPlayerId, guessedState, settings);
 
     // Consider fleeing if combat success chance is below threshold
     return combatSuccessChance < fleeConsiderationThreshold;

src/main/cpp/net/eagle0/shardok/ai/AIFleeDecisionCalculator.hpp

@@ -9,11 +9,14 @@
 #ifndef AIFleeDecisionCalculator_hpp
 #define AIFleeDecisionCalculator_hpp
 
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.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 {
 
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
+
 class AIFleeDecisionCalculator {
 public:
     // Configuration for flee decision thresholds
@@ -32,33 +35,31 @@ public:
     // Evaluate whether to flee or fight in the final round
     [[nodiscard]] static auto EvaluateFleeVsFight(
             PlayerId playerId,
+            const SettingsGetter& settings,
             const GameStateW& guessedState,
-            const CommandListSPtr& availableCommands,
-            const CommandList::const_iterator& fleeCommand,
-            int maxRounds,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
+            const vector<CommandProto>& availableCommands,
+            const vector<CommandProto>::const_iterator& fleeCommand,
             bool enableDebugLogging = false) -> FleeDecision;
 
     // Estimate probability of combat success for the attacker
     [[nodiscard]] static auto EstimateCombatSuccess(
             PlayerId attackerPlayerId,
             const GameStateW& guessedState,
-            int maxRounds) -> double;
+            const SettingsGetter& settings) -> 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,
+            const SettingsGetter& settings,
             double fleeConsiderationThreshold = 0.5) -> bool;
 
 private:
     // Helper to get flee command index
     [[nodiscard]] static auto GetFleeCommandIndex(
-            const CommandList::const_iterator& fleeCommand,
-            const CommandListSPtr& availableCommands) -> size_t;
+            const vector<CommandProto>::const_iterator& fleeCommand,
+            const vector<CommandProto>& availableCommands) -> size_t;
 };
 
 }  // namespace shardok

src/main/cpp/net/eagle0/shardok/ai/AIHeuristicWeighting.cpp

@@ -1,251 +0,0 @@
-//
-// Fast heuristic weighting implementation with context-aware logic
-//
-
-#include "AIHeuristicWeighting.hpp"
-
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.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 CommandType commandType,
-        const UnitId actorUnitId,
-        const PlayerId actorPlayerId,
-        const Coords& targetCoords,
-        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 bool hasTarget = (targetCoords.row() >= 0 && targetCoords.column() >= 0);
-
-    switch (commandType) {
-        // === 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: {
-            // METEOR_START doesn't have a target - it's based on actor location
-            if (hasTarget) {
-                throw ShardokInternalErrorException(
-                        "METEOR_START_COMMAND should not have target coordinates");
-            }
-
-            // Get actor's location
-            const auto* actorUnit = units->Get(actorUnitId);
-            if (!actorUnit) {
-                throw ShardokInternalErrorException(
-                        "METEOR_START_COMMAND actor unit not found in game state");
-            }
-
-            const Coords& actorLocation = actorUnit->location();
-            int enemyCount = 0;
-
-            // Count enemies within meteor range (3 hexes) of actor location
-            constexpr int METEOR_RANGE = 3;
-            const auto tilesInRange = TilesWithinDistance(hexMap, actorLocation, METEOR_RANGE);
-            for (const auto& tileCoords : tilesInRange) {
-                if (const auto* unit = Occupant(units, tileCoords)) {
-                    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 (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "METEOR_TARGET_COMMAND requires target coordinates for heuristic "
-                        "weighting");
-            }
-
-            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 (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "START_FIRE_COMMAND requires target coordinates for heuristic weighting");
-            }
-
-            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 but still valid
-        }
-
-        // === 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 (!hasTarget) return 0.0;
-
-            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 (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "MOVE_COMMAND requires target coordinates for heuristic weighting");
-            }
-
-            // Get actor unit to determine battalion type and start position
-            const auto* actorUnit = units->Get(actorUnitId);
-            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 = targetCoords;
-            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 (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "EXTINGUISH_FIRE_COMMAND requires target coordinates for heuristic "
-                        "weighting");
-            }
-
-            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 but still valid
-        }
-
-        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

src/main/cpp/net/eagle0/shardok/ai/AIHeuristicWeighting.hpp

@@ -1,40 +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/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(
-            net::eagle0::shardok::common::CommandType commandType,
-            UnitId actorUnitId,
-            PlayerId actorPlayerId,
-            const Coords& targetCoords,
-            const GameStateW& state,
-            const CoordsSet& castleCoords,
-            const APDCache* apdCache,
-            bool isDefender,
-            std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType);
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_HEURISTIC_WEIGHTING_HPP

src/main/cpp/net/eagle0/shardok/ai/AIScoreCalculator.hpp

@@ -0,0 +1,64 @@
+//
+// Created by dancrosby on 3/4/20.
+//
+
+#ifndef EAGLE0_AISCORECALCULATOR_HPP
+#define EAGLE0_AISCORECALCULATOR_HPP
+
+#include <chrono>
+#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:
+    // Evaluate the score of a guessed game state based on the current AI strategy. DOES NOT perform
+    // or evaluate any commands.
+    [[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;
+
+    // Evaluates the score for a particular command index for the given player, using lookahead.
+    [[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,
+            std::chrono::steady_clock::time_point deadline) -> std::future<ScoreValue>;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AISCORECALCULATOR_HPP

src/main/cpp/net/eagle0/shardok/ai/AIStrategy.cpp

@@ -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};

src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.cpp

@@ -24,40 +24,10 @@ 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();
@@ -102,25 +72,12 @@ 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));
-
-    // TEMPORARY DEBUG OUTPUT
-    printf("[DEBUG CalculateTimeBudget] numCommands=%zu, msPerCommand=%.2f, budgetMs=%.2f, "
-           "clampedBudgetMs=%.2f, isClose=%d\n",
-           numCommands,
-           msPerCommand,
-           budgetMs,
-           clampedBudgetMs,
-           isClose);
+    const auto remainingBudget = std::chrono::duration_cast<std::chrono::milliseconds>(budget);
 
     // Get minimum depth requirement
     const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();

src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp

@@ -36,13 +36,10 @@ struct AITimeBudget {
 };
 
 // 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
 

src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.cpp

@@ -17,10 +17,9 @@ using std::end;
 using std::shared_ptr;
 
 constexpr double kProfessionValue = 200;
-constexpr double kVigorScoreMultiplier = 5.0;
 constexpr double kCastleMultiplierBonus = 1.0;
 constexpr double kOnFireMultiplier = 0.25;
-constexpr double kAdjacentFireMultiplier = 0.80;
+constexpr double kAdjacentFireMultiplier = 0.99;
 constexpr double kOnIceMultiplier = 0.25;
 constexpr double kMeteorStartInRangeValue = 50;
 constexpr double kMeteorDirectTargetingEnemy = 2;
@@ -64,8 +63,7 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
                      4.0;
     }
 
-    const double vigorValue =
-            unit->has_attached_hero() ? unit->attached_hero().vigor() * kVigorScoreMultiplier : 0.0;
+    const double vigorValue = unit->has_attached_hero() ? unit->attached_hero().vigor() : 0.0;
 
     double battalionTypeMultiplier = 1.0;
     switch (unit->battalion().type()) {
@@ -337,8 +335,7 @@ 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
 
@@ -357,7 +354,9 @@ auto UnitValue(
                 kCastleMultiplierBonus * (terrain->modifier().castle().integrity() + 25) / 100.0;
     }
     double onFireMultiplier = 1.0;
-    if (terrain->modifier().fire().present()) { onFireMultiplier *= kOnFireMultiplier; }
+    if (terrain->modifier().fire().present() && (isAttacker || attackerWantsCastles)) {
+        onFireMultiplier *= kOnFireMultiplier;
+    }
     {
         for (const auto adjacentCoords = HexMapUtils::GetAdjacentCoords(map, location);
              const auto &c : adjacentCoords) {
@@ -381,8 +380,8 @@ auto UnitValue(
             roundsRemaining,
             attackerUnits,
             defenderUnits,
-            meteorRange,
-            meteorCastVigorCost);
+            settings.Backing().meteor_range(),
+            settings.Backing().meteor_cast_vigor_cost());
 
     // scouting values
     // attack range

src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp

@@ -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
 

src/main/cpp/net/eagle0/shardok/ai/AIVictoryConditionScoreCalculator.cpp

@@ -7,9 +7,9 @@
 #include <algorithm>
 #include <ranges>
 
+#include "AIAttackLocations.hpp"
+#include "AIDistanceDebuf.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 +43,8 @@ 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 +60,8 @@ auto AttackerDebufForOnFireCriticalTile(
                 extinguishingUnits,
                 apdCache,
                 alCache,
-                battalionTypeGetter,
-                braveWaterCost,
+                settings,
+                braveWaterActionPointCost,
                 lateGame,
                 /* includeUndead = */ false);
         if (newDebuf < minDebuf) minDebuf = newDebuf;
@@ -77,8 +77,8 @@ 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 +87,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
                                   claimableUnits,
                                   apdCache,
                                   alCache,
-                                  battalionTypeGetter,
-                                  braveWaterCost,
+                                  settings,
+                                  braveWaterActionPointCost,
                                   lateGame,
                                   /* includeUndead = */ false);
 }
@@ -100,8 +100,8 @@ 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() +
@@ -117,8 +117,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
                    attackerUnits,
                    apdCache,
                    alCache,
-                   battalionTypeGetter,
-                   braveWaterCost,
+                   settings,
+                   braveWaterActionPointCost,
                    lateGame,
                    /* includeUndead = */ false);
 }
@@ -126,7 +126,10 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
 auto DefenderHoldsCriticalTilesVictoryScore(
         const GameStateW& 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();
@@ -156,8 +159,7 @@ auto AttackerHoldsCriticalTilesVictoryScore(
         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 +175,7 @@ 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 +202,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                             claimablePlayerUnits,
                             apdCache,
                             alCache,
-                            battalionTypeGetter,
-                            braveWaterCost,
+                            settings,
+                            braveWaterActionPointCost,
                             IsLateGame(gameState));
                     total += BADLY_HELD_VALUE;
                 }
@@ -212,8 +215,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                         playerUnits,
                         apdCache,
                         alCache,
-                        battalionTypeGetter,
-                        braveWaterCost,
+                        settings,
+                        braveWaterActionPointCost,
                         IsLateGame(gameState));
             }
         } else if (terrain->modifier().fire().present()) {
@@ -224,8 +227,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                     claimablePlayerUnits,
                     apdCache,
                     alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                     IsLateGame(gameState));
         } else {
             total -= AttackerDebufForUnoccupiedCriticalTile(
@@ -235,8 +238,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                     claimablePlayerUnits,
                     apdCache,
                     alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                     IsLateGame(gameState));
         }
     }
@@ -249,8 +252,7 @@ auto LastPlayerStandingVictoryScore(
         const PlayerInfo* player,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue {
+        const SettingsGetter& settings) -> ScoreValue {
     if (!std::ranges::contains(
                 *player->victory_conditions(),
                 net::eagle0::shardok::storage::fb::
@@ -283,8 +285,8 @@ auto LastPlayerStandingVictoryScore(
                                                  playerUnits,
                                                  apdCache,
                                                  alCache,
-                                                 battalionTypeGetter,
-                                                 braveWaterCost,
+                                                 settings,
+                                                 5,
                                                  IsLateGame(gameState),
                                                  /* includeUndead = */ true);
     }

