not working

plan
with an int
2026-07-29 13:15:42 +00:00 · 2025-07-28 17:18:46 -07:00 · 2025-07-28 17:17:28 -07:00 · 2025-07-28 17:17:28 -07:00 · 2025-07-28 17:17:28 -07:00
1069 changed files with 31230 additions and 43041 deletions
@@ -1,8 +1,5 @@
 bazel-1.0.0.bazelrc

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

 # Don't use toolchains_llvm for the swift app build
@@ -20,7 +20,7 @@ project/boot/
 project/plugins/project/
 project/target/
 bazel-bin
-bazel-eagle0*
+bazel-eagle0
 bazel-out
 bazel-testlogs
 .ijwb
@@ -32,6 +32,7 @@ buildWin.sh
 __pycache__/
 scripts/refresh_name_layers/vendor/
 scripts/refresh_name_layers/refresh_name_layers.zip
+.pre-commit-config.yaml
 .bazelbsp
 .bsp
 .metals
@@ -1,43 +0,0 @@
-# See https://pre-commit.com for more information
-# See https://pre-commit.com/hooks.html for more hooks
-repos:
-   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
-    hooks:
-    -   id: check-added-large-files
-    -   id: no-commit-to-branch
-        args: [--branch, main]
-   repo: https://github.com/pocc/pre-commit-hooks
-    rev: v1.3.5
-    hooks:
-    -   id: clang-format
-        args: [-i, --no-diff]
-        types_or: ["c++", "c#"]
-        exclude: ^src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins
-   repo: https://github.com/yoheimuta/protolint
-    rev: v0.42.2
-    hooks:
-    -   id: protolint
-        args: [-fix]
-        exclude: ^src/main/protobuf/scalapb/
-   repo: local
-    hooks:
-    -   id: scalafmt
-        name: scalafmt
-        language: system 
-        entry: scalafmt -i -f 
-        types_or: ["scala"]
- repo: local
-  hooks:
-      - id: gazelle
-        name: gazelle
-        language: system
-        entry: bazel run //:gazelle
-        files: '(\.go|\.proto|BUILD\.bazel|BUILD|WORKSPACE|WORKSPACE\.bazel|\.bzl)$'
-   repo: local
-    hooks:
-    -   id: update-action-result-types
-        name: update-action-result-types
-        language: system
-        entry: ./scripts/updateActionResultTypes.sh
-        files: 'src/main/protobuf/net/eagle0/eagle/common/action_result_type.proto'
@@ -1,47 +1,2 @@
-version = "3.9.9"
-runner.dialect = scala3
-rewrite.scala3.convertToNewSyntax = true
-# Keep braces, don't use significant indentation
-# rewrite.scala3.removeOptionalBraces = yes
-rewrite.scala3.insertEndMarkerMinLines = 15
-rewrite.scala3.removeEndMarkerMaxLines = 14
-
-# Strip margin settings
-assumeStandardLibraryStripMargin = false
-align.stripMargin = true
-
-# Code Style & Formatting
-align.preset = more
-align.multiline = true
-align.arrowEnumeratorGenerator = true
-spaces.inImportCurlyBraces = false
-spaces.beforeContextBoundColon = Never
-maxColumn = 120
-docstrings.style = Asterisk
-docstrings.wrap = yes
-
-# Method chaining
-newlines.beforeCurlyLambdaParams = multilineWithCaseOnly
-optIn.breakChainOnFirstMethodDot = true
-includeCurlyBraceInSelectChains = false
-
-# Advanced Scala 3 Features
-rewrite.scala3.countEndMarkerLines = all
-rewrite.redundantBraces.stringInterpolation = true
-rewrite.redundantBraces.parensForOneLineApply = true
-
-# Project-Specific Considerations
-optIn.annotationNewlines = true
-runner.optimizer.forceConfigStyleMinArgCount = 3
-
-# Import sorting configuration
-rewrite.rules = [SortImports, RedundantBraces, RedundantParens]
-rewrite.imports.sort = scalastyle
-rewrite.imports.groups = [
-  ["java\\..*"],
-  ["javax\\..*"],
-  ["scala\\..*"],
-  [".*"]
-]
-rewrite.imports.contiguousGroups = only
-rewrite.trailingCommas.style = never
+version = "3.6.1"
+runner.dialect = scala213
@@ -35,12 +35,9 @@ Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC)
 # 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  
@@ -87,64 +84,6 @@ find . -name "*.cpp" -o -name "*.hpp" | xargs clang-format -i
 find . -name "*.cs" | xargs clang-format -i
 ```

-### Static Analysis
-```bash
-# Run clang-tidy static analysis on C++ files
-# Note: This may show some header include errors but will still analyze the main file
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' <file_path> -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++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++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):**
@@ -229,6 +168,4 @@ done

 - Bazel handles multi-language builds and dependencies
 - CI/CD via GitHub Actions with platform-specific build scripts in `/ci/github_actions/`
- Docker containerization available via `ci/eagle_run.Dockerfile`
- Always run "bazel run //:gazelle" after editing any BUILD.bazel files
- *ALWAYS ALWAYS* run "bazel run gazelle" after any change that modifies a BUILD.bazel file
+- Docker containerization available via `ci/eagle_run.Dockerfile`
@@ -1,177 +0,0 @@
-# MCTS with Player Flips - Clean Design
-
-## Core Principles
-
-1. **Single Perspective**: All scoring is from our AI's perspective (positive = good for us, negative = bad for us)
-2. **Player Flips**: Continue expansion/simulation until N player turn changes occur
-3. **Minimax Integration**: Our turns maximize our score, opponent turns minimize our score
-4. **Simplicity**: No special casing - just track when currentPlayer changes
-
-## Node Structure
-
-```cpp
-struct MCTSNode {
-    // Command that led to this state
-    size_t commandIndex;
-    CommandType commandType;
-
-    // Game state after executing the command
-    GameStateW resultingGameState;
-    PlayerId currentPlayer;  // Whose turn it is in this state
-
-    // Tree position
-    int playerFlipsFromRoot;  // Number of player changes from root
-    bool isOurTurn;          // currentPlayer == our AI's playerId
-
-    // MCTS statistics (always from our perspective)
-    int visitCount = 0;
-    double totalScore = 0.0;
-    double averageScore = 0.0;
-
-    // Tree structure
-    std::vector<std::unique_ptr<MCTSNode>> children;
-    std::vector<size_t> untriedCommands;
-};
-```
-
-## Expansion Algorithm
-
-```cpp
-MCTSNode* Expand(MCTSNode* node) {
-    // Check if we've reached max player flips
-    if (node->playerFlipsFromRoot >= maxPlayerFlips) {
-        return node;  // Don't expand further
-    }
-
-    // Pick untried command
-    size_t cmdIndex = PickUntriedCommand(node);
-
-    // Execute command to create child state
-    auto childEngine = std::make_shared<ShardokEngine>(parentEngine);
-    PlayerId playerBefore = childEngine->GetCurrentPlayerId();
-    childEngine->PostCommand(playerBefore, cmdIndex, averageGenerator);
-    PlayerId playerAfter = childEngine->GetCurrentPlayerId();
-
-    // Create child node
-    auto child = std::make_unique<MCTSNode>();
-    child->commandIndex = cmdIndex;
-    child->resultingGameState = childEngine->GetCurrentGameState();
-    child->currentPlayer = playerAfter;
-    child->isOurTurn = (playerAfter == ourPlayerId);
-
-    // Track player flips
-    child->playerFlipsFromRoot = node->playerFlipsFromRoot;
-    if (playerBefore != playerAfter) {
-        child->playerFlipsFromRoot++;
-    }
-
-    // Score from our perspective
-    child->immediateScore = ScoreFromOurPerspective(child->resultingGameState);
-
-    return child;
-}
-```
-
-## Simulation Algorithm
-
-```cpp
-double Simulate(const GameStateW& startState, PlayerId startPlayer, int startFlips) {
-    auto simEngine = CreateEngine(startState);
-    int currentFlips = startFlips;
-
-    while (currentFlips < maxPlayerFlips) {
-        PlayerId currentPlayer = simEngine->GetCurrentPlayerId();
-        bool isOurTurn = (currentPlayer == ourPlayerId);
-
-        // Get available commands
-        auto commands = simEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        if (commands->empty()) break;
-
-        // Pick best command based on whose turn it is
-        size_t bestCmd = 0;
-        double bestScore = isOurTurn ? -infinity : +infinity;
-
-        for (size_t i = 0; i < commands->size(); ++i) {
-            auto testEngine = CreateEngine(simEngine);
-            testEngine->PostCommand(currentPlayer, i, averageGenerator);
-
-            // Always score from our perspective
-            double score = ScoreFromOurPerspective(testEngine->GetCurrentGameState());
-
-            // Our turn: maximize our score, Opponent turn: minimize our score
-            bool shouldSelect = isOurTurn ? (score > bestScore) : (score < bestScore);
-            if (shouldSelect) {
-                bestScore = score;
-                bestCmd = i;
-            }
-        }
-
-        // Execute chosen command
-        PlayerId playerBefore = simEngine->GetCurrentPlayerId();
-        simEngine->PostCommand(currentPlayer, bestCmd, averageGenerator);
-        PlayerId playerAfter = simEngine->GetCurrentPlayerId();
-
-        // Track player flips
-        if (playerBefore != playerAfter) {
-            currentFlips++;
-        }
-    }
-
-    return ScoreFromOurPerspective(simEngine->GetCurrentGameState());
-}
-```
-
-## Selection Algorithm
-
-```cpp
-MCTSNode* SelectChild(MCTSNode* node) {
-    MCTSNode* bestChild = nullptr;
-    double bestUCB1 = node->isOurTurn ? -infinity : +infinity;
-
-    for (auto& child : node->children) {
-        double ucb1 = child->averageScore + explorationTerm;
-
-        // Our turn: pick highest UCB1, Opponent turn: pick lowest UCB1
-        bool shouldSelect = node->isOurTurn ? (ucb1 > bestUCB1) : (ucb1 < bestUCB1);
-
-        if (shouldSelect) {
-            bestUCB1 = ucb1;
-            bestChild = child.get();
-        }
-    }
-
-    return bestChild;
-}
-```
-
-## Backpropagation Algorithm
-
-```cpp
-void Backpropagate(MCTSNode* node, double score) {
-    while (node != nullptr) {
-        node->visitCount++;
-        node->totalScore += score;  // Always from our perspective
-        node->averageScore = node->totalScore / node->visitCount;
-        node = node->parent;
-    }
-}
-```
-
-## Key Simplifications
-
-1. **No END_TURN special cases** - just check if currentPlayer changed after any command
-2. **Consistent scoring** - always from our AI's perspective throughout
-3. **Clear minimax** - our nodes maximize, opponent nodes minimize
-4. **Simple state tracking** - just count player flips, no complex inheritance
-5. **Unified command handling** - all commands handled the same way
-
-## Implementation Plan
-
-1. **Refactor MCTSNode structure** - simplify to core fields needed
-2. **Rewrite MCTSExpansion** - remove END_TURN special cases, just track player changes
-3. **Fix MCTSSimulation** - ensure consistent perspective and proper minimax
-4. **Simplify MCTSSelection** - clean minimax logic
-5. **Clean up MCTSBackpropagation** - single perspective throughout
-6. **Add comprehensive testing** - verify player flips are tracked correctly
-
-This design eliminates the confusion around perspectives and special cases, making the algorithm much easier to understand and debug.
@@ -1,66 +1,35 @@
-module(name = "net_eagle0")
-
-# Version constants
-SCALA_VERSION = "3.7.2"
-
-NETTY_VERSION = "4.1.110.Final"
-
-SCALAPB_VERSION = "1.0.0-alpha.1"
-
-AWS_SDK_VERSION = "2.28.1"
+bazel_dep(name = "apple_support", repo_name = "build_bazel_apple_support", version = "1.21.1")

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

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

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

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

 use_repo(llvm, "llvm_toolchain")

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

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

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

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

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

 #
-# Protocol Buffers & RPC
+# rules_jvm_external
 #

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

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

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

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

 #
-# External Libraries
+# rules_apple
 #

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

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

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

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

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

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

 http_archive(
    name = "net_eagle0_unity_godice",
-    sha256 = UNITY_GODICE_SHA,
-    strip_prefix = "godice-framework-%s" % UNITY_GODICE_COMMIT,
+    sha256 = unity_godice_sha,
+    strip_prefix = "godice-framework-%s" % unity_godice_commit,
    urls = [
-        "https://github.com/nolen777/godice-framework/archive/%s.zip" % UNITY_GODICE_COMMIT,
+        "https://github.com/nolen777/godice-framework/archive/%s.zip" % unity_godice_commit,
    ],
 )
-
-#
-# Toolchain Registration
-#
-
-register_toolchains(
-    "//tools:unused_dependency_checker_error_and_opts_toolchain",
-    "@rules_scala//testing:scalatest_toolchain",
-)
-
-# Set dev_dependency so we can turn this off for swift MacOS builds
-register_toolchains(
-    "@llvm_toolchain//:all",
-    dev_dependency = True,
-)
@@ -1,205 +0,0 @@
-# Scala 3 Modernization Guide
-
-## Overview
-This document outlines opportunities to modernize the Eagle0 codebase to use Scala 3 best practices and features. The migration to Scala 3 is complete, but the code still uses many Scala 2 patterns that can be improved.
-
-## Modernization Opportunities
-
-### 1. **Convert Sealed Traits to Enums** 🎯 HIGH IMPACT
-**Benefits**: Better performance, more concise syntax, improved exhaustiveness checking
-
-**Current pattern** (`ExternalTextGenerationCaller.scala:23-31`):
-```scala
-sealed trait ExternalTextGenerationError extends Error {
-  def message: String
-}
-case class ExternalTextGenerationRateLimitError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationHttpError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationTimeoutError(message: String)
-    extends ExternalTextGenerationError
-```
-
-**Scala 3 improvement**:
-```scala
-enum ExternalTextGenerationError extends Error:
-  case RateLimit(code: Int, message: String)
-  case Http(code: Int, message: String) 
-  case Timeout(message: String)
-  
-  def message: String = this match
-    case RateLimit(_, msg) => msg
-    case Http(_, msg) => msg
-    case Timeout(msg) => msg
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/llm_integration/ExternalTextGenerationCaller.scala`
- `/src/main/scala/net/eagle0/eagle/model/action_result/generated_text_request/GeneratedTextRequestT.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/quest/concrete/QuestC.scala`
-
-### 2. **Convert Implicit Classes to Extension Methods** 🎯 HIGH IMPACT
-**Benefits**: Modern syntax, better IDE support, cleaner imports
-
-**Current pattern** (`MoreSeq.scala:23-26`):
-```scala
-implicit def SeqCollect[A, Repr[_]](coll: Repr[A])(implicit
-    itr: IsIterable[Repr[A]]
-): SeqCollect[A, Repr, itr.type] =
-  new SeqCollect[A, Repr, itr.type](coll, itr)
-```
-
-**Scala 3 improvement**:
-```scala
-extension [A, Repr[_]](coll: Repr[A])(using itr: IsIterable[Repr[A]])
-  def flatCollect[B](pf: PartialFunction[itr.A, Option[B]])(using Factory[B, Repr[B]]): Repr[B] =
-    Factory[B, Repr[B]].fromSpecific(itr(coll).collect(pf).flatten)
-    
-  def flatCollectFirst[B](pf: PartialFunction[itr.A, Option[B]]): Option[B] =
-    itr(coll).collect(pf).flatten.headOption
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/command_choice_helpers/CommandChooser.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/NewGameCreation.scala`
- `/src/main/scala/net/eagle0/eagle/library/actions/applier/ActionResultProtoApplierImpl.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/StartGameActionResultUtils.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/date/Date.scala`
-
-### 3. **Convert Implicit Parameters to Using Clauses** 🎯 MEDIUM IMPACT
-**Benefits**: Cleaner syntax, better tooling support, clearer intent
-
-**Current pattern**:
-```scala
-def method[T](value: T)(implicit ec: ExecutionContext): Future[T]
-def process[A](items: Seq[A])(implicit ord: Ordering[A]): Seq[A]
-```
-
-**Scala 3 improvement**:
-```scala
-def method[T](value: T)(using ExecutionContext): Future[T]
-def process[A](items: Seq[A])(using Ordering[A]): Seq[A]
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/OpenAIChatCompletionsServiceImpl.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/ClaudeServiceImpl.scala`
-
-### 4. **Opaque Types for Type Safety** 🎯 MEDIUM IMPACT
-**Benefits**: Zero runtime cost, compile-time type safety, prevents mixing up similar types
-
-**Pattern to look for**: Type aliases that represent distinct concepts
-```scala
-// Instead of: type UserId = String, type GameId = String
-opaque type UserId = String
-object UserId:
-  def apply(s: String): UserId = s
-  extension (id: UserId) 
-    def value: String = id
-    def isValid: Boolean = id.nonEmpty && id.length > 3
-
-opaque type GameId = Long  
-object GameId:
-  def apply(l: Long): GameId = l
-  extension (id: GameId) def value: Long = id
-```
-
-**Candidates**: Look for simple type aliases and ID types throughout the codebase.
-
-### 5. **Inline Methods for Performance** 🎯 LOW IMPACT
-**Benefits**: Compile-time optimization, better performance for hot paths
-
-**Pattern**: Mark small, frequently-called methods as `inline`
-```scala
-inline def isValidId(id: String): Boolean = 
-  id.nonEmpty && id.length > 3
-
-inline def calculateScore(base: Int, multiplier: Double): Double = 
-  base * multiplier
-```
-
-**Candidates**: Small utility methods in performance-critical paths (AI calculations, game state updates).