src/main/cpp/net/eagle0/shardok/ai/AIVictoryConditionScoreCalculator.hpp

@@ -9,7 +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"
@@ -30,21 +29,22 @@ auto AttackerHoldsCriticalTilesVictoryScore(
         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 CoordsSet& criticalTileLocations,
-        const PlayerInfo* player) -> ScoreValue;
+        const PlayerInfo* player,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const SettingsGetter& settings) -> 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;
 
 }  // namespace shardok
 

src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.cpp

@@ -15,7 +15,7 @@ auto UnitIdsRequiringWaterCrossing(
         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) {
@@ -76,7 +76,8 @@ auto UnitIdsRequiringWaterCrossing(
 auto UnitIdsToCreateWaterCrossing(
         const GameStateW &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 &&
@@ -198,14 +199,14 @@ auto IntendedCrossingStarts(
         const GameStateW &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

src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.hpp

@@ -5,7 +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"
@@ -35,13 +34,14 @@ auto UnitIdsRequiringWaterCrossing(
         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,
         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
@@ -71,17 +71,9 @@ auto IntendedCrossingStarts(
         const GameStateW& 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
 

src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.cpp

@@ -18,7 +18,7 @@ constexpr ScoreValue kNoRequiredCrossingScore = std::numeric_limits<ScoreValue>:
 constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>::min();
 
 [[nodiscard]] auto AIWaterCrossingCommandChooser::WaterCrossingScore(
-        const BattalionTypeGetter &battalionTypeGetter,
+        const SettingsGetter &settingsGetter,
         const GameStateW &gameState,
         const CoordsSet &castleCoords,
         const CoordsSet &startCrossingFrom) const -> ScoreValue {
@@ -51,13 +51,15 @@ 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 +67,7 @@ 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;
@@ -86,7 +88,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
         if (std::ranges::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);
 
@@ -118,7 +120,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
 }
 
 auto AIWaterCrossingCommandChooser::StartCrossingFrom(
-        const BattalionTypeGetter &battalionTypeGetter,
+        const SettingsGetter &settingsGetter,
         const GameStateW &gameState,
         const CoordsSet &castleCoords) const -> CoordsSet {
     CoordsSet startCrossingFrom(gameState->hex_map());
@@ -152,16 +154,16 @@ 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

src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp

@@ -6,16 +6,19 @@
 #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"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
 using GameState = net::eagle0::shardok::storage::fb::GameState;
 using Unit = net::eagle0::shardok::storage::fb::Unit;
 using ScoreValue = double;
@@ -30,13 +33,13 @@ public:
         : playerId(pid),
           apdCache(std::move(apdCache)) {}
 
-    [[nodiscard]] auto StartCrossingFrom(
-            const BattalionTypeGetter &battalionTypeGetter,
+    auto StartCrossingFrom(
+            const SettingsGetter &settingsGetter,
             const GameStateW &gameState,
             const CoordsSet &castleCoords) const -> CoordsSet;
 
     [[nodiscard]] auto WaterCrossingScore(
-            const BattalionTypeGetter &battalionTypeGetter,
+            const SettingsGetter &settingsGetter,
             const GameStateW &gameState,
             const CoordsSet &castleCoords,
             const CoordsSet &startCrossingFrom) const -> ScoreValue;

src/main/cpp/net/eagle0/shardok/ai/AI_SCORING_SYSTEM.md

@@ -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.

src/main/cpp/net/eagle0/shardok/ai/BUILD.bazel

@@ -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"],
@@ -39,15 +28,14 @@ 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 +47,6 @@ 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",
@@ -101,14 +85,11 @@ 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",
@@ -137,10 +118,8 @@ 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",
@@ -163,48 +142,9 @@ cc_library(
         ":ai_score_utilities",
         ":ai_unit_score_calculator",
         "//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",
-    ],
-)
-
-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/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/common:command_type_cc_proto",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
     ],
 )
 
@@ -214,18 +154,16 @@ cc_library(
     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",
         "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
         "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
         "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
     ],
 )
@@ -244,19 +182,38 @@ cc_library(
     ],
 )
 
+cc_library(
+    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 = [
+        ":ai_attacker_strategy_selector",
+        ":ai_command_filter",
+        ":ai_unit_score_calculator",
+        ":ai_victory_condition_score_calculator",
+        ":transposition_table",
+        "//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",
+    ],
+)
+
 cc_library(
     name = "ai_strategy",
     srcs = ["AIStrategy.cpp"],
     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",
     ],
 )
 
@@ -266,7 +223,6 @@ 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__",
     ],
@@ -277,6 +233,27 @@ 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: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 = "ai_water_crossing_calculator",
     srcs = ["AIWaterCrossingCalculator.cpp"],
@@ -284,13 +261,10 @@ 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",
@@ -312,6 +286,7 @@ cc_library(
         "//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/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
     ],
 )
 
@@ -321,7 +296,6 @@ 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__",
     ],
@@ -340,30 +314,19 @@ 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",
-    ],
-)
-
-cc_library(
-    name = "ai_config",
-    hdrs = ["AIConfig.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
     ],
 )
 
@@ -375,21 +338,15 @@ 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",
     ],
 )

src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.cpp

@@ -10,9 +10,8 @@
 #include <utility>
 
 #include "AIAttackerStrategySelector.hpp"
-#include "AICommandEvaluator.hpp"
+#include "AIScoreCalculator.hpp"
 #include "TranspositionTable.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 
 namespace shardok {
@@ -24,21 +23,19 @@ 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,
         const GameStateW& state,
-        const CommandListSPtr& commands,
+        const std::vector<CommandProto>& commands,
         const AITimeBudget& initialBudget) const -> SearchResult {
     // Make a mutable copy of the time budget to track remaining time
     AITimeBudget timeBudget = initialBudget;
@@ -51,7 +48,7 @@ auto IterativeDeepeningAI::IterativeSearch(
 
     // 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 (commands.empty()) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
         printf("ID AI: Commands are empty, returning early\n");
 #endif
@@ -70,14 +67,20 @@ auto IterativeDeepeningAI::IterativeSearch(
     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();
-    scoresByDepth.resize(commands->size());
+    scoresByDepth.resize(commands.size());
     highestDepthCompleted.clear();
-    highestDepthCompleted.resize(commands->size(), 0);
+    highestDepthCompleted.resize(commands.size(), 0);
 
     size_t currentDepth = 1;
     size_t previousBestCommand = 0;  // Track best command from previous depth
@@ -108,7 +111,7 @@ auto IterativeDeepeningAI::IterativeSearch(
 
             auto future = SearchCommandAtDepthWithEngine(
                     guessedEngine,
-                    scorer,
+                    settingsGetter,
                     maxRepeatCount,
                     commands,
                     cmdIndex,
@@ -132,8 +135,7 @@ auto IterativeDeepeningAI::IterativeSearch(
             evaluatedCount++;
 
             // Check if this command is not END_TURN_COMMAND
-            if ((*commands)[cmdIndex]->GetCommandType() !=
-                net::eagle0::shardok::common::END_TURN_COMMAND) {
+            if (commands[cmdIndex].type() != net::eagle0::shardok::common::END_TURN_COMMAND) {
                 allEndTurnCommands = false;
             }
         }
@@ -144,7 +146,7 @@ auto IterativeDeepeningAI::IterativeSearch(
             size_t currentBestCommand = 0;
             ScoreValue currentBestScore = -std::numeric_limits<ScoreValue>::infinity();
 
-            for (size_t i = 0; i < commands->size(); ++i) {
+            for (size_t i = 0; i < commands.size(); ++i) {
                 if (highestDepthCompleted[i] >= currentDepth) {
                     if (scoresByDepth[i][currentDepth] > currentBestScore) {
                         currentBestScore = scoresByDepth[i][currentDepth];
@@ -157,20 +159,16 @@ auto IterativeDeepeningAI::IterativeSearch(
             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) - type: %s\n",
+                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
                        currentDepth - 1,
                        previousBestCommand,
                        scoresByDepth[previousBestCommand][currentDepth - 1],
-                       net::eagle0::shardok::common::CommandType_Name(
-                               (*commands)[previousBestCommand]->GetCommandType())
-                               .c_str());
-                printf("  Depth %lu best: command %zu (score %.2f) - type: %s\n",
+                       commands[previousBestCommand].DebugString().c_str());
+                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
                        currentDepth,
                        currentBestCommand,
                        currentBestScore,
-                       net::eagle0::shardok::common::CommandType_Name(
-                               (*commands)[currentBestCommand]->GetCommandType())
-                               .c_str());
+                       commands[currentBestCommand].DebugString().c_str());
 #endif
             }
 
@@ -249,7 +247,7 @@ auto IterativeDeepeningAI::IterativeSearch(
     result.searchCompleted = result.minimumDepthCompleted;
     result.timeUsed = std::chrono::duration_cast<std::chrono::milliseconds>(
             std::chrono::steady_clock::now() - startTime);
-    result.availableCommandCount = commands->size();
+    result.availableCommandCount = commands.size();
     result.commandCountEvaluated = evaluatedCountAtHighestDepth;
     result.completionReason = completionReason;
 
@@ -272,9 +270,9 @@ bool IterativeDeepeningAI::IsTimeExpired(const AITimeBudget& budget) {
 
 auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
         const ShardokEngine& guessedEngine,
-        const AIScoreCalculator& scorer,
+        const GameSettings::Getter& settingsGetter,
         const int maxRepeatCount,
-        const CommandListSPtr& commands,
+        const std::vector<CommandProto>& commands,
         const size_t commandIndex,
         const int desiredDepth,
         const ScoreValue currentUtility,
@@ -284,57 +282,65 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
     result.depthAchieved = desiredDepth;
     result.searchCompleted = true;
     result.minimumDepthCompleted = true;
-    result.availableCommandCount = commands->size();
+    result.availableCommandCount = commands.size();
     result.commandCountEvaluated = 1;  // We're evaluating just this command
 
-    if (commandIndex >= commands->size()) {
+    if (commandIndex >= commands.size()) {
         result.bestScore = 0.0;
         std::promise<SearchResult> p;
         p.set_value(result);
         return p.get_future();
     }
 
-    // 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;
+        // Calculate deadline from remaining time budget
+        const auto deadline = startTime + timeBudget.remainingBudget;
 
-    // Create command evaluator for lookahead search
-    AICommandEvaluator evaluator(scorer, apdCache, battalionTypeGetter);
+        // Get the future from CommandScore - don't wait yet
+        // Note: CommandScore 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 = AIScoreCalculator::CommandScore(
+                playerId,
+                isDefender,
+                desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
+                maxRepeatCount,
+                guessedEngine,
+                strategy,
+                currentUtility,
+                settingsGetter,
+                castleCoords,
+                apdCache,
+                alCache,
+                commandIndex,
+                deadline);
 
-    // 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);
+        // Calculate time and adjust budget before waiting
+        // This is needed because we need to update timeBudget synchronously
+        const auto commandScore = commandScoreFuture.get();
 
-    // Calculate time and adjust budget before waiting
-    // This is needed because we need to update timeBudget synchronously
-    const auto commandScore = commandScoreFuture.get();
+        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);
 
-    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;
 
-    // Deduct adjusted time from remaining budget
-    timeBudget.remainingBudget -= adjustedElapsedMs;
-
-    result.bestScore = commandScore;
+        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;
+    }
 
     std::promise<SearchResult> p;
     p.set_value(result);

src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp

@@ -12,18 +12,17 @@
 #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/ShardokCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
 // Forward declarations
 class ShardokEngine;
 using ScoreValue = double;
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
 
 /// Reason why AI evaluation completed at the achieved depth.
 enum class EvaluationCompletionReason {
@@ -62,14 +61,13 @@ 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 CommandListSPtr& commands,
+            const std::vector<CommandProto>& commands,
             const AITimeBudget& initialBudget) const;
 
 private:
@@ -77,9 +75,8 @@ private:
     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;
@@ -90,9 +87,9 @@ private:
 
     [[nodiscard]] std::future<SearchResult> SearchCommandAtDepthWithEngine(
             const ShardokEngine& guessedEngine,
-            const AIScoreCalculator& scorer,
+            const GameSettings::Getter& settingsGetter,
             int maxRepeatCount,
-            const CommandListSPtr& commands,
+            const std::vector<CommandProto>& commands,
             size_t commandIndex,
             int desiredDepth,
             ScoreValue currentUtility,

src/main/cpp/net/eagle0/shardok/ai/ShardokAIClient.cpp

@@ -10,27 +10,15 @@
 
 #define DEBUG_FLEE_DECISIONS
 
-// Enable to dump game state and debug tree to /tmp for debugging
-// #define ENABLE_MCTS_DEBUG_DUMP
-
-#ifdef ENABLE_MCTS_DEBUG_DUMP
-#include <chrono>
-#include <fstream>
-#include <iomanip>
-#include <sstream>
-#endif
+#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"
@@ -54,17 +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);
 
@@ -88,110 +70,38 @@ ShardokAIClient::ShardokAIClient(
     apdCache->ConsolidateThreadLocalCache_Racy();
 }
 
-void CheckCommand(const CommandSPtr &realCommand, const CommandSPtr &guessedCommand) {
-    // Verify that the AI's guessed state produces the same available commands as the real state.
-    // We only compare fields that uniquely identify a command - metadata fields like action_points,
-    // will_unhide, next_round_target_info are not part of command identity.
+void CheckCommand(const CommandProto &realDescriptor, const CommandProto &guessedDescriptor) {
+    string diff;
+    auto differencer = google::protobuf::util::MessageDifferencer();
+    differencer.IgnoreField(CommandProto::descriptor()->FindFieldByNumber(
+            CommandProto::kFollowUpCommandTypesFieldNumber));
+    differencer.ReportDifferencesToString(&diff);
+    if (!differencer.Compare(realDescriptor, guessedDescriptor)) {
+        printf("diff: %s\n\n", diff.c_str());
 
-    if (realCommand->GetCommandType() != guessedCommand->GetCommandType()) {
-        throw ShardokInternalErrorException("Command type mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetPlayerId() != guessedCommand->GetPlayerId()) {
-        throw ShardokInternalErrorException("Player ID mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetActorUnitId() != guessedCommand->GetActorUnitId()) {
-        throw ShardokInternalErrorException("Actor unit mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetTargetRow() != guessedCommand->GetTargetRow() ||
-        realCommand->GetTargetColumn() != guessedCommand->GetTargetColumn()) {
-        throw ShardokInternalErrorException(
-                "Target coordinates mismatch between real and guessed state");
-    }
-
-    // For commands with odds (like FLEE), verify the odds match
-    if (realCommand->HasOdds() != guessedCommand->HasOdds()) {
-        throw ShardokInternalErrorException(
-                "Odds presence mismatch between real and guessed state");
-    }
-
-    if (realCommand->HasOdds() && guessedCommand->HasOdds()) {
-        if (realCommand->GetOddsPercentile() != guessedCommand->GetOddsPercentile()) {
-            throw ShardokInternalErrorException(
-                    "Odds percentile mismatch between real and guessed state");
-        }
+        printf("Selected command descriptor\n%s\ndoes not match guessed\n%s\n\n",
+               realDescriptor.DebugString().c_str(),
+               guessedDescriptor.DebugString().c_str());
+        throw ShardokInternalErrorException("Illegal state for AI client");
     }
 }
 
 auto ShardokAIClient::StandardChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
     const auto settingsGetter = settings->GetGetter();
     const auto guessedEngine = ShardokEngine(settings, guessedState);
-    const auto guessedCommands = guessedEngine.GetAvailableCommandsForAIPlayer(playerId);
-    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);
+    // Calculate time budget based on game situation using new settings
+    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState);
 
-    // 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;
+    const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
+    const auto commandCount = guessedCommands.size();
 
-    // For fair evaluation: simulate leaves to opponent's turn start (maxSimulationFlips=1)
-    // This ensures all leaves are scored at the same game phase:
-    // - Leaves at playerFlips=0 (still my turn): simulate through END_TURN to playerFlips=1
-    // - Leaves at playerFlips=1 (opponent's turn): evaluate immediately
-    // Result: consistent comparison of "what happens after I end my turn"
-    // adjustedMCTSConfig.maxSimulatfixionFlips = 1;
-
-    // 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());
-    // Verify that the AI's guessed state produces the same available commands as reality
+    assert(commandCount == realAvailableCommands.size());
     for (size_t 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;
+        CheckCommand(realAvailableCommands[i], guessedCommands[i]);
     }
 
     // Determine strategy once for consistent scoring throughout iterative deepening
@@ -199,80 +109,23 @@ auto ShardokAIClient::StandardChooseCommandIndex(
     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) {
-#ifdef ENABLE_MCTS_DEBUG_DUMP
-        // Set unique debug dump path for each action using timestamp
-        const auto now = std::chrono::system_clock::now();
-        const auto nowTime = std::chrono::system_clock::to_time_t(now);
-        const auto nowMs =
-                std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()) %
-                1000;
-
-        std::ostringstream pathStream;
-        pathStream << "/tmp/shardok_debug_"
-                   << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
-                   << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
-                   << static_cast<int>(playerId) << ".txt";
-        adjustedMCTSConfig.debugDumpPath = pathStream.str();
-
-        // Also dump the game state to a file for reproduction
-        std::ostringstream statePathStream;
-        statePathStream << "/tmp/shardok_state_"
-                        << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
-                        << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
-                        << static_cast<int>(playerId) << ".bin";
-        const std::string statePath = statePathStream.str();
-
-        // Write the flatbuffer game state to file using SaveTo method
-        if (guessedState.SaveTo(statePath)) {
-            printf("Game state dumped to: %s\n", statePath.c_str());
-        } else {
-            printf("Failed to dump game state to: %s\n", statePath.c_str());
-        }
-#endif  // ENABLE_MCTS_DEBUG_DUMP
-
-        // 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;
@@ -288,12 +141,9 @@ auto ShardokAIClient::StandardChooseCommandIndex(
                    result.commandCountEvaluated,
                    result.availableCommandCount);
         }
-        const auto chosenCommandType =
-                (*realAvailableCommands)[result.chosenIndex]->GetCommandType();
-        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);
     }
@@ -304,20 +154,19 @@ auto ShardokAIClient::StandardChooseCommandIndex(
 auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
     if (const auto dismissCommand = std::ranges::find_if(
-                *realAvailableCommands,
-                [](const CommandSPtr &cmd) {
-                    return cmd->GetCommandType() ==
-                           net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
+                realAvailableCommands,
+                [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
+                    return cmd.type() == net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
                 });
-        dismissCommand == realAvailableCommands->end()) {
+        dismissCommand == realAvailableCommands.end()) {
         return StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
     } else {
         CommandChoiceResults results{};
         results.chosenIndex =
-                static_cast<size_t>(std::distance(realAvailableCommands->begin(), dismissCommand));
-        results.availableCommandCount = realAvailableCommands->size();
+                static_cast<size_t>(std::distance(realAvailableCommands.begin(), dismissCommand));
+        results.availableCommandCount = realAvailableCommands.size();
         results.depthAchieved = 1;          // Simple heuristic choice
         results.commandCountEvaluated = 1;  // Only evaluated one command type
         results.completionReason =
@@ -329,31 +178,24 @@ auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
 auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
-    const auto fleeCommand =
-            std::ranges::find_if(*realAvailableCommands, [](const CommandSPtr &cmd) {
-                return cmd->GetCommandType() == net::eagle0::shardok::common::FLEE_COMMAND;
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
+    const auto fleeCommand = std::ranges::find_if(
+            realAvailableCommands,
+            [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
+                return cmd.type() == net::eagle0::shardok::common::FLEE_COMMAND;
             });
 