-
-### 6. **Union Types Instead of Complex Hierarchies** 🎯 LOW IMPACT  
-**Benefits**: Simpler type definitions for either/or scenarios
-
-**Pattern**: Simple sealed traits with only case classes
-```scala
-// Instead of:
-sealed trait Result
-case class Success(value: String) extends Result  
-case class Error(message: String) extends Result
-
-// Consider:
-type Result = Success | Error
-case class Success(value: String)
-case class Error(message: String)
-```
-
-### 7. **Context Functions for Cleaner APIs** 🎯 LOW IMPACT
-**Benefits**: Cleaner API design, implicit context passing
-
-**Pattern**: Replace implicit function parameters
-```scala
-// Old
-type Handler = GameState => Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = handler(gs)
-
-// New  
-type Handler = GameState ?=> Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = 
-  given GameState = gs
-  handler
-```
-
-## Implementation Priority
-
-### Phase 1: Quick Wins (High Impact, Low Risk)
-1. **Convert Extension Methods** in `MoreSeq.scala` - immediate readability improvement
-2. **Update Using Clauses** - simple find/replace operation  
-3. **Convert Simple Sealed Traits to Enums** - start with error types
-
-### Phase 2: Type Safety Improvements  
-4. **Add Opaque Types** for IDs and measurements - improves type safety
-5. **Inline Performance-Critical Methods** - measure before/after impact
-
-### Phase 3: Advanced Features (Lower Priority)
-6. **Union Types** where appropriate - only for simple either/or cases
-7. **Context Functions** for complex API improvements
-
-## Implementation Guidelines
-
-### Style Consistency
- **Keep curly braces**: Continue using Scala 2 style `{}` instead of indentation-based syntax
- **Gradual adoption**: Modernize files as they're touched for other reasons
- **Test thoroughly**: Each modernization should include verification that behavior is unchanged
-
-### Performance Considerations  
- **Measure enum performance**: Verify that enum conversion actually improves performance in hot paths
- **Benchmark inline methods**: Use profiling to confirm performance gains
- **Consider compilation time**: Some features may increase compile time
-
-### Migration Strategy
- **File-by-file approach**: Complete modernization of one file at a time
- **Separate PRs**: Each modernization type should be its own PR for easier review
- **Documentation**: Update this document as patterns are modernized
-
-## Success Criteria
- [ ] All extension methods converted from implicit classes
- [ ] All implicit parameters converted to using clauses  
- [ ] Key sealed traits converted to enums where appropriate
- [ ] Opaque types introduced for important ID types
- [ ] Performance-critical methods marked as inline (with benchmarks)
- [ ] No regression in functionality or performance
- [ ] Code remains readable and maintainable
-
-## Notes
- Focus on high-impact, low-risk improvements first
- Each change should be driven by clear benefits (performance, readability, type safety)
- Maintain backward compatibility where possible
- Document any breaking changes clearly
@@ -1,2 +1,51 @@
-# This file marks the root of the Bazel workspace.
-# See MODULE.bazel for external dependencies and setup.
+workspace(name = "net_eagle0")
+
+load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
+
+#
+# Scala support
+#
+
+scala_version = "2.13.14"
+
+#rules_scala_version = "6.6.0"
+
+#rules_scala_sha = "e734eef95cf26c0171566bdc24d83bd82bdaf8ca7873bec6ce9b0d524bdaf05d"
+
+#http_archive(
+#    name = "io_bazel_rules_scala",
+#    sha256 = rules_scala_sha,
+#    strip_prefix = "rules_scala-%s" % rules_scala_version,
+#    url = "https://github.com/bazelbuild/rules_scala/releases/download/v%s/rules_scala-v%s.tar.gz" % (rules_scala_version, rules_scala_version),
+#)
+
+# Using a commit from master to get 2.13.14 support. Restore the commented-out lines above with a new
+# release version when one is cut.
+rules_scala_commit = "e53a43bf48f10a5906b3e91c21798281cec1b334"
+
+rules_scala_sha = "b4fd903724d084d9d9f45e17fc22391bda745bf0574f8934d38a9c1c2fc18834"
+
+http_archive(
+    name = "io_bazel_rules_scala",
+    sha256 = rules_scala_sha,
+    strip_prefix = "rules_scala-%s" % rules_scala_commit,
+    url = "https://github.com/bazelbuild/rules_scala/archive/%s.zip" % rules_scala_commit,
+)
+
+load("@io_bazel_rules_scala//:scala_config.bzl", "scala_config")
+
+scala_config(scala_version = scala_version)
+
+load("//tools:toolchains.bzl", "scala_register_toolchains")
+
+scala_register_toolchains()
+
+load("@io_bazel_rules_scala//scala:scala.bzl", "scala_repositories")
+
+scala_repositories()
+
+load("@io_bazel_rules_scala//testing:scalatest.bzl", "scalatest_repositories", "scalatest_toolchain")
+
+scalatest_repositories()
+
+scalatest_toolchain()
@@ -1,305 +0,0 @@
-# Actions and Commands Model Usage Analysis
-
-This document analyzes all actions and commands in `src/main/scala/net/eagle0/eagle/library/actions/impl` to determine which use Scala models vs protobuf models, based on BUILD.bazel dependencies.
-
-**Legend:**
- ✅ **Scala Models Only** - Uses only `//src/main/scala/net/eagle0/eagle/model` dependencies
- ❌ **Uses Protobuf** - Has dependencies on `//src/main/protobuf` targets
- 🔄 **Partial Conversion** - Conversion attempted but blocked by dependencies
-
-## Summary
-
-Based on BUILD.bazel dependency analysis (2025-09-16, updated 2025-09-17):
- **Total Commands Analyzed:** 41
- **Commands Fully Migrated (No Protobuf):** 41 (100%) ✅
- **Commands Still Using Protobuf:** 0 (0%) ✅
- **Total Actions Analyzed:** 48
- **Actions Fully Migrated (No Protobuf):** 5 (10.4%)
- **Actions Partially Migrated:** 19 (39.6%)
- **Actions Still Using Protobuf:** 24 (50%)
- **Base Classes:** 8 protoless variants available, 6 still use protobuf
- **Shared Components:** `ResolvedEagleUnit` migrated to use `Option[BattalionT]` for proper null handling
-
-## Conversion Insights
-
-Based on conversion attempt of `ResolveTruceOfferCommand` (see [PR #4379](https://github.com/nolen777/eagle0/pull/4379)):
-
-### Key Challenges Discovered
-
-1. **LLM Integration Dependencies**: Commands that use `DiplomacyResolutionLlmRequestGenerator` face challenges because the LLM system still expects protobuf enum types, not Scala model enums.
-
-2. **Inconsistent Package Naming**: Some files have inconsistent package declarations vs BUILD file locations (e.g., `generated_text_request_generators` in package vs `llm_request_generators` in BUILD).
-
-3. **Model Constructor Differences**: Scala model constructors (e.g., `TruceOffer`) have different required parameters than their protobuf counterparts, requiring more complex data mapping.
-
-4. **Type System Complexity**: Union types and type constraints become more complex when mixing protobuf and Scala model types during transition.
-
-5. **Cascading Dependency Issues**: Converting to `ActionResultC` requires extensive trait dependencies (`ChangedBattalionT`, `ChangedHeroT`, `GeneratedTextRequestT`, etc.) that create complex BUILD dependency graphs, unlike simple protobuf `ActionResult`.
-
-6. **BUILD Complexity**: Each Scala model conversion requires significantly more BUILD dependencies than protobuf equivalents, making incremental conversion difficult.
-
-7. **Build Verification Critical**: Any conversion must maintain working build state - even simple commands like `DefendCommand` can break main server build due to dependency cascades.
-### Successful Conversion Elements
-
- ✅ Base class conversion (`SimpleAction` → `ProtolessSimpleAction`)
- ✅ Import updates for most Scala model types
- ✅ BUILD.bazel dependency updates for core action result types
- ✅ Basic type conversions for simple cases
-
-### Recommended Conversion Strategy
-
-1. **Architecture-First Approach**: Convert base infrastructure (LLM generators, action result builders) before individual commands
-2. **Wrapper Pattern**: Use existing `Protoless*ActionWrapper` classes as templates for gradual transition
-3. **Dependency Analysis**: Map full dependency trees before attempting conversions to avoid cascading build failures
-4. **Batch Conversions**: Convert related commands together to minimize dependency conflicts
-5. **Build Verification**: **ALWAYS** verify `//src/main/scala/net/eagle0/eagle:eagle_server` and test suite build before creating PRs
-
-### Conversion Requirements
-
-**Before creating any PR:**
- ✅ `bazel build //src/main/scala/net/eagle0/eagle:eagle_server` succeeds
- ✅ `bazel test //src/test/scala/... --keep_going` passes (or doesn't introduce new failures)
- ✅ All BUILD dependencies are correctly specified
- ✅ Scalafmt and other linters pass
-
---
-
-## Common Base Classes
-
-| File | Type | Model Usage | Notes |
-|------|------|-------------|-------|
-| Action.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ActionWithResultingState.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSingleResultAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ProtolessRandomSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessRandomSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| RandomSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| RandomSimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| RandomStateProtoSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| RandomStateTSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| SimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| VigorXPApplier.scala | Utility | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-
---
-
-## Actions
-
-### ✅ Fully Migrated Actions (No Protobuf Dependencies)
-
-These actions have been successfully migrated to use Scala models only:
-
-| File | Base Class | Notes |
-|------|------------|-------|
-| HeroBackstoryUpdateAction.scala | ProtolessSequentialResultsAction | Processes hero backstory updates with LLM integration |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | Uses component-based design (gameId, currentRoundId, currentDate, Scala models) |
-| ProvinceHeldAction.scala | ProtolessSimpleAction | Uses specific components (gameId, currentRoundId, defendingProvince, etc.) instead of full GameState |
-| UnaffiliatedHeroAppearedAction.scala | ProtolessSimpleAction | Handles unaffiliated hero appearance with name generation |
-| WithdrawnArmiesReturnHomeAction.scala | ProtolessSequentialResultsAction | Manages army withdrawal and return mechanics |
-
-### 🔄 Actions Partially Migrated (Using Protoless Base Classes)
-
-These actions use protoless base classes but still have some protobuf dependencies:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| CheckForFactionChangesAction.scala | ProtolessSequentialResultsAction | Still has some protobuf dependencies |
-| CheckForFailedQuestsAction.scala | ProtolessSequentialResultsAction | Depends on `unaffiliated_hero_quest_scala_proto` |
-| CheckForFulfilledQuestsAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndAttackDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndBattleAftermathPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndFreeForAllDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndPlayerCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndUnaffiliatedHeroActionsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndVassalCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| FreeForAllDrawAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| FriendlyMoveAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| PerformUncontestedConquestAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | **CONVERTED** - Uses specific components (gameId, currentRoundId, currentDate, Scala models) |
-| SafePassageArmiesProceedAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ShipmentArrivedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| TruceTurnBackPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| UnaffiliatedHeroRejoinedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| WonFreeForAllAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-
-### ❌ Actions Still Using Protobuf (Not Yet Using Protoless Base Classes)
-
-| File | Notes |
-|------|-------|
-| ChronicleEventGenerator.scala | Depends on multiple protobuf targets |
-| EndBattleRequestPhaseAction.scala | Depends on `diplomacy_offer_status_scala_proto` |
-| EndBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDefenseDecisionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDiplomacyResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleRequestPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndHandleRiotsPhaseAction.scala | Depends on multiple protobuf targets |
-| EndPleaseRecruitMePhaseAction.scala | Depends on multiple protobuf targets |
-| EndProvinceMoveResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| NewRoundAction.scala | Depends on multiple protobuf targets |
-| NewYearAction.scala | Depends on multiple protobuf targets |
-| PerformFoodConsumptionPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformForcedTurnBackAction.scala | Depends on multiple protobuf targets |
-| PerformHeroDeparturesAction.scala | Depends on multiple protobuf targets |
-| PerformHostileArmySetupAction.scala | Depends on multiple protobuf targets |
-| PerformProvinceEventsAction.scala | Depends on `province_event_scala_proto` |
-| PerformProvinceMoveResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformReconResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformUnaffiliatedHeroesAction.scala | Depends on `unaffiliated_hero_quest_scala_proto` |
-| PerformVassalCommandsPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformVassalDefenseDecisionsAction.scala | Depends on multiple protobuf targets |
-| PrisonerEscapeAction.scala | Depends on `game_state_scala_proto` |
-| PrisonerExchangeAction.scala | Depends on multiple protobuf targets |
-| RequestBattlesAction.scala | Depends on multiple protobuf targets |
-| RequestFreeForAllBattlesAction.scala | Depends on multiple protobuf targets |
-| ResolveBattleAction.scala | Depends on `shardok_internal_interface_scala_grpc` |
-| UnaffiliatedHeroMovedAction.scala | Depends on multiple protobuf targets |
-| UnaffiliatedHeroesChangedAction.scala | Depends on multiple protobuf targets |
-
---
-
-## Commands
-
-✅ **ALL COMMANDS FULLY MIGRATED** (100% - 41/41 commands)
-
-All 41 commands in the codebase have been successfully migrated to use Scala models only, with no protobuf dependencies. This includes:
-
- **Simple Actions**: Use `ProtolessSimpleAction` base class
- **Random Actions**: Use `ProtolessRandomSimpleAction` base class
- **Complex Domain Models**: Successfully integrated with LLM systems, diplomacy, quest fulfillment, and state management
- **Complete Type Safety**: All commands now use type-safe Scala domain models
-
-**Key Migration Achievements:**
- ✅ All military commands (ArmTroops, Train, Organize, etc.)
- ✅ All diplomacy commands (Resolve Alliance/Truce/Ransom offers, etc.)