-    if (fleeCommand == realAvailableCommands->end()) {
+    if (fleeCommand == realAvailableCommands.end()) {
         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->GetGetter(),
             guessedState,
             realAvailableCommands,
             fleeCommand,
-            maxRounds,
-            minimumFleeOddsThreshold,
-            desperateFleeThreshold,
 #ifdef DEBUG_FLEE_DECISIONS
             true  // Enable debug logging
 #else
@@ -364,7 +206,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
     if (fleeDecision.shouldFlee) {
         CommandChoiceResults results{};
         results.chosenIndex = fleeDecision.commandIndex;
-        results.availableCommandCount = realAvailableCommands->size();
+        results.availableCommandCount = realAvailableCommands.size();
         results.depthAchieved = 1;          // Heuristic choice
         results.commandCountEvaluated = 1;  // Only evaluated one command type
         results.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
@@ -378,7 +220,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
 auto ShardokAIClient::ChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateView &gsv,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
     static int typeChosenCount[net::eagle0::shardok::common::CommandType_MAX + 1];
     static int totalChoices = 0;
 
@@ -397,7 +239,7 @@ auto ShardokAIClient::ChooseCommandIndex(
         results = StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
     }
 
-    const auto chosenType = (*realAvailableCommands)[results.chosenIndex]->GetCommandType();
+    const auto chosenType = realAvailableCommands[results.chosenIndex].type();
     typeChosenCount[static_cast<int>(chosenType)]++;
     totalChoices++;
 
@@ -423,8 +265,8 @@ auto ShardokAIClient::ChooseCommandIndex(
 
 auto ShardokAIClient::ChooseCommandIndex(const ShardokEngine &engine) const
         -> CommandChoiceResults {
-    if (const auto &availableCommands = engine.GetAvailableCommandsForAIPlayer(playerId);
-        availableCommands->empty()) {
+    if (const auto &availableCommands = engine.GetAvailableCommandProtos(playerId, false);
+        availableCommands.empty()) {
         printf("no commands for player %d\n", playerId);
         throw ShardokInternalErrorException(
                 "Asked to choose a command, but there are none available");

src/main/cpp/net/eagle0/shardok/ai/ShardokAIClient.hpp

@@ -12,13 +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/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
 
 namespace shardok {
@@ -41,55 +38,42 @@ 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,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
     [[nodiscard]] auto LateRoundAttackerChooseCommandIndex(
             const GameSettingsSPtr& settings,
             const GameStateW& guessedState,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
     [[nodiscard]] auto FinalRoundAttackerChooseCommandIndex(
             const GameSettingsSPtr& settings,
             const GameStateW& guessedState,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
+
+    [[nodiscard]] auto ChooseCommandIndex(
+            const GameSettingsSPtr& settings,
+            const net::eagle0::shardok::api::GameStateView& gsv,
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
 
 public:
     explicit ShardokAIClient(
             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;
-
-    // Overload that works on copies of state - allows caller to release lock during AI thinking
-    [[nodiscard]] auto ChooseCommandIndex(
-            const GameSettingsSPtr& settings,
-            const net::eagle0::shardok::api::GameStateView& gsv,
-            const CommandListSPtr& realAvailableCommands) 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
 

src/main/cpp/net/eagle0/shardok/ai/mcts/BUILD.bazel

@@ -1,24 +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/cpp/net/eagle0/shardok/ai/mcts/CHANCE_NODES_DESIGN.md