- ✅ All LLM-integrated commands (backstory generation, diplomacy resolution)
- ✅ All quest and event commands
- ✅ Final remaining command (FreeForAllDecisionCommand) migrated
-
---
-
-## Diplomacy Helpers
-
-All diplomacy helpers use **Scala models only**:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| AllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| BreakAllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| InvitationResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| RansomResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| TruceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-
---
-
-## Migration Priority Analysis
-
-Based on the BUILD.bazel dependency analysis, here are the key findings and recommendations:
-
-### 🎯 High Impact Migration Targets
-
-**Core Dependencies Blocking Multiple Commands:**
-
-1. **`action_result_scala_proto`** - Used by 12+ commands
-   - Blocks: `DefendCommand`, `FreeForAllDecisionCommand`, diplomacy resolvers
-   - Impact: Would unlock many command migrations
-
-2. **`available_command_scala_proto` / `selected_command_scala_proto`** - Used by 10+ commands
-   - Blocks: All UI-interactive commands
-   - Impact: Would enable client-server interaction model migration
-
-3. **`game_state_scala_proto`** - Used by 8+ commands
-   - Blocks: Complex state-dependent commands
-   - Impact: Core state representation migration
-
-### 📊 Migration Tiers by Complexity
-
-**Tier 1 - Quick Wins (2 commands):**
- `ArmTroopsCommand` - Only `battalion_type` dependency
- `TrainCommand` - Only `battalion_type` dependency
- **Effort:** Low, **Impact:** Demonstrates battalion model usage
-
-**Tier 2 - API Layer (5 commands):**
- Commands blocked by `available_command`/`selected_command`
- **Effort:** Medium, **Impact:** High (enables UI interaction models)
-
-**Tier 3 - Diplomacy Suite (6 commands):**
- All `Resolve*Command` diplomacy commands
- **Effort:** High, **Impact:** High (complete diplomacy model migration)
- **Strategy:** Migrate as a group after diplomacy models are ready
-
-### 🏆 Success Metrics
-
-**Current Status:**
- ✅ **100% of commands fully migrated** (41/41) 🎉
- ✅ **All diplomacy helpers use Scala models**
- ✅ **All protoless base classes available**
- ✅ **ALL command migration completed**
-
-**Completed Milestones:**
- ✅ **70% target:** Migrate Tier 1 + some Tier 2 commands **COMPLETED**
- ✅ **80% target:** Continue with remaining non-diplomacy commands **COMPLETED**
- ✅ **85% target:** Complete API layer migration **COMPLETED**
- ✅ **95% target:** Complete diplomacy migration **COMPLETED**
- ✅ **100% target:** Migrate final remaining command (FreeForAllDecisionCommand) **COMPLETED**
-
-### 🎯 Action Migration Progress
-
-**Migration Statistics:**
- 5/48 Actions fully migrated (10.4%)
- 20/48 Actions using protoless base classes but with protobuf dependencies (41.7%)
- 24/48 Actions still fully on protobuf (50%)
-
-**Successfully Migrated Actions:**
-1. **HeroBackstoryUpdateAction** - LLM integration for hero backstories
-2. **ProvinceConqueredAction** - Component-based design with prisoner handling and province conquest
-3. **ProvinceHeldAction** - Component-based design pattern (gameId, currentRoundId, specific models)
-4. **UnaffiliatedHeroAppearedAction** - Hero appearance with name generation
-5. **WithdrawnArmiesReturnHomeAction** - Army withdrawal mechanics
-
-**Recent Migration Updates (2025-09-17):**
- **ResolvedEagleUnit** - Changed `battalion: BattalionT` to `battalion: Option[BattalionT]`
-  - Properly handles units without battalions (battalion ID -1)
-  - Updated `ShardokInterfaceGrpcClient` to check for `defaultBattalionId` and use `None`
-  - Updated `ResolveBattleAction`, `ProvinceConqueredAction`, `RequestBattlesAction`
-  - All tests updated to handle optional battalions
-
-**Key Migration Patterns:**
- ✅ Use specific components instead of full GameState (see ProvinceHeldAction, ProvinceConqueredAction)
- ✅ Convert protobuf models to Scala models at Action boundaries
- ✅ Update BUILD.bazel to remove protobuf dependencies
- ✅ Update all call sites and tests
- ✅ Use `Option[T]` for optional fields instead of special sentinel values (e.g., battalion ID -1)
-
-**Next Migration Candidates (Simple Actions with Protoless Base):**
-1. **FreeForAllDrawAction** - Already uses ProtolessSimpleAction
-2. **FriendlyMoveAction** - Already uses ProtolessSimpleAction
-3. **ShipmentArrivedAction** - Already uses ProtolessSimpleAction
-4. **WonFreeForAllAction** - Already uses ProtolessSimpleAction
-5. **ProvinceConqueredAction** - Already uses ProtolessSimpleAction, only needs `common_unit` migration
-
-### 🔄 Conversion Strategy Updates
-
-**Revised Approach Based on Analysis:**
-
-1. **Focus on Core Dependencies First**
-   - Migrate `battalion_type` model (unlocks 2 commands immediately)
-   - Migrate `action_result` model (unlocks 12+ commands)
-   - Migrate `available_command`/`selected_command` (unlocks UI layer)
-
-2. **Leverage Existing Success**
-   - 77.5% of commands already fully migrated
-   - Use migrated commands as reference implementations
-   - Diplomacy helpers prove complex business logic can work with Scala models
-
-3. **Group Related Migrations**
-   - Military commands: `ArmTroopsCommand`, `TrainCommand`, `OrganizeTroopsCommand`
-   - UI commands: All using `available_command`/`selected_command`
-   - Diplomacy commands: All `Resolve*Command` variants
-
---
-
-*Updated on 2025-09-17 - Analysis based on BUILD.bazel dependencies and code review*
-*Latest update: ResolvedEagleUnit migrated to use Option[BattalionT] for proper battalion handling*
@@ -1,7 +1,7 @@
 {
  "__AUTOGENERATED_FILE_DO_NOT_MODIFY_THIS_FILE_MANUALLY": "THERE_IS_NO_DATA_ONLY_ZUUL",
-  "__INPUT_ARTIFACTS_HASH": 571423113,
-  "__RESOLVED_ARTIFACTS_HASH": 438039003,
+  "__INPUT_ARTIFACTS_HASH": 644967262,
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  "conflict_resolution": {
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@@ -14,7 +14,8 @@
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-    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0"
+    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0",
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@@ -167,29 +168,23 @@
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      "version": "2.10.0"
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+    "com.thesamet.scalapb:compilerplugin_2.13": {
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@@ -197,24 +192,30 @@
      },
      "version": "0.9.7"
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-    "com.thesamet.scalapb:scalapb-json4s_3": {
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-    "com.thesamet.scalapb:scalapb-runtime_3": {
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      "version": "1.0.0-alpha.1"
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+      },
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@@ -460,35 +461,41 @@
      },
      "version": "13.0"
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      "version": "4.0.7"
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-      "version": "4.1.0-M8"
+      "version": "4.0.7"
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+      },
+      "version": "4.0.7"
+    },
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+      },
+      "version": "4.0.7"
+    },
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+      },
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    "org.ow2.asm:asm": {
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@@ -502,29 +509,29 @@
      },
      "version": "1.0.4"
    },
-    "org.scala-lang.modules:scala-collection-compat_3": {
+    "org.scala-lang.modules:scala-collection-compat_2.13": {
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+      "version": "2.13.15"
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      "shasums": {
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+      "version": "2.13.12"
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@@ -786,45 +793,41 @@
      "org.jetbrains.kotlin:kotlin-stdlib",
      "org.jetbrains.kotlin:kotlin-stdlib-common"
    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
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      "com.thesamet.scalapb:protoc-gen_2.13",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
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-    "com.thesamet.scalapb:lenses_3": [
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:lenses_2.13": [
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+      "org.scala-lang:scala-library"
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-      "com.thesamet.scalapb:scalapb-runtime_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
-      "com.thesamet.scalapb:scalapb-runtime_3",
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
      "io.grpc:grpc-protobuf",
      "io.grpc:grpc-stub",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
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-      "com.thesamet.scalapb:lenses_3",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
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+      "org.scala-lang:scala-library"
    ],
    "io.grpc:grpc-api": [
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@@ -992,35 +995,41 @@
      "org.jetbrains.kotlin:kotlin-stdlib-common",
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-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.scala-lang:scala3-library_3": [
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      "org.scala-lang:scala-library"
    ],
-    "org.scalamock:scalamock_3": [
-      "org.scala-lang:scala3-library_3"
+    "org.json4s:json4s-core_2.13": [
+      "com.thoughtworks.paranamer:paranamer",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-scalap_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-jackson-core_2.13": [
+      "com.fasterxml.jackson.core:jackson-databind",
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native-core_2.13": [
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native_2.13": [
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang:scala-reflect": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scalamock:scalamock_2.13": [
+      "org.scala-lang:scala-library",
+      "org.scala-lang:scala-reflect"
    ],
    "org.slf4j:slf4j-simple": [
      "org.slf4j:slf4j-api"
@@ -1463,14 +1472,14 @@
      "okio",
      "okio.internal"
    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
      "scalapb",
      "scalapb.compiler",
      "scalapb.internal",
      "scalapb.options",
      "scalapb.options.compiler"
    ],
-    "com.thesamet.scalapb:lenses_3": [
+    "com.thesamet.scalapb:lenses_2.13": [
      "scalapb.lenses"
    ],
    "com.thesamet.scalapb:protoc-bridge_2.13": [
@@ -1478,21 +1487,16 @@
      "protocbridge.codegen",
      "protocbridge.frontend"
    ],
-    "com.thesamet.scalapb:protoc-bridge_3": [
-      "protocbridge",
-      "protocbridge.codegen",
-      "protocbridge.frontend"
-    ],
    "com.thesamet.scalapb:protoc-gen_2.13": [
      "protocgen"
    ],
-    "com.thesamet.scalapb:scalapb-json4s_3": [
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
      "scalapb.json4s"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
      "scalapb.grpc"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
+    "com.thesamet.scalapb:scalapb-runtime_2.13": [
      "com.google.protobuf.any",
      "com.google.protobuf.api",
      "com.google.protobuf.compiler.plugin",
@@ -1511,6 +1515,9 @@
      "scalapb.options",
      "scalapb.textformat"
    ],
+    "com.thoughtworks.paranamer:paranamer": [
+      "com.thoughtworks.paranamer"
+    ],
    "commons-codec:commons-codec": [
      "org.apache.commons.codec",
      "org.apache.commons.codec.binary",
@@ -1845,24 +1852,28 @@
      "org.intellij.lang.annotations",
      "org.jetbrains.annotations"
    ],
-    "org.json4s:json4s-ast_3": [
+    "org.json4s:json4s-ast_2.13": [
      "org.json4s",
      "org.json4s.prefs"
    ],
-    "org.json4s:json4s-core_3": [
+    "org.json4s:json4s-core_2.13": [
      "org.json4s",
      "org.json4s.prefs",
      "org.json4s.reflect"
    ],
-    "org.json4s:json4s-jackson-core_3": [
+    "org.json4s:json4s-jackson-core_2.13": [
      "org.json4s.jackson"
    ],
-    "org.json4s:json4s-native-core_3": [
+    "org.json4s:json4s-native-core_2.13": [
      "org.json4s.native"
    ],
-    "org.json4s:json4s-native_3": [
+    "org.json4s:json4s-native_2.13": [
      "org.json4s.native"
    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.json4s.scalap",
+      "org.json4s.scalap.scalasig"
+    ],
    "org.ow2.asm:asm": [
      "org.objectweb.asm",
      "org.objectweb.asm.signature"
@@ -1870,7 +1881,7 @@
    "org.reactivestreams:reactive-streams": [
      "org.reactivestreams"
    ],
-    "org.scala-lang.modules:scala-collection-compat_3": [
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
      "scala.collection.compat",
      "scala.collection.compat.immutable",
      "scala.util.control.compat",
@@ -1909,26 +1920,22 @@
      "scala.util.hashing",
      "scala.util.matching"
    ],
-    "org.scala-lang:scala3-library_3": [
-      "scala",
-      "scala.annotation",
-      "scala.annotation.internal",
-      "scala.annotation.unchecked",
-      "scala.compiletime",
-      "scala.compiletime.ops",
-      "scala.compiletime.testing",
-      "scala.deriving",
-      "scala.quoted",
-      "scala.quoted.runtime",
-      "scala.reflect",
-      "scala.runtime",
-      "scala.runtime.coverage",
-      "scala.runtime.function",
-      "scala.runtime.stdLibPatches",
-      "scala.util",
-      "scala.util.control"
+    "org.scala-lang:scala-reflect": [
+      "scala.reflect.api",
+      "scala.reflect.internal",
+      "scala.reflect.internal.annotations",
+      "scala.reflect.internal.pickling",
+      "scala.reflect.internal.settings",
+      "scala.reflect.internal.tpe",
+      "scala.reflect.internal.transform",
+      "scala.reflect.internal.util",
+      "scala.reflect.io",
+      "scala.reflect.macros",
+      "scala.reflect.macros.blackbox",
+      "scala.reflect.macros.whitebox",
+      "scala.reflect.runtime"
    ],
-    "org.scalamock:scalamock_3": [
+    "org.scalamock:scalamock_2.13": [
      "org.scalamock",
      "org.scalamock.clazz",
      "org.scalamock.context",
@@ -1939,8 +1946,6 @@
      "org.scalamock.scalatest",
      "org.scalamock.scalatest.proxy",
      "org.scalamock.specs2",
-      "org.scalamock.stubs",
-      "org.scalamock.stubs.internal",
      "org.scalamock.util"
    ],
    "org.slf4j:slf4j-api": [
@@ -2272,14 +2277,14 @@
      "com.google.truth:truth",
      "com.squareup.okhttp:okhttp",
      "com.squareup.okio:okio",
-      "com.thesamet.scalapb:compilerplugin_3",
-      "com.thesamet.scalapb:lenses_3",
+      "com.thesamet.scalapb:compilerplugin_2.13",
+      "com.thesamet.scalapb:lenses_2.13",
      "com.thesamet.scalapb:protoc-bridge_2.13",
-      "com.thesamet.scalapb:protoc-bridge_3",
      "com.thesamet.scalapb:protoc-gen_2.13",
-      "com.thesamet.scalapb:scalapb-json4s_3",
-      "com.thesamet.scalapb:scalapb-runtime-grpc_3",
-      "com.thesamet.scalapb:scalapb-runtime_3",
+      "com.thesamet.scalapb:scalapb-json4s_2.13",
+      "com.thesamet.scalapb:scalapb-runtime-grpc_2.13",
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "com.thoughtworks.paranamer:paranamer",
      "commons-codec:commons-codec",
      "commons-logging:commons-logging",
      "dev.dirs:directories",
@@ -2325,17 +2330,18 @@
      "org.jetbrains.kotlin:kotlin-stdlib",
      "org.jetbrains.kotlin:kotlin-stdlib-common",
      "org.jetbrains:annotations",
-      "org.json4s:json4s-ast_3",
-      "org.json4s:json4s-core_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.json4s:json4s-native-core_3",
-      "org.json4s:json4s-native_3",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.json4s:json4s-native_2.13",
+      "org.json4s:json4s-scalap_2.13",
      "org.ow2.asm:asm",
      "org.reactivestreams:reactive-streams",
-      "org.scala-lang.modules:scala-collection-compat_3",
+      "org.scala-lang.modules:scala-collection-compat_2.13",
      "org.scala-lang:scala-library",
-      "org.scala-lang:scala3-library_3",
-      "org.scalamock:scalamock_3",
+      "org.scala-lang:scala-reflect",
+      "org.scalamock:scalamock_2.13",
      "org.slf4j:slf4j-api",
      "org.slf4j:slf4j-simple",
      "software.amazon.awssdk:annotations",
@@ -1,310 +0,0 @@
-# Scala 3 Migration: Reflection Issues Found
-
-This document catalogs all reflection-related problems discovered during the Scala 2.13.16 → Scala 3.7.2 migration of the Eagle0 codebase.
-
-## Summary
-
-The migration revealed several categories of reflection issues that needed to be addressed for Scala 3 compatibility:
-
-1. **Scala 2 Runtime Reflection API** - No longer available in Scala 3
-2. **Settings System Reflection** - Custom reflection for loading settings singletons 
-3. **json4s Automatic Case Class Extraction** - Uses reflection that fails with Scala 3 metaprogramming classes
-4. **ScalaTest Exception Handling** - Syntax changes affecting exception variable binding
-
-## 1. Scala 2 Runtime Reflection (FIXED)
-
-### Issue
-Tests using `scala.reflect.runtime.universe` fail because this reflection API doesn't exist in Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-### Error
-```scala
-import scala.reflect.runtime.universe  // Not available in Scala 3
-```
-
-### Solution Applied
-**Deleted the test entirely** as it was redundant. The test was verifying that auto-generated Scala objects (created by Bazel from proto enum values) matched their source proto values - something already guaranteed by the build system. Since the objects are generated directly from the proto definitions, this test provided no value.
-
-**Files deleted:**
- `src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-## 2. Settings System Reflection (FIXED)
-
-### Issue
-Custom `SettingsLoader` class used reflection to access Scala object singletons, but the reflection pattern changed between Scala 2 and Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/settings/loaders/SettingsLoader.scala`
-
-### Error
-```
-java.lang.NoSuchMethodException: net.eagle0.eagle.library.settings.ApprehendOutlawVigorCost$.MODULE$
-```
-
-### Root Cause
-In Scala 2, singleton objects are accessed via `ClassName$.MODULE$()`, but in Scala 3, they're accessed directly via `ClassName$` field. Additionally, `scala.reflect.runtime.universe` is not available in Scala 3.
-
-### Solution Applied
-**Completely eliminated reflection** by auto-generating the entire `SettingsLoader.scala` file from BUILD.bazel definitions:
-
-1. **Created generator**: `src/main/go/net/eagle0/build/settings_loader_generator/settings_loader_generator.go` - parses BUILD.bazel and generates complete SettingsLoader.scala with pattern matching for all 272 settings
-
-2. **Added genrule**: In `src/main/scala/net/eagle0/eagle/library/settings/loaders/BUILD.bazel`:
-```python
-genrule(
-    name = "settings_loader_src",
-    srcs = ["//src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel"],
-    outs = ["SettingsLoader.scala"],
-    cmd = "$(location //src/main/go/net/eagle0/build/settings_loader_generator) $(location //src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel) > $@",
-    tools = ["//src/main/go/net/eagle0/build/settings_loader_generator"],
-)
-```
-
-3. **Result**: SettingsLoader now uses compile-time pattern matching instead of reflection:
-```scala
-private def settingObjectForKey(key: String): Any = key match {
-  case "ActionVigorCost" => ActionVigorCost
-  case "BaseFoodBuyPrice" => BaseFoodBuyPrice
-  // ... all 272 settings auto-generated
-  case _ => throw NoSuchSettingException(key)
-}
-```
-
-### Benefits
- **No reflection** - Completely Scala 3 compatible
- **Maintainable** - New settings automatically included when added to BUILD.bazel
- **Performance** - Pattern matching is faster than reflection
- **Type-safe** - Compile-time checking of all settings
-
-## 3. json4s Reflection Issues (MULTIPLE LOCATIONS)
-
-### 3.1 EagleServiceImpl JSON Serialization (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/service/EagleServiceImpl.scala`
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-```
-
-#### Root Cause
-json4s automatic case class serialization uses reflection that tries to access Scala 3 metaprogramming classes (`scala.quoted.staging.package$`) which aren't available at runtime.
-
-#### Solution Applied
-Replaced automatic json4s serialization with ScalaPB's built-in JSON support:
-
-```scala
-// Old (reflection-based):
-// implicit val formats: DefaultFormats.type = DefaultFormats
-// write(actionResultView)
-
-// New (ScalaPB JSON support):
-import scalapb.json4s.JsonFormat
-JsonFormat.toJsonString(actionResultView.toProto)
-```
-
-### 3.2 ShardokMapInfo JSON Parsing (FIXED)
-
-#### Files Affected  
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala` (Line 44)
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-at org.json4s.reflect.ScalaSigReader$.readConstructor(ScalaSigReader.scala:42)
-```
-
-#### Root Cause
-The line `val extracted = parsedJson.extract[List[ShardokMapInfo]]` uses json4s automatic case class extraction which relies on reflection.
-
-#### Solution Applied
-Replaced automatic extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val extracted = parsedJson.extract[List[ShardokMapInfo]]
-
-// NEW (manual parsing, no reflection):
-val extracted = parsedJson match {
-  case JArray(items) => items.map { item =>
-    val name = (item \ "name").extract[String]
-    val castleCount = (item \ "castleCount").extract[Int] 
-    val positions = (item \ "positions").extract[Map[Int, Int]]
-    ShardokMapInfo(name, castleCount, positions)
-  }
-  case _ => throw new Exception("Expected JSON array for map info")
-}
-```
-
-#### Testing
-The fix was verified - `attack_command_chooser_test` now passes successfully.
-
-### 3.3 HeroNameFetcher JSON Parsing (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
-
-#### Issue  
-Case class extraction `parsedJson.extract[ResponseBody]` uses reflection that may fail in Scala 3.
-
-#### Solution Applied
-Replaced automatic case class extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val parsedJson = json.parse(src.getLines().mkString)
-parsedJson.extract[ResponseBody]
-
-// NEW (manual parsing, no reflection):
-parsedJson \ "names" match {
-  case JArray(nameArray) => 
-    nameArray.map { nameObj =>
-      val id = (nameObj \ "id").extract[String]
-      val name = (nameObj \ "name").extract[String]
-      NameResponse(id, name)
-    }.toVector
-  case _ => throw new Exception("Expected 'names' array in response")
-}
-```
-
-#### Testing
-The fix was verified - HeroNameFetcher now builds successfully without reflection.
-
-### 3.4 Other json4s Usage Analysis
-
-#### Files with json4s extraction:
- **✅ SAFE**: OpenAI/Claude Services - Only extract simple types (`String`, `Int`) - no reflection
- **✅ FIXED**: `HeroNameFetcher.scala` - Replaced `extract[ResponseBody]` with manual parsing (no reflection)
- **⚠️ POTENTIAL ISSUES** (not currently causing failures but should be monitored):
-  - `JsonUtils.scala`: `extract[Map[String, Vector[String]]]` - complex type extraction
-  - `HexMapJsonUtils.scala`: `extract[List[JObject]]` - may be problematic
-
-#### Recommendation
-Apply the same manual parsing pattern to remaining case class extractions if they cause runtime failures during Scala 3 migration.
-
-## 4. ScalaTest Exception Handling Syntax (FIXED)
-
-### Issue
-Scala 3 changed how exception variables are bound in ScalaTest's `the[Exception] thrownBy {...}` construct.