@@ -1,813 +0,0 @@
-# Chance Nodes in MCTS for Shardok
-
-## Problem Statement
-
-### Current Behavior
-The current MCTS implementation uses a fixed roll (50th percentile) for all probabilistic outcomes during simulation. This creates several issues:
-
-1. **Binary success actions overvalued**: A START_FIRE command with 51% success is treated as always succeeding, making it appear better than it actually is.
-2. **Discontinuity at 50%**: Actions with 49% vs 51% success have dramatically different evaluations, when they should be similar.
-3. **Variable-outcome actions simplified**: Melee/archery attacks with damage ranges are evaluated at a single point rather than their full distribution.
-
-### Example Issue
-```
-START_FIRE with 51% success:
-- Current MCTS: Assumes always succeeds (roll = 50)
-- Reality: Succeeds 51% of time, fails 49% of time
-- Result: AI overvalues this action
-```
-
-### How Iterative Deepening Solves This
-The iterative deepening AI (see `AICommandEvaluator.cpp:352-393`) handles randomness correctly:
-
-```cpp
-// For actions with odds (binary success/fail):
-// 1. Evaluate success outcome with representative roll
-auto [successScore, successLookahead] = EvaluateWithRandomness(
-    ...,
-    std::make_shared<SequenceRandomGenerator>(std::vector{1.0 - successChance / 2.0})
-);
-
-// 2. Evaluate failure outcome with representative roll
-auto [failureScore, failureLookahead] = EvaluateWithRandomness(
-    ...,
-    std::make_shared<SequenceRandomGenerator>(std::vector{(1.0 - successChance) / 2.0})
-);
-
-// 3. Compute weighted average (expected value)
-immediateScore = std::lerp(failureScore, successScore, successChance);
-lookaheadScore = std::lerp(failureLookahead.get(), successLookahead.get(), successChance);
-```
-
-This is essentially an implicit form of chance nodes - evaluating both outcomes and weighting by probability.
-
-## Chance Nodes Concept
-
-### Classic MCTS with Chance Nodes
-
-In games with randomness (e.g., backgammon), MCTS uses two types of nodes:
-
-1. **Decision Nodes**: Player chooses an action
-   - Selection uses UCB formula (exploration/exploitation tradeoff)
-   - One child per legal action
-
-2. **Chance Nodes**: Nature determines outcome
-   - Selection uses expectation (weighted by probability)
-   - One child per possible outcome
-
-```
-Decision Node (Player to move)
-├─ Action A
-│  └─ Chance Node
-│     ├─ Outcome 1 (prob 0.3) → Game State
-│     ├─ Outcome 2 (prob 0.5) → Game State
-│     └─ Outcome 3 (prob 0.2) → Game State
-└─ Action B
-   └─ Deterministic → Game State
-```
-
-### Example: START_FIRE in Shardok
-
-**Current approach:**
-```
-State S
-└─ START_FIRE (roll=50)
-   └─ State S' (fire always starts)
-```
-
-**With chance nodes:**
-```
-State S
-└─ START_FIRE action
-   └─ Chance Node
-      ├─ Success (51%) → State S_success (fire started)
-      └─ Failure (49%) → State S_failure (no fire, vigor spent)
-```
-
-### Value Propagation
-
-**Decision nodes:** Maximize/minimize over children (depending on player)
-**Chance nodes:** Expected value over children (weighted by probability)
-
-```cpp
-// Decision node value (max for current player)
-value = max(child.value for child in children)
-
-// Chance node value (expectation)
-value = sum(prob[i] * child[i].value for i in outcomes)
-```
-
-## Implementation Approaches
-
-### Option 1: Explicit Chance Nodes (Full Implementation)
-
-Modify the MCTS tree structure to explicitly represent chance nodes.
-
-**Pros:**
-- Theoretically sound
-- Handles arbitrary outcome distributions
-- Clear separation of decision vs chance
-
-**Cons:**
-- Significant code changes
-- Larger tree (more memory)
-- More complex tree traversal
-
-**Tree Structure:**
-```cpp
-enum class NodeType { DECISION, CHANCE };
-
-struct MCTSNode {
-    NodeType type;
-
-    // For decision nodes
-    MCTSPlayerId player;
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    std::vector<std::unique_ptr<MCTSNode>> children;  // One per action
-
-    // For chance nodes
-    std::vector<double> probabilities;  // One per outcome
-    std::vector<std::unique_ptr<MCTSNode>> outcomes;  // One per outcome
-
-    double visits;
-    double totalReward;
-};
-```
-
-**Selection Phase:**
-```cpp
-MCTSNode* select(MCTSNode* node) {
-    while (!node->isLeaf()) {
-        if (node->type == DECISION) {
-            // Use UCB to select action
-            node = selectChildUCB(node);
-        } else {  // CHANCE node
-            // Use probability-weighted selection
-            node = selectOutcomeByProbability(node);
-        }
-    }
-    return node;
-}
-```
-
-**Backpropagation:**
-```cpp
-void backpropagate(MCTSNode* node, double reward) {
-    while (node != nullptr) {
-        node->visits++;
-        if (node->type == DECISION) {
-            node->totalReward += reward;  // Sum for averaging
-        } else {  // CHANCE node
-            node->totalReward += reward;  // Still sum, but averaged differently
-        }
-        node = node->parent;
-    }
-}
-```
-
-### Option 2: Implicit Chance Nodes (Hybrid Approach)
-
-Keep the current tree structure but sample outcomes during expansion/simulation.
-
-**Pros:**
-- Smaller code changes
-- More memory efficient
-- Easier to implement incrementally
-
-**Cons:**
-- Less theoretically pure
-- May need more visits to converge
-- Sampling introduces variance
-
-**Approach:**
-```cpp
-// During expansion
-std::unique_ptr<MCTSGameState> expand(
-    const MCTSGameState& state,
-    const MCTSAction& action
-) {
-    if (action.isDeterministic()) {
-        return applyActionDeterministic(state, action);
-    } else {
-        // Sample an outcome based on probabilities
-        auto outcome = sampleOutcome(action);
-        return applyActionWithOutcome(state, action, outcome);
-    }
-}
-```
-
-**For binary actions (e.g., START_FIRE):**
-```cpp
-// Expand creates one of two children based on sampling
-if (random() < successProbability) {
-    return applySuccess(state, action);
-} else {
-    return applyFailure(state, action);
-}
-
-// Over many visits, visit ratio will approach probability ratio
-// E.g., 51% success action will have ~51% success children, 49% failure children
-```
-
-### Option 3: Determinized Sampling (Simplest)
-
-Pre-sample all random outcomes at the start of each simulation rollout.
-
-**Pros:**
-- Minimal code changes
-- Easy to understand
-- Works with existing tree structure
-
-**Cons:**
-- May converge slowly
-- Doesn't explicitly represent probability
-- Can waste simulations on unlikely outcomes
-
-**Approach:**
-```cpp
-// At start of each simulation
-std::vector<double> rollSequence = generateRollSequence(maxDepth);
-
-// Use sequence during simulation
-auto state = rootState;
-for (int depth = 0; depth < maxDepth; depth++) {
-    auto action = selectAction(state);
-    state = applyAction(state, action, rollSequence[depth]);
-}
-```
-
-## Recommended Approach: Progressive Enhancement
-
-Implement in phases to manage complexity:
-
-### Phase 1: Binary Chance Nodes (Explicit)
-
-Start with actions that have clear success/failure outcomes (e.g., START_FIRE, EXTINGUISH_FIRE, RAISE_DEAD):
-
-1. Identify binary actions (commands with `HasOdds()`)
-2. Add chance node support for these actions only
-3. Modify tree expansion to create chance nodes
-4. Update selection/backpropagation for chance nodes
-
-**Implementation:**
-```cpp
-// In ShardokGameEngine::getLegalActions()
-// Mark which actions require chance nodes
-struct ActionMetadata {
-    std::unique_ptr<MCTSAction> action;
-    bool requiresChanceNode;
-    double successProbability;  // If requiresChanceNode = true
-};
-```
-
-```cpp
-// In tree expansion
-if (action.requiresChanceNode) {
-    // Create chance node with two children
-    auto chanceNode = std::make_unique<MCTSNode>(CHANCE);
-    chanceNode->probabilities = {successProb, 1.0 - successProb};
-
-    // Expand both outcomes
-    chanceNode->outcomes.push_back(applySuccess(state, action));
-    chanceNode->outcomes.push_back(applyFailure(state, action));
-
-    return chanceNode;
-} else {
-    // Normal deterministic expansion
-    return applyAction(state, action);
-}
-```
-
-### Phase 2: Multi-Outcome Actions
-
-Extend to actions with multiple outcomes (e.g., melee damage ranges):
-
-1. Discretize continuous distributions into buckets
-2. For melee/archery, use 3-5 representative damage values (min, low, avg, high, max)
-3. Compute probabilities for each bucket
-4. Create chance nodes with multiple children
-
-**Example: Melee Attack**
-```cpp
-// Instead of sampling full damage distribution,
-// use representative values
-struct DamageBucket {
-    int damageValue;  // Representative damage
-    double probability;  // Probability of this range
-};
-
-// For a melee attack that can deal 10-20 damage
-std::vector<DamageBucket> buckets = {
-    {10, 0.1},  // Min damage (unlucky)
-    {13, 0.2},  // Low damage
-    {15, 0.4},  // Average damage
-    {17, 0.2},  // High damage
-    {20, 0.1}   // Max damage (lucky)
-};
-```
-
-### Phase 3: Optimization
-
-Once chance nodes work correctly:
-
-1. Add transposition table support for chance nodes
-2. Optimize memory layout
-3. Consider progressive widening (start with 2 outcomes, expand to more if visited often)
-4. Profile and tune
-
-## Design Decisions
-
-### How to Represent Outcomes?
-
-**Option A: Explicit state copies**
-```cpp
-struct ChanceNode {
-    std::vector<std::unique_ptr<MCTSGameState>> outcomeStates;
-    std::vector<double> probabilities;
-};
-```
-
-**Option B: Lazy evaluation**
-```cpp
-struct ChanceNode {
-    MCTSGameState baseState;
-    MCTSAction action;
-    std::vector<int> outcomeRolls;  // Roll values for each outcome
-    std::vector<double> probabilities;
-
-    // Compute state on-demand
-    MCTSGameState getOutcome(size_t index) {
-        return applyActionWithRoll(baseState, action, outcomeRolls[index]);
-    }
-};
-```
-
-**Recommendation:** Option B - lazy evaluation. Only materialize states when visited.
-
-### How Many Outcomes per Action?
-
-**Binary actions (START_FIRE, etc.):**
-- Exactly 2 outcomes (success/fail)
-- Use exact probabilities from `GetOddsPercentile()`
-
-**Damage actions (MELEE, ARCHERY):**
-- Start with 3 outcomes (low/med/high)
-- Can expand to 5 if needed for accuracy
-- Use representative rolls: 10th, 50th, 90th percentile
-
-**Complex actions (METEOR):**
-- Consider 2-3 outcomes initially
-- Can model as "hits N enemies" for N in {0, 1, 2, 3+}
-
-### How to Handle Transposition Table?
-
-**Challenge:** Same state can be reached via different chance outcomes
-
-**Solution:**
-- Hash based on game state only (not the path taken)
-- When looking up, return cached evaluation if state matches
-- This is already how transposition tables work!
-
-```cpp
-// Current approach works fine:
-auto hash = computeHash(gameState);  // Doesn't include how we got here
-if (auto cached = transpositionTable.lookup(hash)) {
-    return cached->value;
-}
-```
-
-### Selection at Chance Nodes
-
-**During tree traversal:**
-```cpp
-size_t selectOutcome(const ChanceNode& node) {
-    // Option 1: Sample by probability (introduces variance)
-    double r = random();
-    double cumulative = 0.0;
-    for (size_t i = 0; i < node.probabilities.size(); i++) {
-        cumulative += node.probabilities[i];
-        if (r < cumulative) return i;
-    }
-
-    // Option 2: Round-robin weighted by visit count vs probability
-    // (Explore under-visited outcomes more)
-    size_t leastVisited = findMostUnderExploredOutcome(node);
-    return leastVisited;
-}
-```
-
-**Recommendation:** Use Option 2 to ensure all outcomes get explored proportionally.
-
-## Integration Points
-
-### Modified Functions
-
-1. **`ShardokGameEngine::getLegalActions()`**
-   - Add metadata about which actions need chance nodes
-   - Return action + probability information
-
-2. **`ShardokGameEngine::applyAction()`**
-   - For binary actions, return both possible outcomes
-   - Or: take an explicit outcome index parameter
-
-3. **`AbstractMCTSAI::selection()`**
-   - Handle chance nodes differently from decision nodes
-   - Use probability-weighted selection instead of UCB
-
-4. **`AbstractMCTSAI::expand()`**
-   - Create chance node children for probabilistic actions
-   - May create multiple child nodes per action
-
-5. **`AbstractMCTSAI::backpropagate()`**
-   - Update all nodes in path (both decision and chance)
-   - Value calculation already handles this correctly (just averages)
-
-### New Functions Needed
-
-```cpp
-// In ShardokGameEngine
-struct ChanceOutcome {
-    int roll;  // The dice roll that produces this outcome
-    double probability;  // Probability of this outcome
-};
-
-std::vector<ChanceOutcome> getChanceOutcomes(const MCTSAction& action) const;
-```
-
-```cpp
-// In MCTSNode
-bool isChanceNode() const;
-const std::vector<double>& getOutcomeProbabilities() const;
-```
-
-## Testing Strategy
-
-### Unit Tests
-
-1. **Binary action correctness**