-
-### Files Affected
-**70+ test files** across the codebase using exception testing patterns.
-
-### Error Pattern
-```
-Not found: ex
-```
-
-### Root Cause
-In Scala 2: `the[Exception] thrownBy { ... }` automatically creates an `ex` variable.
-In Scala 3: The exception variable must be explicitly bound.
-
-### Solution Applied
-Added explicit variable binding across all affected test files:
-
-```scala
-// Old Scala 2 syntax:
-the[EagleCommandException] thrownBy {
-  // test code
-}
-ex.getMessage shouldBe "expected message"
-
-// New Scala 3 syntax:
-val ex = the[EagleCommandException] thrownBy {
-  // test code  
-}
-ex.getMessage shouldBe "expected message"
-```
-
-### Script Used
-Created and ran a systematic fix script that processed 70+ files:
-
-```bash
-# Pattern to find and fix exception handling
-find . -name "*.scala" -exec sed -i '' 's/the\[\([^]]*\)\] thrownBy {/val ex = the[\1] thrownBy {/g' {} \;
-```
-
-## 5. ScalaTest Import Changes (FIXED)
-
-### Issue
-Scala 3 requires different imports for ScalaTest matchers.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/impl/command/DeclineQuestCommandTest.scala`
-
-### Error
-```
-value convertToAnyShouldWrapper is not a member of object org.scalatest.matchers.should.Matchers
-```
-
-### Solution Applied
-Changed from specific imports to wildcard import:
-
-```scala
-// Old:
-import org.scalatest.matchers.should.Matchers.{convertToAnyShouldWrapper, the}
-
-// New:
-import org.scalatest.matchers.should.Matchers.*
-```
-
-## 6. Mock Framework Issues (FIXED)
-
-### Issue
-ScalaMock had type inference issues with Scala 3 for classes with constructor parameters.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/EngineImplTest.scala`
-
-### Error
-```
-Found: Vector
-Required: Vector[net.eagle0.eagle.library.util.hero_generator.hero_with_name.HeroWithName]
-```
-
-### Root Cause
-Mock framework couldn't properly infer types for `mock[HeroGenerator]` where `HeroGenerator` has constructor parameters.
-
-### Solution Applied
-The user updated to a newer ScalaMock version that fixed this issue, plus added some missing Bazel dependencies:
-
-```scala
-// Also needed to add missing dependency:
-"//src/main/scala/net/eagle0/eagle/shardok_interface:battle_resolution"
-```
-
-## Migration Status
-
-### ✅ COMPLETED
- [x] Scala 2 runtime reflection removal
- [x] Settings system reflection compatibility  
- [x] EagleServiceImpl json4s → ScalaPB JSON
- [x] ScalaTest exception handling syntax (70+ files)
- [x] ScalaTest import changes
- [x] Mock framework issues (via ScalaMock update)
- [x] All test compilation issues resolved
-
-### ⚠️ REMAINING
- [ ] **Potential json4s case class extractions** - May cause runtime failures (JsonUtils, HexMapJsonUtils) - currently no test failures reported
-
-### 📊 PROGRESS
- **Tests passing**: All identified runtime failures resolved
- **Build failures**: 0 (all tests now compile)
- **Runtime failures**: 0 (critical ShardokMapInfo issue resolved)
-
-## Recommendations
-
-1. **✅ COMPLETED**: ShardokMapInfo json4s reflection issue resolved with manual parsing
-2. **Monitor remaining json4s usage**: Watch for runtime failures in HeroNameFetcher, JsonUtils, and HexMapJsonUtils during full Scala 3 migration
-3. **Consider ScalaPB for new JSON needs**: For new functionality, prefer ScalaPB's JSON support to avoid reflection entirely
-4. **Apply manual parsing pattern**: If other json4s case class extractions cause runtime failures, use the same manual parsing approach demonstrated in ShardokMapInfo
-
-## Key Learnings
-
- **Scala 3 reflection changes**: Major differences in singleton object access patterns
- **json4s compatibility**: Automatic case class extraction doesn't work well with Scala 3 metaprogramming
- **ScalaPB advantage**: Using ScalaPB's JSON support avoids reflection issues entirely
- **Systematic approach**: Many issues followed patterns that could be fixed with scripts across multiple files
@@ -22,6 +22,13 @@ cc_library(
    visibility = ["//visibility:public"],
 )

+cc_library(
+    name = "container_utils",
+    hdrs = ["ContainerUtils.hpp"],
+    copts = COPTS,
+    visibility = ["//visibility:public"],
+)
+
 cc_library(
    name = "filesystem_utils",
    srcs = ["FilesystemUtils.cpp"],
@@ -7,23 +7,12 @@

 #include <cstdint>

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

-// FNV-1a algorithm: XOR first, then multiply
 static inline auto MixIn(uint64_t& hash, const uint8_t byte) {
-    hash ^= byte;
-    hash *= FNV_PRIME;
-}
-
-// Hash an entire buffer using FNV-1a
-static inline auto HashBuffer(const uint8_t* data, size_t size) -> uint64_t {
-    uint64_t hash = FNV_OFFSET_BASIS;
-    if (data != nullptr) {
-        for (size_t i = 0; i < size; ++i) { MixIn(hash, data[i]); }
-    }
-    return hash;
+    hash = hash * FNV_PRIME;
+    hash = hash ^ byte;
 }

 #endif  // EAGLE0_BYTEHASHER_HPP
@@ -0,0 +1,173 @@
+//
+// Created by Dan Crosby on 12/25/20.
+//
+
+#ifndef EAGLE0_CONTAINERUTILS_HPP
+#define EAGLE0_CONTAINERUTILS_HPP
+
+#include <algorithm>
+#include <functional>
+#include <optional>
+
+namespace common {
+
+using std::allocator;
+using std::back_inserter;
+using std::begin;
+using std::copy_if;
+using std::count_if;
+using std::end;
+using std::find;
+using std::find_if;
+using std::function;
+using std::optional;
+using std::remove_if;
+using std::vector;
+
+template<class T, class Container>
+auto Contains(const Container& container, const T& elt) -> bool {
+    return find(begin(container), end(container), elt) != end(container);
+}
+
+template<class Container, class Func>
+auto CountIf(const Container& container, Func fn) -> size_t {
+    Container result{};
+    return count_if(begin(container), end(container), fn);
+}
+
+template<class Container, class Func>
+void FilterInPlace(Container& container, Func fn) {
+    container.erase(
+            remove_if(begin(container), end(container), [fn](const auto& elt) { return !fn(elt); }),
+            end(container));
+}
+
+template<class Container, class Func>
+auto Filtered(const Container& container, Func fn) -> Container {
+    Container result{};
+    copy_if(begin(container), end(container), back_inserter(result), fn);
+
+    return result;
+}
+
+template<class Container, class Func>
+auto FilteredToVector(const Container& container, Func fn) -> decltype(auto) {
+    typedef typename Container::value_type value_type;
+    vector<value_type> result{};
+    copy_if(begin(container), end(container), back_inserter(result), fn);
+
+    return result;
+}
+
+template<typename Container, typename Func>
+auto FindIf(const Container& container, Func fn) -> optional<typename Container::value_type> {
+    const auto& t = find_if(begin(container), end(container), fn);
+
+    if (t == end(container)) {
+        return {};
+    } else {
+        return optional<typename Container::value_type>(*t);
+    }
+}
+
+template<typename Container, typename Func>
+auto ContainsWhere(const Container& container, Func fn) -> bool {
+    return find_if(begin(container), end(container), fn) != end(container);
+}
+
+template<
+        template<typename, typename>
+        class TwoTypeContainer,
+        typename T,
+        typename Allocator = allocator<T>,
+        typename Func>
+auto Map(const TwoTypeContainer<T, Allocator>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    TwoTypeContainer<result_type, allocator<result_type>> result{};
+    result.reserve(input.size());
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<template<typename> class OneTypeContainer, typename T, typename Func>
+auto Map(const OneTypeContainer<T>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    OneTypeContainer<result_type> result{};
+    result.reserve(input.size());
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<typename Container, typename Func>
+auto MapToVector(const Container& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type result_type;
+
+    vector<result_type> result{};
+
+    transform(begin(input), end(input), back_inserter(result), fn);
+    return result;
+}
+
+template<
+        template<typename, typename>
+        class TwoTypeContainer,
+        typename T,
+        typename Allocator = allocator<T>,
+        typename Func>
+auto FlatMap(const TwoTypeContainer<T, Allocator>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type result_value_type;
+
+    TwoTypeContainer<result_value_type, allocator<result_value_type>> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<template<typename> class OneTypeContainer, typename T, typename Func>
+auto FlatMap(const OneTypeContainer<T>& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type result_value_type;
+
+    OneTypeContainer<result_value_type> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<typename Container, typename Func>
+auto FlatMapToVector(const Container& input, Func fn) -> decltype(auto) {
+    typedef typename decltype(function(fn))::result_type::value_type value_type;
+
+    vector<value_type> result{};
+
+    for (const auto& elt : input) {
+        const auto& outContainer = fn(elt);
+        for (const auto& outElt : outContainer) { result.push_back(outElt); }
+    }
+    return result;
+}
+
+template<typename Container>
+auto ToVector(const Container& input) -> decltype(auto) {
+    typedef typename Container::value_type value_type;
+    return vector<value_type>(begin(input), end(input));
+}
+
+template<typename C1, typename C2>
+auto Append(C1& recipient, const C2& newItems) -> C1& {
+    recipient.insert(end(recipient), begin(newItems), end(newItems));
+    return recipient;
+}
+
+}  // namespace common
+
+#endif  // EAGLE0_CONTAINERUTILS_HPP
@@ -145,7 +145,7 @@ auto FilesystemUtils::LoadFromPath(const string& path) -> byte_vector {
    const std::streamsize size = inputFileStream.tellg();
    inputFileStream.seekg(0, std::ios::beg);

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

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

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

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

 auto StdLibraryGenerator::IntBetween(const int min, const int max) -> int {
    std::uniform_int_distribution<int> unifInt(min, max - 1);
@@ -8,8 +8,6 @@ namespace shardok {

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 namespace shardok {

@@ -36,7 +36,7 @@ auto CalculateMap(
            .name = mapName,
            .positionsRequiringCrossing = {}};

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

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

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

 #include <iostream>
-#include <memory>

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

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

-            outputStream << "      \"" << position << "\": " << count;
+            outputStream << "      \"" << kv.first << "\": " << kv.second;
        }
        outputStream << endl << "    }" << endl << "  }";
    }
@@ -4,9 +4,6 @@

 #include "AIAttackGroups.hpp"

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

 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -224,15 +221,11 @@ auto GenerateTargetPriorities(
                    Power(unit);
        }

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

    return allTargetsUnitsAndDistances;
@@ -4,7 +4,6 @@

 #include "AIAttackerStrategySelector.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"

@@ -12,21 +11,21 @@ namespace shardok {

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

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

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

    vector<const Unit*> attackerUnits{};
@@ -41,6 +40,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
        if (pi != nullptr) {
            if (pi->is_defender()) {
                if (unit->location().row() >= 0) {
+                    defenderTroops += unit->battalion().size();
+
                    if (criticalTileCoords.Contains(unit->location())) {
                        ++defenderOccupiedCriticalTileCount;
                    }
@@ -49,6 +50,7 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                }
            } else if (unit->player_id() == attackerPid) {
                ++attackerUnitCount;
+                attackerTroops += unit->battalion().size();
                if (unit->can_flee()) canFlee = true;
                attackerUnits.push_back(unit);
            } else {
@@ -58,13 +60,7 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
    }

    AIStrategy chosenStrategy;
-
-    // Use sophisticated combat success estimation instead of simple troop ratio
-    if (canFlee && AIFleeDecisionCalculator::ShouldConsiderFleeing(
-                           attackerPid,
-                           gameState,
-                           settings,
-                           FLEE_CONSIDERATION_THRESHOLD)) {
+    if (canFlee && attackerTroops < MAXIMUM_RATIO_FOR_ATTACKER_TO_FLEE * defenderTroops) {
        chosenStrategy = FleeStrategy;
    } else if (const CoordsSet startCrossingLocations =
                       waterCrossingCommandChooser
@@ -8,16 +8,18 @@
 #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/ai/AIWaterCrossingCommandChooser.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"

 namespace shardok {

+using GameState = net::eagle0::shardok::storage::fb::GameState;
+
 class AIAttackerStrategySelector {
 public:
    static auto BestAttackerStrategy(
            PlayerId attackerPid,
-            const GameStateW& gameState,
+            const GameState* gameState,
            const CoordsSet& criticalTileCoords,
            const APDCache& apdCache,
            const ALCache& alCache,
@@ -20,8 +20,8 @@ CoordsSet AICommandFilter::BuildEnemyLocations(const GameStateW& gameState, Play
    CoordsSet enemyLocations(gameState->hex_map());
    const auto* units = gameState->units();

-    for (size_t i = 0; i < units->size(); ++i) {
-        const auto* unit = units->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < units->size(); ++i) {
+        const auto* unit = units->Get(i);
        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            unit->player_id() != pid && !unit->hidden() && unit->location().column() != -1) {
            enemyLocations.Add(unit->location());
@@ -486,12 +486,12 @@ bool AICommandFilter::IsWastefulMovement(
 }

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

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

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

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

 bool AICommandFilter::WouldAbandonCriticalCastle(
-        const ShardokCommand& /*cmd*/,
-        PlayerId /*pid*/,
-        const GameStateW& /*gameState*/) {
+        const ShardokCommand& cmd,
+        PlayerId pid,
+        const GameStateW& gameState) {
    // Simplified implementation - return false for now
    // TODO: Implement proper castle abandonment detection when API is available
    return false;
@@ -1,19 +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 (original)
-    MCTS_CLEAN            // Clean MCTS implementation with fixed simulation perspective
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_CONFIG_HPP
@@ -4,9 +4,6 @@

 #include "AIDefenderStrategySelector.hpp"

-#include <algorithm>
-#include <ranges>
-
 #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/library/util/HexMapUtils.hpp"
@@ -17,7 +14,7 @@ constexpr double MAXIMUM_RATIO_FOR_DEFENDER_TO_FLEE = 0.15;
 constexpr double MINIMUM_RATIO_FOR_DEFENDER_TO_HOLD = 0.60;

 auto AIDefenderStrategySelector::BestDefenderStrategy(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const CoordsSet& criticalTileCoords,
        const APDCache& apdCache,
        const SettingsGetter& settings) -> AIStrategy {
@@ -60,9 +57,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                    net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD) {
                    ++attackerNonUndeadUnitCount;

-                    if (!std::ranges::contains(
-                                attackerUnitIdsRequiringWaterCrossing,
-                                unit->unit_id())) {
+                    if (!common::Contains(attackerUnitIdsRequiringWaterCrossing, unit->unit_id())) {
                        ++attackerNonUndeadUnitNotRequiringWaterCrossingCount;
                    }
                }
@@ -7,15 +7,16 @@

 #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/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"

 namespace shardok {
 class AIDefenderStrategySelector {
+    using GameState = net::eagle0::shardok::storage::fb::GameState;
+
 public:
    static auto BestDefenderStrategy(
-            const GameStateW& gameState,
+            const GameState* gameState,
            const CoordsSet& criticalTileCoords,
            const APDCache& apdCache,
            const SettingsGetter& settings) -> AIStrategy;
@@ -1,228 +0,0 @@
-//
-//  AIFleeDecisionCalculator.cpp
-//  eagle0
-//
-//  Handles AI flee decision logic including combat success estimation
-//  and flee vs fight evaluation for final round scenarios
-//
-
-#include "AIFleeDecisionCalculator.hpp"
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-
-namespace shardok {
-
-auto AIFleeDecisionCalculator::GetFleeCommandIndex(
-        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,
-        const SettingsGetter& settings) -> double {
-    if (gameState->status() == nullptr ||
-        gameState->status()->state() !=
-                net::eagle0::shardok::storage::fb::GameStatus_::State_GAME_RUNNING) {
-        return 1.0;  // we're still in set_up so we can't really evaluate
-    }
-
-    // Combat success estimation based on unit power, heroes, and capture dynamics
-    double attackerPower = 0.0;
-    double defenderPower = 0.0;
-    int attackerTroops = 0;  // Still track raw troops for special cases
-    int defenderTroops = 0;
-    int attackerUnits = 0;
-    int defenderUnits = 0;
-    int attackerHeroes = 0;
-    int defenderHeroes = 0;
-    bool defenderHasVips = false;
-
-    // Calculate total power and count units/heroes for each side
-    for (const auto* unit : *gameState->units()) {
-        if (unit->status() != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;
-
-        const auto* pi = PlayerInfoForPid(gameState, unit->player_id());
-        if (pi == nullptr) continue;
-
-        const int unitTroops = unit->battalion().size();
-        const bool hasHero = unit->has_attached_hero();
-        const double unitPower = ContextFreeUnitValue(unit);
-
-        if (pi->is_defender()) {
-            defenderPower += unitPower;
-            defenderTroops += unitTroops;
-            defenderUnits++;
-            if (hasHero) {
-                defenderHeroes++;
-                if (unit->attached_hero().is_vip()) { defenderHasVips = true; }
-            }
-        } else if (unit->player_id() == attackerPlayerId) {
-            attackerPower += unitPower;
-            attackerTroops += unitTroops;
-            attackerUnits++;
-            if (hasHero) { attackerHeroes++; }
-        }
-    }
-
-    const int roundsRemaining = settings.Backing().max_rounds() - gameState->current_round();
-
-    // Special case: Attacker has no heroes - automatic loss
-    if (attackerHeroes == 0) {
-        return 0.0;  // Cannot win without heroes
-    }
-
-    // Special case: Defender has no heroes - automatic win for attacker
-    if (defenderHeroes == 0) {
-        return 1.0;  // Guaranteed win
-    }
-
-    // Special case: Attacker has no troops (but has heroes)
-    if (attackerTroops == 0) {
-        // Very difficult to win with heroes alone
-        return 0.05;  // Extremely low chance
-    }
-
-    // Special case: Defender has no troops but has heroes
-    if (defenderTroops == 0) {
-        // Defenders with only heroes are vulnerable to capture
-        // Only truly difficult if time is extremely limited
-        if (roundsRemaining <= 1) {
-            // Last round - very hard to capture all heroes
-            return 0.3;  // Low but not impossible
-        } else if (roundsRemaining <= 2) {
-            return 0.6;  // Still achievable
-        } else {
-            // With 3+ rounds, capturing defenseless heroes is quite feasible
-            return 0.85;  // High probability of success
-        }
-    }
-
-    // Normal case: Both sides have troops
-    // Base probability from power ratio (accounts for unit quality, not just quantity)
-    const double powerRatio = attackerPower / std::max(1.0, defenderPower);
-    double baseProbability = std::min(0.95, std::max(0.05, powerRatio * 0.5));
-
-    // Adjust for time pressure - attackers need to win before time runs out
-    if (roundsRemaining <= 1) {
-        baseProbability *= 0.6;  // Severe penalty for last round
-    } else if (roundsRemaining <= 3) {
-        baseProbability *= 0.8;  // Moderate penalty
-    }
-
-    // Adjust for unit count (more units = better tactical flexibility)
-    const double unitRatio =
-            static_cast<double>(attackerUnits) / std::max(1.0, static_cast<double>(defenderUnits));
-    if (unitRatio < 0.5) {
-        baseProbability *= 0.8;
-    } else if (unitRatio > 1.5) {
-        baseProbability *= 1.15;
-    }
-
-    // Adjust for hero presence
-    if (defenderHeroes > attackerHeroes && defenderHasVips) {
-        // Defender has more heroes including VIPs - harder to capture
-        baseProbability *= 0.85;
-    }
-
-    return std::min(0.95, std::max(0.05, baseProbability));
-}
-
-auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
-        PlayerId playerId,
-        const SettingsGetter& settingsGetter,
-        const GameStateW& guessedState,
-        const vector<CommandProto>& availableCommands,
-        const vector<CommandProto>::const_iterator& fleeCommand,
-        bool enableDebugLogging) -> FleeDecision {
-    // Get flee success odds
-    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);
-    }
-
-    // Check if flee odds are good enough to attempt
-    if (fleeSuccessChance >= minimumFleeOddsThreshold) {
-        if (enableDebugLogging) {
-            printf("AI FinalRound: Good flee odds (%d%% >= %d%%), choosing flee\n",
-                   fleeSuccessChance,
-                   minimumFleeOddsThreshold);
-        }
-        return FleeDecision{
-                true,
-                GetFleeCommandIndex(fleeCommand, availableCommands),
-                "Good flee odds"};
-    }
-
-    // Low flee odds - evaluate if fighting might be better
-    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) {
-        if (enableDebugLogging) {
-            printf("AI FinalRound: Combat hopeless (%.1f%%), desperate flee attempt (%d%%)\n",
-                   combatWinChance * 100,
-                   fleeSuccessChance);
-        }
-        return FleeDecision{
-                true,
-                GetFleeCommandIndex(fleeCommand, availableCommands),
-                "Combat hopeless, desperate flee"};
-    }
-
-    // Detailed flee vs fight comparison
-    const double fleeChance = static_cast<double>(fleeSuccessChance) / 100.0;
-
-    // Compare expected outcomes:
-    // - Flee: fleeChance of survival (not victory, but avoiding loss)
-    // - Fight: combatWinChance of victory (better than survival)
-
-    constexpr double FLEE_VS_COMBAT_MARGIN =
-            0.8;  // Require 80% of combat chance to prefer fighting
-    const double adjustedCombatThreshold = combatWinChance * FLEE_VS_COMBAT_MARGIN;
-
-    if (enableDebugLogging) {
-        printf("AI FinalRound: Flee=%d%%, Combat=%.1f%%, Threshold=%.1f%% -> ",
-               fleeSuccessChance,
-               combatWinChance * 100,
-               adjustedCombatThreshold * 100);
-    }
-
-    if (fleeChance > adjustedCombatThreshold) {
-        if (enableDebugLogging) { printf("FLEE (better odds)\n"); }
-        return FleeDecision{
-                true,
-                GetFleeCommandIndex(fleeCommand, availableCommands),
-                "Flee has better expected outcome"};
-    } else {
-        if (enableDebugLogging) { printf("FIGHT (better expected outcome)\n"); }
-        // Return 0 to indicate we should use standard command selection
-        return FleeDecision{
-                false,
-                0,  // Will be replaced by StandardChooseCommandIndex
-                "Fighting has better expected outcome"};
-    }
-}
-
-auto AIFleeDecisionCalculator::ShouldConsiderFleeing(
-        PlayerId attackerPlayerId,
-        const GameStateW& guessedState,
-        const SettingsGetter& settings,
-        double fleeConsiderationThreshold) -> bool {
-    // Get combat success probability
-    const double combatSuccessChance =
-            EstimateCombatSuccess(attackerPlayerId, guessedState, settings);
-
-    // Consider fleeing if combat success chance is below threshold
-    return combatSuccessChance < fleeConsiderationThreshold;
-}
-
-}  // namespace shardok
@@ -1,67 +0,0 @@
-//
-//  AIFleeDecisionCalculator.hpp
-//  eagle0
-//
-//  Handles AI flee decision logic including combat success estimation
-//  and flee vs fight evaluation for final round scenarios
-//
-
-#ifndef AIFleeDecisionCalculator_hpp
-#define AIFleeDecisionCalculator_hpp
-
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-
-namespace shardok {
-
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-class AIFleeDecisionCalculator {
-public:
-    // Configuration for flee decision thresholds
-    struct FleeThresholds {
-        int minimumFleeOddsThreshold;  // Minimum flee success odds to consider fleeing
-        int desperateFleeThreshold;    // Flee threshold when combat is hopeless
-    };
-
-    // Result of flee vs fight evaluation
-    struct FleeDecision {
-        bool shouldFlee;
-        size_t commandIndex;    // Index of command to execute (flee or fight)
-        const char* reasoning;  // Debug explanation of decision
-    };
-
-    // Evaluate whether to flee or fight in the final round
-    [[nodiscard]] static auto EvaluateFleeVsFight(
-            PlayerId playerId,
-            const SettingsGetter& settings,
-            const GameStateW& guessedState,
-            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,
-            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,
-            const SettingsGetter& settings,
-            double fleeConsiderationThreshold = 0.5) -> bool;
-
-private:
-    // Helper to get flee command index
-    [[nodiscard]] static auto GetFleeCommandIndex(
-            const vector<CommandProto>::const_iterator& fleeCommand,
-            const vector<CommandProto>& availableCommands) -> size_t;
-};
-
-}  // namespace shardok
-
-#endif /* AIFleeDecisionCalculator_hpp */
@@ -5,11 +5,12 @@
 #ifndef EAGLE0_AISCORECALCULATOR_HPP
 #define EAGLE0_AISCORECALCULATOR_HPP

-#include <chrono>
 #include <future>

+#include "src/main/cpp/net/eagle0/common/ThreadPool.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/ai/AITimeBudget.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"
@@ -30,9 +31,111 @@ using ScoreValue = double;
 using CommandProto = net::eagle0::shardok::api::CommandDescriptor;

 class AIScoreCalculator {
+private:
+    // Static thread pool with 32 threads for parallel AI calculations
+    static inline eagle0::common::ThreadPool threadPool{32};
+
+public:
+    struct IndexAndScore {
+        size_t index;
+        CommandType type;
+        ScoreValue lookaheadScore;
+        ScoreValue immediateScore;
+    };
+
+private:
+    [[nodiscard]] static auto DefenderScatterStrategyScoreForState(
+            const GameStateW &gameState,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto DefenderHoldCastlesStrategyScoreForState(
+            const GameStateW &gameState,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto FleeStrategyScoreForState(
+            const GameStateW &gameState,
+            PlayerId playerId) -> ScoreValue;
+
+    [[nodiscard]] static auto DefenderScoreForState(
+            const GameStateW &gameState,
+            const AIStrategy &defenderStrategy,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    [[nodiscard]] static auto AttackerScoreForState(
+            const GameStateW &gameState,
+            const AIStrategy &attackerStrategy,
+            const CoordsSet &castleCoords,
+            int roundsRemaining,
+            const SettingsGetter &settings,
+            const ALCache &alCache,
+            const APDCache &apdCache) -> ScoreValue;
+
+    struct ImmediateAndLookaheadScore {
+        ScoreValue immediateScore;
+        future<eagle0::common::TaskResult<ScoreValue>> lookaheadScore;
+    };
+
+    static auto BasicLookaheadCalculator(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const shared_ptr<ShardokEngine> &innerEngine,
+            ScoreValue currentUtility,
+            const AIStrategy &attackerStrategy,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            const AITimeBudget *timeBudget = nullptr) -> ScoreValue;
+
+    static auto CalcOne(
+            PlayerId pid,
+            bool isDefender,
+            uint32_t commandIndex,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const std::shared_ptr<RandomGenerator> &randomGenerator,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            const AITimeBudget *timeBudget = nullptr) -> ImmediateAndLookaheadScore;
+
+    struct CommandEvaluationResult {
+        ScoreValue immediateScore;
+        ScoreValue lookaheadScore;
+    };
+
+    static auto EvaluateCommand(
+            PlayerId pid,
+            bool isDefender,
+            uint32_t commandIndex,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            const AITimeBudget *timeBudget = nullptr) -> CommandEvaluationResult;
+
 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,
@@ -42,7 +145,20 @@ public:
            const APDCache &apdCache,
            const ALCache &alCache) -> ScoreValue;

-    // Evaluates the score for a particular command index for the given player, using lookahead.
+    [[nodiscard]] static auto BestCommandIndex(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            const AITimeBudget *timeBudget = nullptr) -> IndexAndScore;
+
    [[nodiscard]] static auto CommandScore(
            PlayerId pid,
            bool isDefender,
@@ -56,7 +172,7 @@ public:
            const APDCache &apdCache,
            const ALCache &alCache,
            size_t commandIndex,
-            std::chrono::steady_clock::time_point deadline) -> std::future<ScoreValue>;
+            const AITimeBudget *timeBudget = nullptr) -> ScoreValue;
 };

 }  // namespace shardok
@@ -16,7 +16,7 @@ auto HasAttachedHeroWithProfession(
           unit->attached_hero().profession_info().profession() == profession;
 }

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

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

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

 #include <vector>

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

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

 }  // namespace shardok

@@ -32,8 +32,8 @@ auto CalculateTimeBudget(
    bool isClose = false;
    const auto *units = state->units();

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

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

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

            const auto &enemyCoords = enemyUnit->location();
@@ -80,7 +80,7 @@ auto CalculateTimeBudget(
    const auto remainingBudget = std::chrono::duration_cast<std::chrono::milliseconds>(budget);

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

    return AITimeBudget{
            .remainingBudget = remainingBudget,
@@ -31,7 +31,7 @@ public:
 // Configuration structure for iterative deepening time budget
 struct AITimeBudget {
    std::chrono::milliseconds remainingBudget;  // Time budget remaining (decremented as used)
-    size_t minDepthRequired;                    // Minimum depth from minLookaheadTurns
+    int minDepthRequired;                       // Minimum depth from minLookaheadTurns
    bool isCloseToEnemy;                        // Proximity flag for budget selection
 };

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

 #include <algorithm>
-#include <cstdlib>

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

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

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

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

-auto fearValue(const Unit * /*unit*/) -> double {
+auto fearValue(const Unit *unit) -> double {
    // TODO: make this depend on the value of the targets
    return kFearPossibleValue;
 }
@@ -343,8 +342,7 @@ auto UnitValue(
            unit->battalion().type() == net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD;

    const int coordsIndex = location.row() * map->column_count() + location.column();
-    const auto *terrain = map->terrain()->Get(coordsIndex);
-
+    const auto &terrain = map->terrain()->Get(coordsIndex);
    double castleMultiplier = 1.0;
    // Only give a multiplier for being in a castle if the castle is useful, and the unit is not
    // undead
@@ -360,8 +358,8 @@ auto UnitValue(
    {
        for (const auto adjacentCoords = HexMapUtils::GetAdjacentCoords(map, location);
             const auto &c : adjacentCoords) {
-            if (const auto *adjTerrain = GetTerrain(map, c);
-                adjTerrain && adjTerrain->modifier().fire().present()) {
+            if (const auto &adjTerrain = GetTerrain(map, c);
+                adjTerrain->modifier().fire().present()) {
                onFireMultiplier *= kAdjacentFireMultiplier;
            }
        }
@@ -416,7 +414,7 @@ auto UnitValue(
        if (const auto commandingUnitId = unit->commanding_unit_id(); commandingUnitId != -1) {
            const Unit *commandingUnit = nullptr;
            for (const Unit *attackerUnit : attackerUnits) {
-                if (attackerUnit && attackerUnit->unit_id() == commandingUnitId) {
+                if (attackerUnit->unit_id() == commandingUnitId) {
                    commandingUnit = attackerUnit;
                    break;
                }
@@ -424,7 +422,7 @@ auto UnitValue(

            if (commandingUnit == nullptr) {
                for (const Unit *defenderUnit : defenderUnits) {
-                    if (defenderUnit && defenderUnit->unit_id() == commandingUnitId) {
+                    if (defenderUnit->unit_id() == commandingUnitId) {
                        commandingUnit = defenderUnit;
                        break;
                    }
@@ -4,11 +4,9 @@

 #include "AIVictoryConditionScoreCalculator.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "AIAttackLocations.hpp"
 #include "AIDistanceDebuf.hpp"
+#include "src/main/cpp/net/eagle0/common/ContainerUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/victory_condition.hpp"
@@ -124,12 +122,12 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
 }

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

    const auto rc = gameState->hex_map()->row_count();
@@ -154,7 +152,7 @@ auto DefenderHoldsCriticalTilesVictoryScore(
 }

 auto AttackerHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
        const PlayerInfo* player,
        const APDCache& apdCache,
@@ -248,12 +246,12 @@ auto AttackerHoldsCriticalTilesVictoryScore(
 }

 auto LastPlayerStandingVictoryScore(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
        const SettingsGetter& settings) -> ScoreValue {
-    if (!std::ranges::contains(
+    if (!common::Contains(
                *player->victory_conditions(),
                net::eagle0::shardok::storage::fb::
                        VictoryCondition_VICTORY_CONDITION_LAST_PLAYER_STANDING)) {
@@ -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/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -24,7 +23,7 @@ using std::vector;
 using ScoreValue = double;

 auto AttackerHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
        const PlayerInfo* player,
        const APDCache& apdCache,
@@ -32,7 +31,7 @@ auto AttackerHoldsCriticalTilesVictoryScore(
        const SettingsGetter& settings) -> ScoreValue;

 auto DefenderHoldsCriticalTilesVictoryScore(
-        const GameStateW& gameState,
+        const net::eagle0::shardok::storage::fb::GameState* gameState,
        const CoordsSet& criticalTileLocations,
        const PlayerInfo* player,
        const APDCache& apdCache,
@@ -40,7 +39,7 @@ auto DefenderHoldsCriticalTilesVictoryScore(
        const SettingsGetter& settings) -> ScoreValue;

 auto LastPlayerStandingVictoryScore(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
@@ -11,7 +11,7 @@
 namespace shardok {

 auto UnitIdsRequiringWaterCrossing(
-        const GameStateW &gameState,
+        const GameState *gameState,
        const PlayerId pid,
        const CoordsSet &destinations,
        const APDCache &apdCache,
@@ -74,9 +74,9 @@ auto UnitIdsRequiringWaterCrossing(
 }

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

@@ -196,7 +196,7 @@ auto WaterCrossingTiles(

 // Returns the set of tiles that the attacker should try to approach in order to bridge/freeze
 auto IntendedCrossingStarts(
-        const GameStateW &gameState,
+        const GameState *gameState,
        const vector<UnitId> &unitIdsCreatingCrossing,
        const CoordsSet &tilesToStartCrossingFrom,
        const MapId &mapId,
@@ -5,7 +5,6 @@
 #ifndef EAGLE0_AIWATERCROSSINGCALCULATOR_HPP
 #define EAGLE0_AIWATERCROSSINGCALCULATOR_HPP

-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
@@ -30,7 +29,7 @@ static inline void AssertValid(const Coords& c, const HexMap* hexMap) {

 // Units that need a water crossing to reach at least one of the destinations
 auto UnitIdsRequiringWaterCrossing(
-        const GameStateW& gameState,
+        const GameState* gameState,
        PlayerId pid,
        const CoordsSet& destinations,
        const APDCache& apdCache,
@@ -38,7 +37,7 @@ auto UnitIdsRequiringWaterCrossing(

 // Units belonging to the player that are capable of creating water crossings
 auto UnitIdsToCreateWaterCrossing(
-        const GameStateW& gameState,
+        const GameState* gameState,
        PlayerId pid,
        const APDCache& apdCache,
        const SettingsGetter& settings) -> vector<UnitId>;
@@ -68,7 +67,7 @@ auto WaterCrossingTiles(

 // Returns the set of tiles that the attacker should try to approach in order to bridge/freeze
 auto IntendedCrossingStarts(
-        const GameStateW& gameState,
+        const GameState* gameState,
        const vector<UnitId>& unitIdsCreatingCrossing,
        const CoordsSet& tilesToStartCrossingFrom,
        const MapId& mapId,
@@ -4,10 +4,8 @@

 #include "AIWaterCrossingCommandChooser.hpp"

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

 namespace shardok {
@@ -19,10 +17,10 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:

 [[nodiscard]] auto AIWaterCrossingCommandChooser::WaterCrossingScore(
        const SettingsGetter &settingsGetter,
-        const GameStateW &gameState,
+        const GameState *gameState,
        const CoordsSet &castleCoords,
        const CoordsSet &startCrossingFrom) const -> ScoreValue {
-    uint32_t castleClaimCount = 0;
+    int castleClaimCount = 0;
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != playerId) continue;
        const auto status = unit->status();
@@ -85,7 +83,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
    // a large penalty
    for (const UnitId uid : unitIdsRequiringCrossing) {
        // If this unit ID can also create a crossing, we already handled it
-        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
+        if (common::Contains(unitIdsCreatingCrossing, uid)) continue;

        const Unit *unit = gameState->units()->Get(uid);
        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
@@ -121,11 +119,11 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:

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

-    uint32_t castleClaimCount = 0;
+    int castleClaimCount = 0;
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != playerId) continue;
        const auto status = unit->status();
@@ -8,7 +8,6 @@
 #include <utility>
 #include <vector>

-#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"
@@ -35,12 +34,12 @@ public:

    auto StartCrossingFrom(
            const SettingsGetter &settingsGetter,
-            const GameStateW &gameState,
+            const GameState *gameState,
            const CoordsSet &castleCoords) const -> CoordsSet;

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

-This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
-
-## AIScoreCalculator Function Reference
-
-### Public Interface Functions
-
-#### `GuessedStateScore`
-**Purpose**: Evaluates the score of a game state from the perspective of the current AI strategy without performing any commands.