-   ```cpp
-   TEST(ChanceNodes, BinaryActionExpectedValue) {
-       // START_FIRE with 60% success
-       // Run MCTS with chance nodes
-       // Verify: visits to success ~= 60%, visits to failure ~= 40%
-       // Verify: expected value matches manual calculation
-   }
-   ```
-
-2. **Comparison with iterative deepening**
-   ```cpp
-   TEST(ChanceNodes, MatchesIterativeDeepening) {
-       // Same position, both AIs
-       // Should choose same action
-       // Scores should be similar (within variance)
-   }
-   ```
-
-3. **Transposition table with chance**
-   ```cpp
-   TEST(ChanceNodes, TranspositionConsistency) {
-       // Two paths to same state via different chance outcomes
-       // Should reuse cached evaluation
-   }
-   ```
-
-### Integration Tests
-
-1. Compare MCTS with/without chance nodes on test positions
-2. Verify that chance nodes reduce overvaluation of marginal actions
-3. Performance test: measure slowdown (expect 1.5-2x for binary actions)
-
-### Real-World Validation
-
-Run the problematic START_FIRE scenario:
-- With current MCTS: Should overvalue START_FIRE
-- With chance nodes: Should correctly weight success/failure
-- Expected: END_TURN should get significantly more visits
-
-## Performance Considerations
-
-### Memory Overhead
-
-**Per chance node:**
-- Probability vector: `N * sizeof(double)` (N = number of outcomes)
-- Outcome children: `N * sizeof(unique_ptr)`
-- For binary: ~32 bytes per chance node
-
-**Estimate:**
-- Current tree: ~100K nodes per search
-- With chance nodes: ~150K nodes (50% actions are probabilistic)
-- Extra memory: ~50K * 32 bytes = ~1.6 MB
-- **Acceptable overhead**
-
-### Computational Overhead
-
-**Per simulation:**
-- Current: 1 path through tree
-- With chance nodes: Still 1 path, but more nodes
-- Overhead: ~20-30% (more node visits)
-
-**Mitigation:**
-- Transposition table helps (same states via different paths)
-- Progressive widening (start with 2 outcomes, expand if visited often)
-- Lazy state evaluation (don't materialize until needed)
-
-### Convergence Speed
-
-Chance nodes may require more visits to converge because:
-- More children per action (branching factor increases)
-- Outcomes need proportional exploration
-
-**Mitigation:**
-- Use visit count thresholds before expanding chance nodes
-- Consider progressive widening (UCT-ProgressiveWidening)
-
-## Migration Path
-
-### Step 1: Infrastructure (1-2 days)
-- Add `NodeType` enum and metadata to MCTSNode
-- Implement chance node creation (without using them yet)
-- Add unit tests for chance node structure
-
-### Step 2: Binary Actions (2-3 days)
-- Identify all binary success/fail actions
-- Modify expansion to create chance nodes for these
-- Update selection/backpropagation
-- Test on START_FIRE scenario
-
-### Step 3: Integration Testing (1 day)
-- Run full MCTS tests with chance nodes enabled
-- Compare with iterative deepening on test positions
-- Validate that it fixes the START_FIRE overvaluation
-
-### Step 4: Multi-Outcome Actions (2-3 days)
-- Implement damage bucketing for MELEE/ARCHERY
-- Create chance nodes with 3-5 outcomes
-- Test on combat scenarios
-
-### Step 5: Optimization (1-2 days)
-- Profile performance
-- Add progressive widening if needed
-- Tune outcome granularity
-
-### Step 6: Documentation & Cleanup (1 day)
-- Document the new approach
-- Clean up code
-- Add comprehensive tests
-
-## Alternative: Simpler Hybrid Approach
-
-If full chance nodes are too complex, consider a hybrid:
-
-1. **Keep current tree structure** (no explicit chance nodes)
-2. **During expansion:** Sample outcome and create one child
-3. **Over many simulations:** Statistics converge to correct probabilities
-4. **Add outcome tracking:** Store "which outcome" in edge/node metadata
-
-**Example:**
-```cpp
-// Expansion samples an outcome
-auto expand(state, action) {
-    if (action.hasBinaryOutcome()) {
-        // Sample once
-        bool success = (random() < successProb);
-        // Store which outcome this edge represents
-        edge.metadata.outcome = success ? OUTCOME_SUCCESS : OUTCOME_FAILURE;
-        return applyWithOutcome(state, action, success);
-    }
-}
-
-// Selection prioritizes under-explored outcomes
-auto selectChild(node) {
-    // Find action where outcome distribution is unbalanced
-    // E.g., 60% success action should have ~60% success children
-    // If we have 80% success children, prefer exploring failure
-}
-```
-
-This is simpler but less theoretically sound. It's a reasonable starting point if full chance nodes prove too complex.
-
-## Comparison: Chance Nodes vs Open-Loop MCTS
-
-### What is Open-Loop MCTS?
-
-**Open-loop MCTS** (also called "determinization MCTS" or "information set MCTS") is an alternative approach to handling randomness:
-
-1. At the **start of each simulation**, sample all random outcomes needed for that simulation
-2. Play out the entire simulation using those fixed random values
-3. Different simulations use different random seeds
-4. The tree structure doesn't explicitly model randomness - it's all in the rollouts
-
-**Example implementation:**
-```cpp
-// At start of simulation
-std::vector<double> rollSequence = sampleRolls(maxDepth);  // Pre-sample all rolls
-
-// During simulation
-MCTSNode* node = root;
-for (int depth = 0; depth < maxDepth; depth++) {
-    Action action = selectAction(node);
-    node = applyAction(node, action, rollSequence[depth]);  // Use pre-sampled roll
-}
-```
-
-### Open-Loop MCTS for Shardok
-
-**How it would work:**
-```cpp
-// Each simulation samples a "possible world"
-void simulate(MCTSNode* root) {
-    // Sample random rolls for this simulation
-    auto rolls = generateRollSequence();  // e.g., {0.45, 0.78, 0.23, ...}
-
-    // Play out simulation using these fixed rolls
-    auto state = root->state;
-    for (int depth = 0; depth < maxDepth; depth++) {
-        auto action = selectAction(state);
-        state = applyAction(state, action, rolls[depth]);
-    }
-
-    double reward = evaluate(state);
-    backpropagate(root, reward);
-}
-```
-
-**Would this fix the START_FIRE issue?**
-
-**Yes** - partially. Different simulations would see different outcomes:
-- Some simulations: START_FIRE succeeds (roll < 0.51)
-- Some simulations: START_FIRE fails (roll >= 0.51)
-- Over many simulations, the action's value would approach the expected value
-
-**However**, it's less efficient than chance nodes because:
-- Needs MORE simulations to converge
-- Wastes effort exploring unlikely scenarios equally with likely ones
-- Doesn't explicitly guide exploration based on probability
-
-### Detailed Comparison
-
-| Aspect | Chance Nodes (Closed-Loop) | Open-Loop MCTS | Current (Fixed Roll) |
-|--------|---------------------------|----------------|----------------------|
-| **Randomness Handling** | Explicit in tree structure | Implicit in simulation sampling | Fixed roll=50 |
-| **Convergence Speed** | Fast - probabilities guide search | Slower - needs more samples | N/A (wrong answer) |
-| **Memory Usage** | Higher (more nodes) | Lower (no extra nodes) | Lowest |
-| **Implementation Complexity** | High (tree structure changes) | Medium (sampling layer) | Low (current) |
-| **Theoretical Soundness** | Highest (models true game tree) | Medium (approximation via sampling) | Low (assumes fixed outcome) |
-| **START_FIRE Fix** | ✅ Yes, accurately | ✅ Yes, eventually | ❌ No |
-| **Efficiency** | Most efficient per simulation | Less efficient (wasted samples) | Efficient but wrong |
-| **Handles Hidden Information** | Poor | Excellent | N/A |
-
-### When to Prefer Each Approach
-
-**Prefer Chance Nodes when:**
-- Randomness outcomes are discrete and enumerable (e.g., binary success/fail)
-- Probabilities are known precisely
-- You want fastest convergence to correct answer
-- Game tree is the primary concern (no hidden information)
-- **This is Shardok's situation** ✅
-
-**Prefer Open-Loop when:**
-- Randomness is continuous and high-dimensional
-- Hidden information or imperfect information is present
-- Simplicity is paramount
-- You can afford many simulations
-- Used in games like poker, bridge, Skat
-
-### Why Chance Nodes are Better for Shardok
-
-1. **Discrete outcomes**: Most Shardok randomness is binary (success/fail) or small discrete sets (damage ranges)
-   - START_FIRE: 2 outcomes (success/fail)
-   - MELEE: Can bucket into 3-5 damage ranges
-   - Not continuous - perfect fit for chance nodes
-
-2. **Known probabilities**: We have exact probabilities from `GetOddsPercentile()`
-   - Chance nodes can use exact probabilities
-   - Open-loop just samples blindly
-
-3. **No hidden information**: Shardok is perfect information (all units visible to AI)
-   - Chance nodes' main weakness doesn't apply
-   - Open-loop's main strength doesn't help
-
-4. **Convergence matters**: Limited simulation budget
-   - Need to converge quickly
-   - Chance nodes achieve this better
-
-5. **Existing infrastructure**: We already have deterministic state transitions
-   - Adding chance nodes builds on what we have
-   - Open-loop would need different rollout structure
-
-### Performance Analysis
-
-**Chance Nodes:**
-```
-Time per simulation: 1.3x current
-Simulations needed: 10,000 to converge
-Total time: 13,000x units
-
-Memory: 1.5x current (extra chance nodes)
-```
-
-**Open-Loop:**
-```
-Time per simulation: 1.0x current (same as now)
-Simulations needed: 30,000 to converge (more variance)
-Total time: 30,000x units
-
-Memory: 1.0x current (no extra nodes)
-```
-
-**Result:** Chance nodes are **2.3x faster overall** despite being slower per simulation, because they converge with fewer simulations.
-
-### Hybrid Approach: Best of Both Worlds?
-
-Could we combine them?
-
-**Idea:** Use chance nodes for high-probability branches, open-loop for rare events
-```cpp
-if (probability > 0.1 && outcomeCount <= 5) {
-    // Use explicit chance node
-    createChanceNode(outcomes, probabilities);
-} else {
-    // Use open-loop sampling
-    sampleOutcome();
-}
-```
-
-**Verdict:** Probably not worth the complexity. Shardok's randomness is simple enough that chance nodes handle everything well.
-
-### Recommendation for Shardok
-
-**Use Chance Nodes**, specifically:
-
-1. **Phase 1:** Binary actions (START_FIRE, RAISE_DEAD, etc.)
-   - 2 outcomes, exact probabilities
-   - Biggest bang for buck
-
-2. **Phase 2:** Damage ranges (MELEE, ARCHERY)
-   - 3-5 buckets
-   - Still manageable
-
-3. **If needed:** Could fall back to open-loop for complex actions
-   - E.g., METEOR with many possible outcomes
-   - But likely unnecessary
-
-### Why Not Open-Loop?
-
-While open-loop would eventually fix the START_FIRE issue, it has significant downsides for Shardok:
-
-1. **Slower convergence**: Needs 2-3x more simulations
-2. **Doesn't leverage known probabilities**: We have exact odds, why ignore them?
-3. **Less interpretable**: Harder to debug why AI chose an action
-4. **Doesn't align with iterative deepening**: We want MCTS to match the proven algorithm
-
-The only advantage of open-loop (simplicity) is outweighed by chance nodes' efficiency and correctness.
-
-### Could We Use Current Approach + Better Sampling?
-
-**Idea:** Keep fixed rolls but use different rolls per simulation?
-
-```cpp
-// Instead of always roll=50
-double roll = random();  // Different each simulation
-```
-
-**Problem:** This is essentially open-loop without the tree!
-- Even slower to converge
-- Tree doesn't learn the outcome probabilities
-- Worst of both worlds
-
-**Verdict:** No, this doesn't help. If we're going to sample, do it properly (open-loop). Otherwise, use chance nodes.
-
-### Final Verdict
-
-**For Shardok, chance nodes are clearly superior:**
-
-- ✅ Faster convergence (2-3x vs open-loop)
-- ✅ Leverages exact probabilities
-- ✅ Perfect fit for discrete outcomes
-- ✅ Aligns with iterative deepening approach
-- ✅ Better debuggability and interpretability
-- ❌ More complex implementation (but manageable)
-
-Open-loop would be a fallback if chance nodes prove too difficult, but given the benefits and the bounded complexity (only binary and small discrete outcomes), chance nodes are the right choice.
-
-## Conclusion
-
-Implementing chance nodes will fix the overvaluation of marginal probabilistic actions like START_FIRE with 51% success. The recommended approach is:
-
-1. Start with **explicit chance nodes for binary actions**
-2. Use **lazy state evaluation** to minimize memory
-3. **Progressive enhancement** - binary first, then multi-outcome
-4. Compare with iterative deepening to validate correctness
-
-Expected benefits:
-- More accurate action evaluation
-- Better handling of probabilistic outcomes
-- Closer alignment with theoretical MCTS
-- Fixes the START_FIRE issue without tuning heuristics
-
-Expected costs:
-- ~20-30% slower per simulation (more nodes)
-- ~1-2MB extra memory
-- ~1-2 weeks development time
-
-The benefits significantly outweigh the costs for a more theoretically sound and accurate AI.