-
-**Parameters**:
- `isDefender`: Whether the AI is playing as defender
- `state`: Current game state to evaluate
- `aiStrategy`: Strategy being used (attack castles, hold castles, scatter, etc.)
- `allCastleCoords`: Set of all castle coordinates on the map
- `settingsGetter`: Game configuration and rules
- `apdCache`: Cached action point distances for movement calculations
- `alCache`: Cached attack locations for combat calculations
-
-**Returns**: Score value representing how favorable the state is for the evaluating player (positive = good, negative = bad)
-
-#### `CommandScore`
-**Purpose**: Evaluates the score for a specific command using lookahead search to consider future consequences.
-
-**Parameters**:
- `pid`: Player ID executing the command
- `isDefender`: Whether the player is a defender
- `remainingLookahead`: Depth of recursive search remaining
- `maxRepeatCount`: Number of random simulations for non-deterministic commands
- `guessedEngine`: Current game engine state
- `attackerStrategy`: Strategy being used by attackers
- `currentUtility`: Current game state score before command execution
- `settingsGetter`: Game configuration
- `allCastleCoords`: Castle locations
- `apdCache` & `alCache`: Cached distance/attack calculations
- `commandIndex`: Index of command to evaluate
- `deadline`: Time limit for computation
-
-**Returns**: Future containing the final score after lookahead evaluation
-
-### Internal Core Functions
-
-#### `BuildDecisionTree` (NEW)
-**Purpose**: Builds a complete decision tree containing all evaluated command paths up to the specified depth.
-
-**Process**:
-1. Filters commands using `AICommandFilter` to reduce search space
-2. For each command, calls `ExecuteCommandForTree` to build complete subtrees
-3. Returns full tree with all possible moves and their consequences
-4. Identifies best command within the complete tree structure
-
-**Returns**: `std::future<CommandDecisionTree>` containing the complete decision tree
-
-#### `BestCommandIndex` (Legacy - Wrapper)
-**Purpose**: Backward compatibility wrapper that uses `BuildDecisionTree` but returns traditional `IndexAndScore`.
-
-**Process**:
-1. Calls `BuildDecisionTree` to get complete tree
-2. Extracts best command information for compatibility
-3. Returns only the optimal command details in legacy format
-
-#### `ExecuteCommandForTree` (NEW)
-**Purpose**: Executes a command and creates a tree node with the resulting game state and scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Creates `CommandTreeNode` with command results and game state
-3. Calculates immediate score using `GuessedStateScore`
-4. Calls `RecursiveTreeBuilder` to populate child nodes if depth allows
-5. Calculates lookahead score from children (or uses immediate score)
-
-**Returns**: `std::unique_ptr<CommandTreeNode>` containing the command execution results and subtree
-
-#### `RecursiveTreeBuilder` (NEW)
-**Purpose**: Recursively populates child nodes of a tree node by building subtrees for subsequent moves.
-
-**Process**:
-1. Gets available commands for the next player
-2. Filters commands to reduce search space
-3. For each command, calls `ExecuteCommandForTree` to create child nodes
-4. Handles different command types (deterministic, odds-based, random)
-5. Populates the parent node's children vector with complete subtrees
-
-#### `CalcOne` (Legacy)
-**Purpose**: Executes a single command simulation with specified randomness and returns both immediate and lookahead scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Calculates immediate score using `GuessedStateScore`
-3. Initiates recursive lookahead calculation if depth remains
-4. Handles timeouts gracefully by returning default scores
-
-#### `EvaluateCommand`
-**Purpose**: Lower-level command evaluation that handles different command types appropriately.
-
-**Command Type Handling**:
- **Deterministic**: Single evaluation with average randomness (0.5)
- **Odds-based**: Two evaluations (success/failure) weighted by success probability
- **Non-deterministic**: Multiple evaluations with distributed random values, averaged
-
-#### `BasicLookaheadCalculator`
-**Purpose**: Recursive lookahead search that finds the best future command sequence and propagates scores backward.
-
-**Features**:
- Uses transposition table to cache previously computed positions
- Handles depth limits and terminal states
- Returns futures for asynchronous computation
- Stores results in transposition table for reuse
-
-### Strategy-Specific Scoring Functions
-
-#### `AttackerScoreForState`
-**Purpose**: Calculates state score from attacker perspective based on strategy type.
-
-**Strategy Support**:
- `STRATEGY_ATTACK_CASTLES`: Prioritizes capturing castle positions
- `STRATEGY_ATTACK_UNITS`: Focuses on eliminating defender units
- `STRATEGY_HOLD_CASTLES`: Maintains control of captured castles
- `STRATEGY_CROSS_RIVERS`: Special water crossing objectives
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `DefenderScoreForState`
-**Purpose**: Calculates state score from defender perspective.
-
-**Strategy Support**:
- `STRATEGY_HOLD_CASTLES`: Defend critical castle positions
- `STRATEGY_SCATTER`: Spread units to avoid elimination
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `AttackerUnitsScore`
-**Purpose**: Core unit valuation function that calculates total value of all units on the board with contextual modifiers.
-
-**Features**:
- Uses `UnitValue` for individual unit calculations
- Applies distance multipliers based on proximity to objectives
- Handles special cases like undead, VIP units, and scattered defenders
- Incorporates castle bonuses and environmental penalties
-
-### Specialized Strategy Functions
-
-#### `DefenderScatterStrategyScoreForState`
-**Purpose**: Implements scatter strategy scoring that rewards defensive units for staying far from enemies and friendlies.
-
-#### `DefenderHoldCastlesStrategyScoreForState`
-**Purpose**: Implements castle defense strategy with victory condition scoring.
-
-#### `FleeStrategyScoreForState`
-**Purpose**: Implements flee strategy that heavily penalizes remaining on the battlefield.
-
-### Utility Functions
-
-#### `AttackerMultiplierForTargetDistance`
-**Purpose**: Calculates distance-based scoring multipliers for attackers based on proximity to priority targets.
-
-**Features**:
- Uses recursive priority list evaluation
- Accounts for occupied vs. unoccupied targets
- Incorporates brave water crossing capabilities
- Uses cached action point distances for efficiency
-
-#### `CommandSorter`
-**Purpose**: Comparison function for ranking commands by lookahead score (primary) and immediate score (tiebreaker).
-
-#### `IsDeterministic`
-**Purpose**: Determines if a command type has predictable outcomes or requires random simulation.
-
-### Performance and Caching
-
-#### `EffectiveDistanceCache`
-**Purpose**: Memoization cache for expensive distance calculations between units and targets.
-
-#### `AttackerScorePerformanceLogger`
-**Purpose**: Performance monitoring system that tracks call frequency and timing for `AttackerScoreForState`.
-
-The function architecture supports parallel evaluation, caching, and recursive lookahead while maintaining separation between strategy-specific logic and core evaluation mechanics.
-
-## Decision Tree Data Structures (NEW)
-
-### CommandTreeNode
-**Purpose**: Represents a single command execution and its consequences in the decision tree.
-
-**Key Fields**:
- `commandIndex`: Index of the command in the original command list
- `commandType`: Type of command (MOVE, MELEE, END_TURN, etc.)
- `immediateScore`: Score of the game state immediately after this command
- `lookaheadScore`: Best achievable score considering future moves
- `resultingGameState`: Game state after command execution
- `children`: Vector of child nodes representing subsequent possible moves
- `playerId`, `depth`, `isDefender`: Metadata about the command context
-
-**Features**:
- Stores complete game state for each decision point
- Maintains parent-child relationships for tree traversal
- Supports both immediate and lookahead scoring
- Contains metadata for debugging and analysis
-
-### CommandDecisionTree
-**Purpose**: Complete decision tree containing all evaluated command paths from a given position.
-
-**Key Fields**:
- `rootNodes`: All possible first moves from the starting position
- `bestCommand`: Pointer to the optimal root command
- `maxDepth`: Maximum lookahead depth of the tree
- `totalNodes`: Total number of nodes in the tree (for statistics)
-
-**Features**:
- Provides complete visibility into AI decision-making process
- Enables analysis of alternative moves and their consequences
- Supports tree statistics and debugging information
- Maintains backward compatibility through `GetBestCommandIndex()`
-
-**Memory Management**:
- Uses `std::unique_ptr` for automatic memory cleanup
- `GameStateW` objects are stored directly (not shared pointers for simplicity)
- Tree structure ensures proper cleanup when nodes go out of scope
-
-### Tree vs. Legacy Approach Comparison
-
-| Aspect | Legacy (Single Best) | Tree-Based (Complete) |
-|--------|---------------------|----------------------|
-| **Output** | Best command only | Complete decision tree |
-| **Memory** | Minimal | Higher (stores all paths) |
-| **Analysis** | Limited visibility | Full decision transparency |
-| **Debugging** | Single command info | Complete move sequences |
-| **Performance** | Slightly faster | Comparable (same calculations) |
-| **Compatibility** | Direct usage | Wrapper maintains compatibility |
-
-### Usage Patterns
-
-**For AI Decision Making**:
-```cpp
-auto treeFuture = BuildDecisionTree(pid, isDefender, depth, maxRepeat,
-                                   engine, strategy, utility, settings,
-                                   castles, apdCache, alCache, deadline);
-CommandDecisionTree tree = treeFuture.get();
-size_t bestCommand = tree.bestCommand->commandIndex;
-```
-
-**For Analysis and Debugging**:
-```cpp
-CommandDecisionTree tree = treeFuture.get();
-// Examine all possible moves
-for (const auto& rootNode : tree.rootNodes) {
-    std::cout << "Command " << rootNode->commandIndex
-              << " Score: " << rootNode->lookaheadScore << std::endl;
-    // Traverse children to see consequences
-    for (const auto& child : rootNode->children) {
-        // ... analyze child moves
-    }
-}
-```
-
-**Legacy Compatibility**:
-```cpp
-// Existing code continues to work unchanged
-auto indexScoreFuture = BestCommandIndex(pid, isDefender, ...);
-IndexAndScore result = indexScoreFuture.get();
-size_t bestCommand = result.index;
-```
-
-The tree-based approach provides complete decision transparency while maintaining full backward compatibility with existing AI code.
-
-## MCTS Alternative: Randomness Handling Recommendations
-
-The new MCTS-based AI system is available in `MCTSAI.hpp/.cpp` and provides an alternative to the iterative deepening approach. However, the current MCTS implementation uses simplified randomness handling compared to the sophisticated approach in the original system.
-
-### Current MCTS Limitations
-
-1. **Expansion Phase**: Uses average rolls (0.5) for all commands during tree expansion
-2. **Simulation Phase**: Uses random command selection with average rolls
-3. **Missing**: No explicit chance nodes for commands with `HasOdds()`
-4. **Missing**: No multi-sample evaluation for stochastic commands
-
-### Recommended Improvements: Chance Node Integration
-
-#### 1. **Explicit Chance Nodes** (Highest Priority)
-
-For commands with `HasOdds()`, create explicit chance nodes in the MCTS tree:
-
-```cpp
-// During MCTSExpansion
-if (descriptor->HasOdds()) {
-    // Create TWO child nodes: success and failure
-    auto successNode = CreateMCTSNode(commandIndex, SUCCESS_VARIANT);
-    auto failureNode = CreateMCTSNode(commandIndex, FAILURE_VARIANT);
-
-    // Execute with deterministic rolls (matching original system)
-    ExecuteWithRoll(successNode, 1.0 - successChance/2.0);  // High roll
-    ExecuteWithRoll(failureNode, (1.0 - successChance)/2.0); // Low roll
-
-    // Set probability weights for selection
-    successNode->probabilityWeight = successChance;
-    failureNode->probabilityWeight = 1.0 - successChance;
-}
-```
-
-#### 2. **Weighted Selection for Chance Nodes**
-
-Modify `MCTSSelection` to handle chance nodes:
-
-```cpp
-if (node->isChanceNode) {
-    // Select based on probability distribution, not UCB1
-    return SelectByProbability(node->children);
-} else {
-    // Normal UCB1 selection for decision nodes
-    return node->GetBestChild(explorationConstant);
-}
-```
-
-#### 3. **Probability-Weighted Backpropagation**
-
-Update backpropagation to account for chance node probabilities:
-
-```cpp
-void MCTSBackpropagation(MCTSNode* node, double reward) {
-    while (node) {
-        node->visitCount++;
-
-        // Weight reward by probability for chance nodes
-        double weightedReward = reward;
-        if (node->parent && node->parent->isChanceNode) {
-            weightedReward *= node->probabilityWeight;
-        }
-
-        node->totalReward += weightedReward;
-        node->averageReward = node->totalReward / node->visitCount;
-        node = node->parent;
-    }
-}
-```
-
-#### 4. **Multi-Sample Commands**
-
-For commands without explicit odds but with randomness, use stratified sampling:
-
-```cpp
-// During expansion, create multiple child nodes with different rolls
-for (int sample = 0; sample < numSamples; ++sample) {
-    double roll = static_cast<double>(sample) / (numSamples - 1);
-    auto sampleNode = CreateMCTSNodeWithRoll(commandIndex, roll);
-    sampleNode->probabilityWeight = 1.0 / numSamples;
-}
-```
-
-### Benefits of Chance Node Integration
-
-1. **Accurate Evaluation**: Preserves the sophisticated randomness handling from the original system
-2. **Better Convergence**: MCTS can properly explore both success/failure outcomes
-3. **Realistic Simulations**: Tree accurately represents game's probability distributions
-4. **Comparable Results**: Makes MCTS results directly comparable to iterative deepening
-
-### Implementation Priority
-
-1. **Phase 1**: Add explicit chance nodes for `HasOdds()` commands
-2. **Phase 2**: Implement probability-weighted selection and backpropagation
-3. **Phase 3**: Add multi-sample support for general stochastic commands
-4. **Phase 4**: Optimize performance with lazy expansion of chance nodes
-
-### Alternative: Determinization Approach
-
-If explicit chance nodes prove too complex, consider **determinization**:
-
- Run multiple MCTS trees with different fixed random seeds
- Aggregate results across all determinizations
- Simpler to implement but potentially less accurate than explicit chance nodes
-
-### Switching Between AI Systems
-
-Both AI systems (`IterativeDeepeningAI` and `MCTSAI`) implement compatible interfaces. The algorithm is selected at **runtime** via the ShardokAIClient constructor:
-
-```cpp
-// Using Iterative Deepening (default)
-ShardokAIClient client(playerId, isDefender, hexMap, settings);
-// Or explicitly:
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::ITERATIVE_DEEPENING);
-
-// Using MCTS
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::MCTS);
-
-// Note: MCTS configuration can be customized via MCTSConfig:
-// - maxIterations: 10000 (max MCTS iterations per move)
-// - maxSimulationDepth: 10 (depth for rollout phase)
-// - maxTreeDepth: 20 (max tree depth to prevent stack overflow)
-// - explorationConstant: 1.414 (UCB1 exploration vs exploitation)
-// - useMultithreading: true (APD cache is thread-safe with TLS + mutex protection)
-// - numThreads: 4
-```
-
-The selection is made per AI client instance, allowing different algorithms for different players or game situations within the same server process.
-
-#### Direct AI Usage (Lower Level)
-
-Both AI systems can also be used directly:
-
-```cpp
-// Using Iterative Deepening directly
-auto iterativeAI = IterativeDeepeningAI(playerId, isDefender, strategy,
-                                       castleCoords, apdCache, alCache);
-auto result = iterativeAI.IterativeSearch(settings, state, commands, budget);
-
-// Using MCTS directly
-auto mctsAI = MCTSAI(playerId, isDefender, strategy,
-                    castleCoords, apdCache, alCache);
-auto result = mctsAI.Search(settings, state, commands, budget);
-```
-
-#### Algorithm Comparison
-| Feature | Iterative Deepening | MCTS |
-|---------|-------------------|------|
-| **Randomness Handling** | Sophisticated (chance nodes, multi-sample) | Simplified (average rolls) |
-| **Performance** | Single-threaded | Multithreaded |
-| **Search Type** | Fixed depth with iterative deepening | Adaptive with time budget |
-| **Memory Usage** | Lower | Higher (maintains tree) |
-| **Max Tree Depth** | Limited by lookahead setting | Limited by `maxTreeDepth` config (default: 20) |
-| **Tree Destruction** | Not applicable | Iterative (avoids stack overflow) |
-| **Best For** | Precise evaluation, production | Performance testing, fast decisions |
-
-The MCTS implementation provides a solid foundation. Known limitations:
-1. **Randomness Handling**: Simplified compared to iterative deepening (no explicit chance nodes)
-2. **Simulation Quality**: Uses random rollouts instead of sophisticated evaluation
-
-Note: The APD cache is fully thread-safe using thread-local storage and mutex-protected shared cache.
-
-<<<<<<< HEAD
-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.
@@ -11,7 +11,6 @@ cc_library(
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_flee_decision_calculator",
        ":ai_score_utilities",
        ":ai_strategy",
        ":ai_water_crossing_command_chooser",
@@ -71,7 +70,6 @@ cc_library(
        ":ai_score_utilities",
        ":ai_strategy",
        ":ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
@@ -122,39 +120,18 @@ cc_library(
        "//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:shardok_c_types",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
    ],
 )

-cc_library(
-    name = "ai_flee_decision_calculator",
-    srcs = ["AIFleeDecisionCalculator.cpp"],
-    hdrs = ["AIFleeDecisionCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_score_utilities",
-        ":ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-    ],
-)
-
 cc_library(
    name = "ai_command_filter",
    srcs = ["AICommandFilter.cpp"],
    hdrs = ["AICommandFilter.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
@@ -169,37 +146,23 @@ cc_library(
    ],
 )

-cc_library(
-    name = "transposition_table",
-    srcs = ["TranspositionTable.cpp"],
-    hdrs = ["TranspositionTable.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-    ],
-)
-
 cc_library(
    name = "ai_score_calculator",
    srcs = ["AIScoreCalculator.cpp"],
    hdrs = ["AIScoreCalculator.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_filter",
+        ":ai_time_budget",
        ":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/common:thread_pool",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
        "//src/main/cpp/net/eagle0/shardok/library/view_filters:game_state_guesser",
    ],
@@ -211,7 +174,6 @@ cc_library(
    hdrs = ["AIStrategy.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:__subpackages__",
    ],
@@ -250,7 +212,6 @@ cc_library(
        ":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",
@@ -268,7 +229,6 @@ cc_library(
    ],
    deps = [
        ":ai_minimum_distance_and_target",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
        "//src/main/cpp/net/eagle0/shardok/library/fb_helpers:hex_map_helpers",
@@ -286,7 +246,6 @@ cc_library(
    deps = [
        ":ai_minimum_distance_and_target",
        ":ai_water_crossing_calculator",
-        "//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",
@@ -299,7 +258,6 @@ 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__",
    ],
@@ -318,7 +276,6 @@ 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__",
    ],
@@ -335,53 +292,6 @@ cc_library(
    ],
 )

-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__",
-    ],
-)
-
-cc_library(
-    name = "ai_mcts_clean",
-    srcs = ["MCTSCleanAI.cpp"],
-    hdrs = ["MCTSCleanAI.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_attack_locations",
-        ":ai_config",
-        ":ai_iterative_deepening",  # For SearchResult compatibility
-        ":ai_score_calculator",
-        ":ai_strategy",
-        ":ai_time_budget",
-        "//src/main/cpp/net/eagle0/common:random_generator",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//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/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-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__",
-    ],
-)
-
 cc_library(
    name = "shardok_ai_client",
    srcs = ["ShardokAIClient.cpp"],
@@ -390,15 +300,12 @@ 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:mcts_ai",  # Direct dependency for runtime selection
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
        "@com_google_protobuf//:protobuf",
@@ -11,7 +11,7 @@

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

 namespace shardok {
@@ -43,11 +43,6 @@ auto IterativeDeepeningAI::IterativeSearch(
    const auto initialBudgetMs = initialBudget.remainingBudget;
    SearchResult result;

-    // Increment TT age for replacement strategy (new search)
-    g_transpositionTable.incrementAge();
-
-    // DEBUG: Clear TT to see if that's causing the suspicious depth reaching
-    // g_transpositionTable.clear();  // Uncomment to test without cross-search caching
    if (commands.empty()) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
        printf("ID AI: Commands are empty, returning early\n");
@@ -56,12 +51,11 @@ auto IterativeDeepeningAI::IterativeSearch(
        return result;
    }

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

    // Calculate current utility and create engine once for all command evaluations
    const auto& settingsGetter = settings->GetGetter();
@@ -82,10 +76,10 @@ auto IterativeDeepeningAI::IterativeSearch(
    highestDepthCompleted.clear();
    highestDepthCompleted.resize(commands.size(), 0);

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

    // Main iterative deepening loop
    while ((currentDepth == 1 || !IsTimeExpired(timeBudget)) && currentDepth <= maxDepth) {
@@ -95,37 +89,27 @@ auto IterativeDeepeningAI::IterativeSearch(
                scoresByDepth,
                highestDepthCompleted);

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

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

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

-            futures.emplace_back(cmdIndex, std::move(future));
-        }
-
-        // Now wait for all futures and collect results
-        for (auto& [cmdIndex, future] : futures) {
-            auto cmdResult = future.get();
-
            // Ensure scoresByDepth[cmdIndex] has enough space
            if (scoresByDepth[cmdIndex].size() <= currentDepth) {
                scoresByDepth[cmdIndex].resize(currentDepth + 1);
@@ -158,13 +142,13 @@ auto IterativeDeepeningAI::IterativeSearch(
            // Log if best command changed from previous depth
            if (currentDepth > 1 && currentBestCommand != previousBestCommand) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
-                printf("ID AI: Best command changed at depth %lu:\n", currentDepth);
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                printf("ID AI: Best command changed at depth %d:\n", currentDepth);
+                printf("  Depth %d best: command %zu (score %.2f) - %s\n",
                       currentDepth - 1,
                       previousBestCommand,
                       scoresByDepth[previousBestCommand][currentDepth - 1],
                       commands[previousBestCommand].DebugString().c_str());
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                printf("  Depth %d best: command %zu (score %.2f) - %s\n",
                       currentDepth,
                       currentBestCommand,
                       currentBestScore,
@@ -191,12 +175,12 @@ auto IterativeDeepeningAI::IterativeSearch(
        // This indicates we've hit END_TURN in the lookahead
        if (currentDepth > 1 && evaluatedCount > 0) {
            bool scoresUnchanged = true;
-            size_t unchangedCount = 0;
+            int unchangedCount = 0;

            for (size_t i = 0; i < sortedIndices.size() && i < evaluatedCount; ++i) {
+                size_t cmdIndex = sortedIndices[i];
                // This command was evaluated at both current and previous depth
-                if (size_t cmdIndex = sortedIndices[i];
-                    scoresByDepth[cmdIndex].size() > currentDepth &&
+                if (scoresByDepth[cmdIndex].size() > currentDepth &&
                    scoresByDepth[cmdIndex].size() > currentDepth - 1) {
                    // Check if score changed between depth N-1 and depth N
                    if (std::abs(
@@ -220,11 +204,10 @@ auto IterativeDeepeningAI::IterativeSearch(
        // Check if we've used more than 50% of total budget
        auto totalElapsed = std::chrono::steady_clock::now() - startTime;
        auto totalElapsedMs = std::chrono::duration_cast<std::chrono::milliseconds>(totalElapsed);
-        double budgetUsedPercent = static_cast<double>(totalElapsedMs.count()) /
-                                   static_cast<double>(initialBudgetMs.count());
+        double budgetUsedPercent = (double)totalElapsedMs.count() / initialBudgetMs.count();

        if (budgetUsedPercent > 0.5) {
-            printf("ID AI: Stopping after depth %lu - used %.1f%% of time budget\n",
+            printf("ID AI: Stopping after depth %d - used %.1f%% of time budget\n",
                   currentDepth,
                   budgetUsedPercent * 100);
            completionReason = EvaluationCompletionReason::NOT_ENOUGH_TIME_TO_CONTINUE;
@@ -259,8 +242,6 @@ auto IterativeDeepeningAI::IterativeSearch(
               result.availableCommandCount);
    }

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

@@ -274,12 +255,12 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
        const int maxRepeatCount,
        const std::vector<CommandProto>& commands,
        const size_t commandIndex,
-        const int desiredDepth,
+        const int depth,
        const ScoreValue currentUtility,
-        AITimeBudget& timeBudget) const -> std::future<SearchResult> {
+        AITimeBudget& timeBudget) const -> SearchResult {
    SearchResult result;
    result.bestCommandIndex = commandIndex;
-    result.depthAchieved = desiredDepth;
+    result.depthAchieved = depth;
    result.searchCompleted = true;
    result.minimumDepthCompleted = true;
    result.availableCommandCount = commands.size();
@@ -287,9 +268,7 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(

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

    try {
@@ -297,18 +276,11 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
        AIEvaluationCounter counter;
        const auto startTime = std::chrono::steady_clock::now();

-        // Calculate deadline from remaining time budget
-        const auto deadline = startTime + timeBudget.remainingBudget;
-
-        // 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(
+        // Use CommandScore to evaluate the specific command at the given depth
+        const auto commandScore = AIScoreCalculator::CommandScore(
                playerId,
                isDefender,
-                desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
+                depth,
                maxRepeatCount,
                guessedEngine,
                strategy,
@@ -317,15 +289,11 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
                castleCoords,
                apdCache,
                alCache,
-                commandIndex,
-                deadline);
-
-        // Calculate time and adjust budget before waiting
-        // This is needed because we need to update timeBudget synchronously
-        const auto commandScore = commandScoreFuture.get();
+                commandIndex);

+        // Calculate time used and adjust based on concurrent evaluations
        const auto elapsed = std::chrono::steady_clock::now() - startTime;
-        const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
+        const int concurrentCount = counter.GetCurrentCount();
        const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
        const auto adjustedElapsedMs =
                std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);
@@ -342,15 +310,13 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
        result.bestScore = 0.0;
    }

-    std::promise<SearchResult> p;
-    p.set_value(result);
-    return p.get_future();
+    return result;
 }

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

@@ -360,21 +326,11 @@ auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(
    }

    // Sort by score at previous depth
-    const size_t prevDepth = currentDepth - 1;
-    std::ranges::sort(indices, [&](const size_t a, const size_t b) {
-        // Bounds check - if indices are out of range, or inner vectors are too small, treat as not
-        // evaluated
-        if (a >= scoresByDepth.size() || b >= scoresByDepth.size() ||
-            a >= highestDepthCompleted.size() || b >= highestDepthCompleted.size()) {
-            return a < b;  // Maintain stable order for out-of-bounds indices
-        }
-
-        // Check if the scores for previous depth exist
+    int prevDepth = currentDepth - 1;
+    std::sort(indices.begin(), indices.end(), [&](size_t a, size_t b) {
+        // Only consider commands that were evaluated at previous depth
        if (highestDepthCompleted[a] >= prevDepth && highestDepthCompleted[b] >= prevDepth) {
-            // Additional safety check for inner vector size
-            if (scoresByDepth[a].size() > prevDepth && scoresByDepth[b].size() > prevDepth) {
-                return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
-            }
+            return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
        }
        // Commands not evaluated at prev depth go to the end
        return highestDepthCompleted[a] >= prevDepth;
@@ -385,7 +341,7 @@ auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(

 auto IterativeDeepeningAI::SelectBestResult(
        const std::vector<std::vector<ScoreValue>>& scoresByDepth,
-        const std::vector<size_t>& highestDepthCompleted) -> SearchResult {
+        const std::vector<int>& highestDepthCompleted) const -> SearchResult {
    SearchResult result;
    result.bestScore = -std::numeric_limits<ScoreValue>::infinity();
    result.searchCompleted = false;
@@ -393,8 +349,9 @@ auto IterativeDeepeningAI::SelectBestResult(
    // Find the command with best score at its highest evaluated depth
    for (size_t i = 0; i < scoresByDepth.size(); ++i) {
        if (highestDepthCompleted[i] > 0) {
-            const size_t depth = highestDepthCompleted[i];
-            if (ScoreValue score = scoresByDepth[i][depth]; score > result.bestScore) {
+            int depth = highestDepthCompleted[i];
+            ScoreValue score = scoresByDepth[i][depth];
+            if (score > result.bestScore) {
                result.bestScore = score;
                result.bestCommandIndex = i;
                result.depthAchieved = depth;
@@ -6,7 +6,6 @@
 #define EAGLE0_ITERATIVEDEEPENINGAI_HPP

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

 #include "AIStrategy.hpp"
@@ -36,7 +35,7 @@ public:
    struct SearchResult {
        size_t bestCommandIndex;
        ScoreValue bestScore;
-        size_t depthAchieved;
+        int depthAchieved;
        std::chrono::milliseconds timeUsed;
        bool minimumDepthCompleted;
        bool searchCompleted;
@@ -68,7 +67,7 @@ public:
            const GameSettingsSPtr& settings,
            const GameStateW& state,
            const std::vector<CommandProto>& commands,
-            const AITimeBudget& initialBudget) const;
+            const AITimeBudget& timeBudget) const;

 private:
    PlayerId playerId;
@@ -80,29 +79,29 @@ private:

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

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

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

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

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

 }  // namespace shardok
@@ -1,105 +0,0 @@
-//
-// MCTS-based AI system for Shardok
-// Alternative to IterativeDeepeningAI using Monte Carlo Tree Search
-//
-
-#ifndef EAGLE0_MCTSAI_HPP
-#define EAGLE0_MCTSAI_HPP
-
-#include <chrono>
-#include <future>
-#include <memory>
-#include <vector>
-
-#include "AIStrategy.hpp"
-#include "AITimeBudget.hpp"
-#include "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"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-struct MCTSNode;
-
-// Configuration for MCTS algorithm
-struct MCTSConfig {
-    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
-    int maxPlayerFlips = 1;              // Number of player turn changes to evaluate
-    bool useMultithreading = true;       // Enable parallel MCTS
-    int numThreads = 16;                 // Number of threads for parallel MCTS (when enabled)
-};
-
-class MCTSAI {
-public:
-    using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-    using SearchResult = IterativeDeepeningAI::SearchResult;
-
-    MCTSAI(PlayerId playerId,
-           bool isDefender,
-           AIStrategy strategy,
-           const CoordsSet& castleCoords,
-           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 std::vector<CommandProto>& commands,
-            const AITimeBudget& budget) const -> SearchResult;
-
-    // Get/set configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return config; }
-    void SetConfig(const MCTSConfig& newConfig) { config = newConfig; }
-
-private:
-    PlayerId playerId;
-    bool isDefender;
-    AIStrategy strategy;
-    const CoordsSet& castleCoords;
-    const APDCache& apdCache;
-    const ALCache& alCache;
-    MCTSConfig config;
-
-    // Internal MCTS tree building
-    [[nodiscard]] auto BuildMCTSTree(
-            const ShardokEngine& engine,
-            const SettingsGetter& settingsGetter,
-            std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode>;
-
-    // MCTS algorithm phases
-    auto MCTSSelection(MCTSNode* root) const -> MCTSNode*;
-    auto MCTSExpansion(
-            MCTSNode* node,
-            const ShardokEngine& engine,
-            const SettingsGetter& settingsGetter) const -> MCTSNode*;
-    auto MCTSSimulation(
-            const ShardokEngine& engineState,
-            PlayerId currentPlayer,
-            const SettingsGetter& settingsGetter) const -> double;
-    auto MCTSBackpropagation(MCTSNode* node, double reward) const -> void;
-
-    // Helper functions
-    [[nodiscard]] auto IsTerminalForPlayer(
-            const GameStateW& gameState,
-            PlayerId currentPlayer,
-            const SettingsGetter& settingsGetter) const -> bool;
-
-    // Get coordinate information for logging
-    [[nodiscard]] std::string GetCommandCoordinateInfo(
-            net::eagle0::shardok::common::CommandType commandType,
-            size_t commandIndex,
-            const GameStateW& gameState,
-            const GameSettingsSPtr& settings) const;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTSAI_HPP
@@ -1,292 +0,0 @@
-#include "MCTSCleanAI.hpp"
-
-#include <algorithm>
-#include <chrono>
-#include <cmath>
-#include <limits>
-
-#include "AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-MCTSCleanAI::MCTSCleanAI(
-        PlayerId playerId,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache)
-    : ourPlayerId(playerId),
-      isDefender(isDefender),
-      strategy(strategy),
-      castleCoords(castleCoords),
-      apdCache(apdCache),
-      alCache(alCache),
-      rng(std::chrono::steady_clock::now().time_since_epoch().count()) {}
-
-IterativeDeepeningAI::SearchResult MCTSCleanAI::Search(
-        const GameSettingsSPtr& settings,
-        const GameStateW& gameState,
-        const std::vector<CommandProto>& availableCommands,
-        const AITimeBudget& timeBudget) {
-    const auto startTime = std::chrono::steady_clock::now();
-    const auto maxTime = std::chrono::duration_cast<std::chrono::milliseconds>(
-            timeBudget.remainingBudget * 0.9);  // 90% of budget
-
-    // Create root node
-    auto root = std::make_unique<MCTSNode>();