src/main/cpp/net/eagle0/shardok/ai/mcts/ShardokMCTSAI.cpp

@@ -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

src/main/cpp/net/eagle0/shardok/ai/mcts/ShardokMCTSAI.hpp

@@ -1,71 +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"
-#pragma clang diagnostic pop
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-
-class ShardokMCTSAI {
-public:
-    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

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/BUILD.bazel

@@ -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/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//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",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-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/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokAction.cpp

@@ -1,88 +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::mcts {
-
-// Constructor: extract and store just the essential fields
-ShardokAction::ShardokAction(
-        size_t index,
-        CommandType type,
-        PlayerId player,
-        int actorId,
-        int targetRow,
-        int targetCol,
-        bool hasOdds)
-    : commandIndex_(index),
-      type_(type),
-      player_(player),
-      actorId_(actorId),
-      targetRow_(targetRow),
-      targetCol_(targetCol),
-      hasOdds_(hasOdds) {}
-
-std::string ShardokAction::getDescription() const {
-    std::stringstream ss;
-
-    // Show player
-    ss << "P" << static_cast<int>(player_) << " ";
-
-    ss << net::eagle0::shardok::common::CommandType_Name(type_);
-
-    if (actorId_ >= 0) { ss << " Unit:" << actorId_; }
-
-    if (targetRow_ >= 0 && targetCol_ >= 0) {
-        ss << " @(" << targetRow_ << "," << targetCol_ << ")";
-    }
-
-    return ss.str();
-}
-
-std::unique_ptr<MCTSAction> ShardokAction::clone() const {
-    return std::make_unique<ShardokAction>(
-            commandIndex_,
-            type_,
-            player_,
-            actorId_,
-            targetRow_,
-            targetCol_,
-            hasOdds_);
-}
-
-bool ShardokAction::equals(const MCTSAction& other) const {
-    const auto* shardokOther = dynamic_cast<const ShardokAction*>(&other);
-    if (!shardokOther) { return false; }
-
-    // Compare by index only - actions from same command list are uniquely identified by index
-    return commandIndex_ == shardokOther->commandIndex_;
-}
-
-bool ShardokAction::requiresChanceNode() const {
-    // Actions with probabilistic outcomes require chance nodes:
-    // 1. Binary success/failure actions (hasOdds_): START_FIRE, FEAR, etc.
-    // 2. END_TURN: random effects (fire spread, weather changes)
-    // 3. Combat actions: roll affects damage dealt (MELEE, ARCHERY, CHARGE, DUEL)
-    if (hasOdds_) { return true; }
-
-    using namespace net::eagle0::shardok::common;
-    switch (type_) {
-        case END_TURN_COMMAND:
-        case MELEE_COMMAND:
-        case ARCHERY_COMMAND:
-        case CHARGE_COMMAND:
-        case CHALLENGE_DUEL_COMMAND:
-        case REDUCE_COMMAND: return true;
-        default: return false;
-    }
-}
-
-}  // namespace shardok::mcts

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokAction.hpp

@@ -1,61 +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"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-#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::mcts {
-
-class ShardokAction : public MCTSAction {
-public:
-    using CommandType = net::eagle0::shardok::common::CommandType;
-
-    // Constructor: store just the essential fields (no proto, no pointer)
-    ShardokAction(
-            size_t index,
-            CommandType type,
-            PlayerId player,
-            int actorId,
-            int targetRow,
-            int targetCol,
-            bool hasOdds);
-
-    // 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;
-    [[nodiscard]] bool requiresChanceNode() const override;
-
-    // Shardok-specific accessors (O(1), no allocations)
-    [[nodiscard]] int getType() const { return static_cast<int>(type_); }
-    [[nodiscard]] PlayerId getPlayer() const { return player_; }
-    [[nodiscard]] int getActorId() const { return actorId_; }
-    [[nodiscard]] std::pair<int, int> getTarget() const { return {targetRow_, targetCol_}; }
-
-private:
-    // Store only essential fields (~25 bytes, all POD, cache-friendly)
-    size_t commandIndex_;
-    CommandType type_;
-    PlayerId player_;
-    int actorId_;    // -1 if no actor
-    int targetRow_;  // -1 if no target
-    int targetCol_;  // -1 if no target
-    bool hasOdds_;   // true if command has probabilistic outcome
-};
-
-}  // namespace shardok::mcts
-
-#endif  // EAGLE0_SHARDOK_ACTION_HPP

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokGameEngine.cpp

@@ -1,628 +0,0 @@
-//
-// Shardok-specific game engine adapter implementation
-//
-
-#include "ShardokGameEngine.hpp"
-
-#include <algorithm>
-#include <chrono>
-#include <numeric>
-
-#include "ShardokAction.hpp"
-#include "ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.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/ShardokException.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-// Shared cache for legal actions (uses lock-free parallel hash map for thread safety)
-// Using 8 submaps to reduce contention with 16 MCTS threads
-gtl::parallel_flat_hash_map<
-        uint64_t,
-        ShardokGameEngine::LegalActionsCache,
-        std::hash<uint64_t>,
-        std::equal_to<uint64_t>,
-        std::allocator<std::pair<const uint64_t, ShardokGameEngine::LegalActionsCache>>,
-        8,
-        std::mutex>
-        ShardokGameEngine::legalActionsCache_;
-std::atomic<uint64_t> ShardokGameEngine::cacheHits_{0};
-std::atomic<uint64_t> ShardokGameEngine::cacheMisses_{0};
-std::atomic<uint64_t> ShardokGameEngine::timeInHashComputation_{0};
-std::atomic<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,
-        double deterministicRoll) 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);
-    }
-
-    // Create deterministic random generator if a specific roll is requested
-    // deterministicRoll of -1.0 (default) means use random generator
-    // Any other value (including negative) creates a deterministic generator
-    // For open-ended percentile commands, we compute a sequence of values that will
-    // produce the desired final result through the normal open-ended mechanics
-    std::shared_ptr<::RandomGenerator> randomGen = nullptr;
-    constexpr double kNoRollSentinel = -1.0;
-    if (deterministicRoll != kNoRollSentinel) {
-        std::vector<double> sequence;
-
-        if (deterministicRoll >= 5.0 && deterministicRoll <= 95.0) {
-            // Normal range: single value works directly
-            sequence = {deterministicRoll / 100.0};
-        } else if (deterministicRoll < 5.0) {
-            // Need open-ended LOW result (e.g., -100 for guaranteed success)
-            // OpenEndedPercentile: if initial < 5, returns initial - OpenEndedHighImpl(0, 4)
-            // We want: initial - accumulated = deterministicRoll
-            // Use initial = 2 (clearly < 5), so accumulated = 2 - deterministicRoll
-            constexpr double kInitialLow = 2.0;
-            sequence = {kInitialLow / 100.0};
-            // OpenEndedHighImpl accumulates rolls until one < 95
-            // Split accumulated into rolls: 96 (continues) + remaining (stops)
-            double remaining = kInitialLow - deterministicRoll;
-            while (remaining > 95.0) {
-                sequence.push_back(0.96);  // 96 > 95, continues accumulation
-                remaining -= 96.0;
-            }
-            sequence.push_back(remaining / 100.0);  // Final roll < 95, stops
-        } else {
-            // Need open-ended HIGH result (e.g., 150 for guaranteed failure)
-            // OpenEndedPercentile: if initial > 95, returns OpenEndedHighImpl(initial, 4)
-            // OpenEndedHighImpl accumulates rolls until one < 95
-            constexpr double kInitialHigh = 96.0;
-            sequence = {kInitialHigh / 100.0};
-            double remaining = deterministicRoll - kInitialHigh;
-            while (remaining > 95.0) {
-                sequence.push_back(0.96);
-                remaining -= 96.0;
-            }
-            sequence.push_back(remaining / 100.0);
-        }
-
-        randomGen = std::make_shared<::SequenceRandomGenerator>(sequence);
-    }
-
-    engine->PostCommand(currentPlayer, shardokAction->getIndex(), randomGen);
-
-    // Create and return the new state
-    auto newState = std::make_unique<ShardokGameState>(
-            engine->GetCurrentGameState(),
-            scoreCalculator_,
-            gameSettings_.get(),
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            *apdCache_,
-            *alCache_,
-            criticalTileCoords_);
-
-    // Cache the engine on the new state so score() can use it for END_TURN normalization
-    // The engine's command list may be stale after the action was applied, but that's OK -
-    // we'll refresh it when we call GetAvailableCommandsForAIPlayer() in score()
-    newState->setCachedEngine(engine);
-
-    // 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_.fetch_add(
-            std::chrono::duration_cast<std::chrono::microseconds>(hashEnd - hashStart).count(),
-            std::memory_order_relaxed);
-
-    // Check transposition table for cached legal actions
-    if (auto it = legalActionsCache_.find(stateHash); it != legalActionsCache_.end()) {
-        cacheHits_.fetch_add(1, std::memory_order_relaxed);
-
-        // 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);
-
-                // Extract essential fields directly from command (no proto conversion!)
-                actions.push_back(std::make_unique<ShardokAction>(
-                        origIdx,
-                        cmd->GetCommandType(),
-                        cmd->GetPlayerId(),
-                        cmd->GetActorUnitId(),
-                        cmd->GetTargetRow(),
-                        cmd->GetTargetColumn(),
-                        cmd->HasOdds()));
-            }
-        }
-
-        // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
-        const std::vector<double> weights = getActionWeights(actions, state);
-
-        std::vector<size_t> sortedIndices(actions.size());
-        std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
-
-        std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
-            return weights[a] > weights[b];
-        });
-
-        std::vector<std::unique_ptr<MCTSAction>> sortedActions;
-        sortedActions.reserve(actions.size());
-        for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
-
-        return sortedActions;
-    }
-
-    cacheMisses_.fetch_add(1, std::memory_order_relaxed);
-
-    // 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);
-
-            // Extract essential fields directly from command (no proto conversion!)
-            actions.push_back(std::make_unique<ShardokAction>(
-                    idx,
-                    cmd->GetCommandType(),
-                    cmd->GetPlayerId(),
-                    cmd->GetActorUnitId(),
-                    cmd->GetTargetRow(),
-                    cmd->GetTargetColumn(),
-                    cmd->HasOdds()));
-        }
-    }
-
-    // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
-    // This is critical when maxPlayerFlips is low (e.g., 1), as only the first few actions
-    // get explored deeply. Original indices are preserved in ShardokAction::getIndex()
-    const std::vector<double> weights = getActionWeights(actions, state);
-
-    // Create index vector for sorting
-    std::vector<size_t> sortedIndices(actions.size());
-    std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
-
-    // Sort indices by weight (descending)
-    std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
-        return weights[a] > weights[b];
-    });
-
-    // Reorder actions according to sorted indices
-    std::vector<std::unique_ptr<MCTSAction>> sortedActions;
-    sortedActions.reserve(actions.size());
-    for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
-    actions = std::move(sortedActions);
-
-    const auto actionsEnd = std::chrono::high_resolution_clock::now();
-    timeInLegalActionsComputation_.fetch_add(
-            std::chrono::duration_cast<std::chrono::microseconds>(actionsEnd - actionsStart)
-                    .count(),
-            std::memory_order_relaxed);
-
-    // 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
-    // Use lazy_emplace_l to ensure thread-safe insertion (locks the bucket during construction)
-    legalActionsCache_.lazy_emplace_l(
-            stateHash,
-            [&](typename decltype(legalActionsCache_)::value_type& v) {
-                // Update existing entry
-                v.second.filteredIndices = filteredIndices;
-                v.second.engine = engine;
-            },
-            [&](const typename decltype(legalActionsCache_)::constructor& ctor) {
-                // Create new entry
-                ctor(stateHash, LegalActionsCache{filteredIndices, engine});
-            });
-
-    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");
-    }
-
-    // Get cached engine and command list for looking up command protos
-    auto cachedEngine = shardokState->getCachedEngine();
-    if (!cachedEngine) {
-        throw MCTSInternalError(
-                "ShardokGameEngine::getActionWeights called with state that has no cached engine");
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-    const CommandListSPtr commands = cachedEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-    // Determine if current player is defender (not root player!)
-    // During simulation we need to use the correct perspective for action weighting
-    bool currentPlayerIsDefender = false;
-    const auto& gameState = shardokState->getShardokState();
-    for (const auto* pi : *gameState->player_infos()) {
-        if (pi->player_id() == currentPlayer) {
-            currentPlayerIsDefender = pi->is_defender();
-            break;
-        }
-    }
-
-    // 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");
-        }
-
-        // Look up command proto from cached engine using action's index
-        const size_t cmdIndex = shardokAction->getIndex();
-        if (cmdIndex >= commands->size()) {
-            throw MCTSInternalError(
-                    "ShardokGameEngine::getActionWeights: action index out of bounds");
-        }
-
-        const auto& cmd = commands->at(cmdIndex);
-
-        weights.push_back(AIHeuristicWeighting::GetCommandWeight(
-                cmd->GetCommandType(),
-                cmd->GetActorUnitId(),
-                cmd->GetPlayerId(),
-                Coords{cmd->GetTargetRow(), cmd->GetTargetColumn()},
-                gameState,
-                castleCoords_,
-                apdCache_,
-                currentPlayerIsDefender,  // Use current player's role, not root player's!
-                [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 hits = cacheHits_.load(std::memory_order_relaxed);
-    const uint64_t misses = cacheMisses_.load(std::memory_order_relaxed);
-    const uint64_t hashTime = timeInHashComputation_.load(std::memory_order_relaxed);
-    const uint64_t actionsTime = timeInLegalActionsComputation_.load(std::memory_order_relaxed);
-    const uint64_t totalLookups = hits + misses;
-
-    if (totalLookups > 0) {
-        const double hitRate = static_cast<double>(hits) / static_cast<double>(totalLookups);
-        const double avgHashTimeUs =
-                static_cast<double>(hashTime) / static_cast<double>(totalLookups);
-        const double avgActionsTimeUs =
-                misses > 0 ? static_cast<double>(actionsTime) / static_cast<double>(misses) : 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>(hits),
-               static_cast<unsigned long long>(misses),
-               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",
-               hashTime / 1000.0,
-               actionsTime / 1000.0);
-
-        // Calculate if transposition table is worth it
-        const double timeWithCache = hashTime + actionsTime;
-        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_.store(0, std::memory_order_relaxed);
-    cacheMisses_.store(0, std::memory_order_relaxed);
-    timeInHashComputation_.store(0, std::memory_order_relaxed);
-    timeInLegalActionsComputation_.store(0, std::memory_order_relaxed);
-}
-
-ChanceOutcomeInfo ShardokGameEngine::getBinaryOutcomeInfo(
-        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) {
-        throw ShardokInternalErrorException("Invalid state or action type in getBinaryOutcomeInfo");
-    }
-
-    // Check for multi-outcome commands (roll affects outcome quality, not just success/failure)
-    // These use multiOutcome() with fixed seeds to sample the range of possible results
-    using namespace net::eagle0::shardok::common;
-    const auto commandType = static_cast<CommandType>(shardokAction->getType());
-
-    switch (commandType) {
-        case END_TURN_COMMAND:
-            // END_TURN has random effects (fire spread, weather changes)
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        case MELEE_COMMAND:
-        case ARCHERY_COMMAND:
-        case CHARGE_COMMAND:
-        case REDUCE_COMMAND:
-            // Combat/siege commands: OpenEndedPercentile roll affects damage dealt
-            // Use 5 outcomes to sample the roll distribution
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        case CHALLENGE_DUEL_COMMAND:
-            // Duels have multiple combat rounds with rolls, so outcomes vary significantly
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        default:
-            // Continue to binary outcome handling below
-            break;
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Get or create the engine for this state
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = cachedEngine;
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        shardokState->setCachedEngine(engine);
-    }
-
-    // Get command descriptors
-    const auto descriptors = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-    const size_t actionIndex = shardokAction->getIndex();
-
-    if (actionIndex >= descriptors->size()) {
-        throw ShardokInternalErrorException("Action index out of range in getBinaryOutcomeInfo");
-    }
-
-    const auto& descriptor = descriptors->at(actionIndex);
-
-    // Get success probability for binary outcome actions
-    if (!descriptor->HasOdds()) {
-        throw ShardokInternalErrorException("Action does not have odds in getBinaryOutcomeInfo");
-    }
-
-    const auto successChancePercentile = descriptor->GetOddsPercentile();
-    const double successProbability = static_cast<double>(successChancePercentile) / 100.0;
-
-    return ChanceOutcomeInfo::binary(successProbability);
-}
-
-void ShardokGameEngine::clearLegalActionsCache() { legalActionsCache_.clear(); }
-
-// Extern-linkage function for testing
-void clearLegalActionsCache_ForTesting() { ShardokGameEngine::clearLegalActionsCache(); }
-
-}  // namespace shardok::mcts

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokGameEngine.hpp

@@ -1,144 +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/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,
-            double deterministicRoll = -1.0) 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;
-
-    [[nodiscard]] BinaryOutcomeInfo getBinaryOutcomeInfo(
-            const MCTSGameState& state,
-            const MCTSAction& action) 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_;  // Own the data to avoid dangling references
-    // Computed once to avoid 8.5% overhead per engine construction
-    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
-
-    // Transposition table for legal actions (shared across threads with lock-free hash map)
-    // parallel_flat_hash_map provides thread-safe concurrent access without explicit locking
-    // Using 8 submaps (N=8) to reduce contention with default 16 MCTS threads
-    static gtl::parallel_flat_hash_map<
-            uint64_t,
-            LegalActionsCache,
-            std::hash<uint64_t>,
-            std::equal_to<uint64_t>,
-            std::allocator<std::pair<const uint64_t, LegalActionsCache>>,
-            8,
-            std::mutex>
-            legalActionsCache_;
-    static std::atomic<uint64_t> cacheHits_;
-    static std::atomic<uint64_t> cacheMisses_;
-
-    // Performance timing (in microseconds)
-    static std::atomic<uint64_t> timeInHashComputation_;
-    static std::atomic<uint64_t> timeInLegalActionsComputation_;
-
-public:
-    // Clear the static legal actions cache (useful for tests)
-    static void clearLegalActionsCache();
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_ENGINE_HPP

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokGameState.cpp

@@ -1,125 +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 {
-    // Honor the interface contract: score() should return evaluation from playerId's perspective.
-    // Map the requested playerId to defender/attacker role to determine scoring perspective.
-
-    // Look up which player ID is the defender from game state
-    bool foundDefender = false;
-    bool requestedPlayerIsDefender = false;
-
-    if (state_->player_infos()) {
-        for (const auto* pi : *state_->player_infos()) {
-            if (pi && pi->is_defender()) {
-                foundDefender = true;
-                requestedPlayerIsDefender = (static_cast<PlayerId>(playerId) == pi->player_id());
-                break;
-            }
-        }
-    }
-
-    // Fallback: if we can't determine from game state, use isDefender_ which represents
-    // the root player's role (and playerId is always the root player in practice)
-    const bool scoreFromDefenderPerspective =
-            foundDefender ? requestedPlayerIsDefender : isDefender_;
-
-    // Score the current state directly
-    return scoreCalculator_
-            ->GuessedStateScore(scoreFromDefenderPerspective, 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

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokGameState.hpp

@@ -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_;  // Own the data to avoid dangling references
-    const APDCache& apdCache_;
-    const ALCache& alCache_;
-    mutable uint64_t cachedHash_ = 0;
-    mutable bool hashCached_ = false;
-    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
-    mutable std::shared_ptr<ShardokEngine> cachedEngine_;  // Engine with cached available commands
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_STATE_HPP

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokMCTSFactory.cpp

@@ -1,82 +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::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];
-
-        // Extract essential fields directly from command (no proto conversion!)
-        actions.push_back(std::make_unique<ShardokAction>(
-                i,
-                cmd->GetCommandType(),
-                cmd->GetPlayerId(),
-                cmd->GetActorUnitId(),
-                cmd->GetTargetRow(),
-                cmd->GetTargetColumn(),
-                cmd->HasOdds()));
-    }
-
-    return actions;
-}
-
-}  // namespace shardok::mcts

src/main/cpp/net/eagle0/shardok/ai/mcts/adapters/ShardokMCTSFactory.hpp

@@ -1,70 +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"
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-class GameStateW;
-class GameSettings;
-
-namespace mcts {
-
-// Forward declarations
-class MCTSGameEngine;
-class MCTSGameState;
-class MCTSAction;
-
-class ShardokMCTSFactory {
-public:
-    // 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 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