-    root->resultingGameState = gameState;
-    root->currentPlayer = ourPlayerId;
-    root->isOurTurn = true;
-    root->playerFlipsFromRoot = 0;
-
-    // Initialize untried commands for root
-    for (size_t i = 0; i < availableCommands.size(); ++i) { root->untriedCommands.push_back(i); }
-
-    int iterationCount = 0;
-
-    // Main MCTS loop
-    while (std::chrono::steady_clock::now() - startTime < maxTime) {
-        // 1. Selection - find leaf node to expand
-        MCTSNode* selected = Selection(root.get());
-
-        // 2. Expansion - add new child if possible
-        MCTSNode* expanded = Expansion(selected, settings, availableCommands);
-
-        // 3. Simulation - run random playout
-        double reward = Simulation(
-                expanded->resultingGameState,
-                expanded->currentPlayer,
-                expanded->playerFlipsFromRoot,
-                settings);
-
-        // 4. Backpropagation - update statistics
-        Backpropagation(expanded, reward);
-
-        iterationCount++;
-
-        // Early exit if all commands tried
-        if (root->untriedCommands.empty() && root->children.size() == availableCommands.size()) {
-            bool allChildrenFullyExplored = true;
-            for (const auto& child : root->children) {
-                if (child->visitCount < 10) {  // Minimum visits per child
-                    allChildrenFullyExplored = false;
-                    break;
-                }
-            }
-            if (allChildrenFullyExplored) { break; }
-        }
-    }
-
-    // Select best command based on visit counts
-    size_t bestCommandIndex = 0;
-    int maxVisits = 0;
-
-    for (size_t i = 0; i < root->children.size(); ++i) {
-        if (root->children[i]->visitCount > maxVisits) {
-            maxVisits = root->children[i]->visitCount;
-            bestCommandIndex = root->children[i]->commandIndex;
-        }
-    }
-
-    // Create search result
-    IterativeDeepeningAI::SearchResult result;
-    result.bestCommandIndex = bestCommandIndex;
-    result.availableCommandCount = availableCommands.size();
-    result.depthAchieved = maxPlayerFlips;  // Our max search depth
-    result.commandCountEvaluated = iterationCount;
-    result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
-
-    printf("MCTS Clean: %d iterations, best command %zu with %d visits\n",
-           iterationCount,
-           bestCommandIndex,
-           maxVisits);
-
-    return result;
-}
-
-// Selection - navigate to leaf using UCB1
-MCTSCleanAI::MCTSNode* MCTSCleanAI::Selection(MCTSNode* root) {
-    MCTSNode* current = root;
-
-    while (!current->children.empty() && current->untriedCommands.empty()) {
-        current = SelectChild(current);
-    }
-
-    return current;
-}
-
-// Expansion - add new child node
-MCTSCleanAI::MCTSNode* MCTSCleanAI::Expansion(
-        MCTSNode* node,
-        const GameSettingsSPtr& settings,
-        const std::vector<CommandProto>& availableCommands) {
-    // If we've reached max player flips, don't expand
-    if (node->playerFlipsFromRoot >= maxPlayerFlips) { return node; }
-
-    // If no untried commands, return current node
-    if (node->untriedCommands.empty()) { return node; }
-
-    // Pick an untried command
-    size_t cmdIndex = PickUntriedCommand(node);
-
-    // Create child engine and execute command
-    auto childEngine = CreateEngine(node->resultingGameState, settings);
-    PlayerId playerBefore = childEngine->GetCurrentPlayerId();
-
-    // Use sequence random generator for deterministic results
-    auto averageGenerator = std::make_shared<SequenceRandomGenerator>(std::vector<double>{0.5});
-    childEngine->PostCommand(playerBefore, cmdIndex, averageGenerator);
-
-    PlayerId playerAfter = childEngine->GetCurrentPlayerId();
-
-    // Create child node
-    bool isOurTurnAfter = (playerAfter == ourPlayerId);
-    auto child = std::make_unique<MCTSNode>(
-            cmdIndex,
-            availableCommands[cmdIndex].type(),
-            playerAfter,
-            isOurTurnAfter);
-    child->resultingGameState = childEngine->GetCurrentGameState();
-    child->parent = node;
-
-    // Track player flips
-    child->playerFlipsFromRoot = node->playerFlipsFromRoot;
-    if (playerBefore != playerAfter) { child->playerFlipsFromRoot++; }
-
-    // Initialize child's untried commands if we haven't hit max flips
-    if (child->playerFlipsFromRoot < maxPlayerFlips) {
-        auto childCommands = childEngine->GetAvailableCommandsForAIPlayer(playerAfter);
-        for (size_t i = 0; i < childCommands->size(); ++i) { child->untriedCommands.push_back(i); }
-    }
-
-    MCTSNode* childPtr = child.get();
-    node->children.push_back(std::move(child));
-
-    return childPtr;
-}
-
-// Simulation - run random playout from current state
-double MCTSCleanAI::Simulation(
-        const GameStateW& startState,
-        PlayerId /* startPlayer */,
-        int startFlips,
-        const GameSettingsSPtr& settings) {
-    auto simEngine = CreateEngine(startState, settings);
-    int currentFlips = startFlips;
-    auto averageGenerator = std::make_shared<SequenceRandomGenerator>(std::vector<double>{0.5});
-
-    while (currentFlips < maxPlayerFlips) {
-        PlayerId currentPlayer = simEngine->GetCurrentPlayerId();
-        bool isOurTurn = (currentPlayer == ourPlayerId);
-
-        // Get available commands
-        auto commands = simEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        if (commands->empty()) break;
-
-        // Pick best command based on whose turn it is
-        size_t bestCmd = 0;
-        double bestScore = isOurTurn ? -std::numeric_limits<double>::infinity()
-                                     : std::numeric_limits<double>::infinity();
-
-        for (size_t i = 0; i < commands->size(); ++i) {
-            auto testEngine = CreateEngine(simEngine->GetCurrentGameState(), settings);
-            testEngine->PostCommand(currentPlayer, i, averageGenerator);
-
-            // Always score from our perspective
-            double score = ScoreFromOurPerspective(
-                    testEngine->GetCurrentGameState(),
-                    settings->GetGetter());
-
-            // Our turn: maximize our score, Opponent turn: minimize our score
-            bool shouldSelect = isOurTurn ? (score > bestScore) : (score < bestScore);
-            if (shouldSelect) {
-                bestScore = score;
-                bestCmd = i;
-            }
-        }
-
-        // Execute chosen command
-        PlayerId playerBefore = simEngine->GetCurrentPlayerId();
-        simEngine->PostCommand(currentPlayer, bestCmd, averageGenerator);
-        PlayerId playerAfter = simEngine->GetCurrentPlayerId();
-
-        // Track player flips
-        if (playerBefore != playerAfter) { currentFlips++; }
-    }
-
-    return ScoreFromOurPerspective(simEngine->GetCurrentGameState(), settings->GetGetter());
-}
-
-// Backpropagation - update node statistics
-void MCTSCleanAI::Backpropagation(MCTSNode* node, double score) {
-    while (node != nullptr) {
-        node->visitCount++;
-        node->totalScore += score;  // Always from our perspective
-        node->averageScore = node->totalScore / node->visitCount;
-        node = node->parent;
-    }
-}
-
-// Helper functions
-double MCTSCleanAI::ScoreFromOurPerspective(
-        const GameStateW& gameState,
-        const SettingsGetter& settingsGetter) {
-    return AIScoreCalculator::GuessedStateScore(
-            isDefender,
-            gameState,
-            strategy,
-            castleCoords,
-            settingsGetter,
-            apdCache,
-            alCache);
-}
-
-MCTSCleanAI::MCTSNode* MCTSCleanAI::SelectChild(MCTSNode* node) {
-    MCTSNode* bestChild = nullptr;
-    double bestUCB1 = node->isOurTurn ? -std::numeric_limits<double>::infinity()
-                                      : std::numeric_limits<double>::infinity();
-
-    for (const auto& child : node->children) {
-        double exploitation = child->averageScore;
-        double exploration =
-                explorationConstant * std::sqrt(std::log(node->visitCount) / child->visitCount);
-        double ucb1 = exploitation + exploration;
-
-        // Our turn: pick highest UCB1, Opponent turn: pick lowest UCB1
-        bool shouldSelect = node->isOurTurn ? (ucb1 > bestUCB1) : (ucb1 < bestUCB1);
-
-        if (shouldSelect) {
-            bestUCB1 = ucb1;
-            bestChild = child.get();
-        }
-    }
-
-    return bestChild;
-}
-
-size_t MCTSCleanAI::PickUntriedCommand(MCTSNode* node) {
-    if (node->untriedCommands.empty()) {
-        return 0;  // Should not happen
-    }
-
-    // Pick random untried command
-    std::uniform_int_distribution<size_t> indexDist(0, node->untriedCommands.size() - 1);
-    size_t randomIndex = indexDist(rng);
-
-    size_t cmdIndex = node->untriedCommands[randomIndex];
-    node->untriedCommands.erase(node->untriedCommands.begin() + randomIndex);
-
-    return cmdIndex;
-}
-
-std::shared_ptr<ShardokEngine> MCTSCleanAI::CreateEngine(
-        const GameStateW& gameState,
-        const GameSettingsSPtr& settings) {
-    return std::make_shared<ShardokEngine>(settings, gameState);
-}
-
-}  // namespace shardok
@@ -1,133 +0,0 @@
-#pragma once
-
-#include <memory>
-#include <random>
-#include <vector>
-
-#include "AIAttackLocations.hpp"
-#include "AIConfig.hpp"
-#include "AIStrategy.hpp"
-#include "AITimeBudget.hpp"
-#include "IterativeDeepeningAI.hpp"  // For SearchResult
-#include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-// Forward declare cache type aliases
-using APDCache = std::shared_ptr<ActionPointDistancesCache>;
-using ALCache = std::unique_ptr<AttackLocationsCache>;
-
-}  // namespace shardok
-
-namespace shardok {
-
-// Clean MCTS implementation following the design document
-class MCTSCleanAI {
-public:
-    // Clean node structure with single perspective scoring
-    struct MCTSNode {
-        // Command that led to this state
-        size_t commandIndex;
-        net::eagle0::shardok::common::CommandType commandType;
-
-        // Game state after executing the command
-        GameStateW resultingGameState;
-        PlayerId currentPlayer;  // Whose turn it is in this state
-
-        // Tree position
-        int playerFlipsFromRoot;  // Number of player changes from root
-        bool isOurTurn;           // currentPlayer == our AI's playerId
-
-        // MCTS statistics (always from our perspective)
-        int visitCount = 0;
-        double totalScore = 0.0;
-        double averageScore = 0.0;
-
-        // Tree structure
-        std::vector<std::unique_ptr<MCTSNode>> children;
-        std::vector<size_t> untriedCommands;
-        MCTSNode* parent = nullptr;
-
-        // Constructor
-        MCTSNode(
-                size_t cmdIndex,
-                net::eagle0::shardok::common::CommandType cmdType,
-                PlayerId currentPlayerId,
-                bool ourTurn)
-            : commandIndex(cmdIndex),
-              commandType(cmdType),
-              currentPlayer(currentPlayerId),
-              playerFlipsFromRoot(0),
-              isOurTurn(ourTurn) {}
-
-        // Root constructor
-        MCTSNode()
-            : commandIndex(0),
-              commandType(net::eagle0::shardok::common::UNKNOWN_COMMAND),
-              currentPlayer(0),
-              playerFlipsFromRoot(0),
-              isOurTurn(true) {}
-    };
-
-    MCTSCleanAI(
-            PlayerId playerId,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const APDCache& apdCache,
-            const ALCache& alCache);
-
-    // Main search function compatible with existing interface
-    IterativeDeepeningAI::SearchResult Search(
-            const GameSettingsSPtr& settings,
-            const GameStateW& gameState,
-            const std::vector<CommandProto>& availableCommands,
-            const AITimeBudget& timeBudget);
-
-private:
-    PlayerId ourPlayerId;
-    bool isDefender;
-    AIStrategy strategy;
-    CoordsSet castleCoords;
-    const APDCache& apdCache;
-    const ALCache& alCache;
-
-    // MCTS parameters
-    static constexpr int maxPlayerFlips = 5;              // Stop after N player changes
-    static constexpr double explorationConstant = 1.414;  // sqrt(2)
-
-    // Random number generation
-    std::mt19937 rng;
-    std::uniform_real_distribution<double> uniformDist{0.0, 1.0};
-
-    // Core MCTS algorithms
-    MCTSNode* Selection(MCTSNode* root);
-    MCTSNode* Expansion(
-            MCTSNode* node,
-            const GameSettingsSPtr& settings,
-            const std::vector<CommandProto>& availableCommands);
-    double Simulation(
-            const GameStateW& startState,
-            PlayerId startPlayer,
-            int startFlips,
-            const GameSettingsSPtr& settings);
-    void Backpropagation(MCTSNode* node, double score);
-
-    // Helper functions
-    double ScoreFromOurPerspective(
-            const GameStateW& gameState,
-            const SettingsGetter& settingsGetter);
-    MCTSNode* SelectChild(MCTSNode* node);
-    size_t PickUntriedCommand(MCTSNode* node);
-    std::shared_ptr<ShardokEngine> CreateEngine(
-            const GameStateW& gameState,
-            const GameSettingsSPtr& settings);
-};
-
-}  // namespace shardok
@@ -1,147 +0,0 @@
-# MCTS Player-Flip Depth System Design
-
-## Overview
-Replace command-count-based depth limits with player-turn-aware depth that naturally aligns with game structure. All nodes evaluate to the same player-flip depth to ensure comparable scores.
-
-## Core Concepts
-
-### Player-Flip Depth
- **Depth 1**: Evaluate until first player flip (complete our turn)
- **Depth 2**: Continue through opponent's full turn
- **Depth 3**: Continue through our next full turn
- **Depth N**: N complete player turn changes
-
-### Minimax Selection
- **Always evaluate from original AI's perspective**
- **Our turn**: Select moves that maximize our score
- **Opponent's turn**: Select moves that minimize our score
- Same backpropagation value regardless of whose turn
-
-## Implementation Plan
-
-### 1. Configuration Changes
-
-```cpp
-struct MCTSConfig {
-    double explorationConstant = 1.414;
-    int maxPlayerFlips = 2;        // How many player changes to evaluate
-    bool useMultithreading = true;
-    int numThreads = 16;
-    // REMOVED: maxTreeDepth - all nodes go to same player-flip depth
-    // REMOVED: maxSimulationDepth - replaced by maxPlayerFlips
-};
-```
-
-### 2. Node Structure Updates
-
-```cpp
-struct MCTSNode {
-    // Existing fields...
-
-    // New fields for player-flip tracking
-    int playerFlipsFromRoot = 0;
-    bool isMaximizingPlayer = true;  // true = our turn, false = opponent's
-
-    // Modified selection for minimax
-    MCTSNode* GetBestChild(double explorationConstant) {
-        if (isMaximizingPlayer) {
-            return GetChildWithHighestUCB1(explorationConstant);
-        } else {
-            return GetChildWithLowestUCB1(explorationConstant);
-        }
-    }
-};
-```
-
-### 3. Expansion Rules
-
- **Continue expanding** until reaching `maxPlayerFlips` player changes
- **No arbitrary depth limit** - accept theoretical stack overflow risk
- **Mark as terminal** only when:
-  - Game is over
-  - Reached `maxPlayerFlips` player changes
-  - No available commands
-
-### 4. Key Implementation Details
-
-#### Terminal Detection
-```cpp
-bool IsTerminalForExpansion() {
-    return playerFlipsFromRoot >= maxPlayerFlips ||
-           gameIsOver ||
-           noCommandsAvailable;
-}
-```
-
-#### Player Tracking
-```cpp
-// When expanding END_TURN or END_PLAYER_SETUP
-child->playerFlipsFromRoot = parent->playerFlipsFromRoot + 1;
-child->isMaximizingPlayer = !parent->isMaximizingPlayer;
-```
-
-#### UCB1 for Minimax
- Maximizing player: Choose highest UCB1
- Minimizing player: Choose lowest UCB1
- Unvisited nodes: Extreme values to force exploration
-
-### 5. Simulation Strategy
-
-Simulations run until `maxPlayerFlips` is reached:
- Random moves for both players
- Stop at player-flip boundaries
- Always evaluate from original AI perspective
-
-## Benefits
-
-### Consistent Evaluation
- All leaf nodes at same player-flip depth
- Scores are directly comparable
- No apples-to-oranges comparison issues
-
-### Natural Game Structure
- Respects turn boundaries
- Complete tactical sequences evaluated
- Opponent responses properly modeled
-
-### Strategic Depth Control
- **Setup/Early**: `maxPlayerFlips = 1` (fast, local tactics)
- **Mid-game**: `maxPlayerFlips = 2` (balanced)
- **Critical**: `maxPlayerFlips = 3+` (deep strategy)
-
-## Implementation Order
-
-1. **Phase 1**: Update MCTSConfig
-   - Remove `maxTreeDepth` and `maxSimulationDepth`
-   - Add `maxPlayerFlips`
-
-2. **Phase 2**: Modify MCTSNode
-   - Add `playerFlipsFromRoot` and `isMaximizingPlayer`
-   - Update child selection for minimax
-
-3. **Phase 3**: Update Expansion
-   - Track player flips
-   - Remove depth-based termination
-   - Only terminate at player-flip boundaries
-
-4. **Phase 4**: Fix Selection
-   - Implement minimax selection based on `isMaximizingPlayer`
-   - Modify UCB1 interpretation
-
-5. **Phase 5**: Update Simulation
-   - Run until `maxPlayerFlips` reached
-   - Handle both player perspectives
-
-## Testing Strategy
-
-1. Verify all evaluations reach same player-flip depth
-2. Confirm opponent chooses minimizing moves
-3. Test with different `maxPlayerFlips` settings
-4. Validate score consistency across tree
-
-## Notes
-
- Stack overflow risk accepted for evaluation consistency
- Each unit can make multiple moves per turn (move + scout + attack)
- Maximum ~10 units per player limits practical depth
- END_TURN and END_PLAYER_SETUP both count as player flips
@@ -8,18 +8,12 @@

 #include "ShardokAIClient.hpp"

-#define DEBUG_FLEE_DECISIONS
-
 #include <google/protobuf/util/message_differencer.h>

 #include "AIAttackerStrategySelector.hpp"
-#include "AIConfig.hpp"  // Must come before other AI includes
 #include "AIDefenderStrategySelector.hpp"
-#include "AIFleeDecisionCalculator.hpp"
-#include "AIScoreUtilities.hpp"
 #include "AITimeBudget.hpp"
 #include "IterativeDeepeningAI.hpp"
-#include "mcts/MCTSAI.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"
@@ -32,7 +26,7 @@ using net::eagle0::shardok::api::GameStateView;

 static constexpr bool kPerformanceLogging = true;

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

 auto RoundsRemaining(const GameSettingsSPtr &settings, const GameStateView &gsv) -> int {
    const int maxRounds = settings->GetGetter().Backing().max_rounds();
@@ -44,11 +38,9 @@ ShardokAIClient::ShardokAIClient(
        const PlayerId playerId,
        const bool isDefender,
        const HexMap *hexMap,
-        const SettingsGetter &settings,
-        const AIAlgorithmType aiAlgorithmType)
+        const SettingsGetter &settings)
    : playerId(playerId),
      isDefender(isDefender),
-      aiAlgorithmType(aiAlgorithmType),
      alCache(std::make_unique<AttackLocationsCache>(hexMap, settings)),
      waterCrossingCommandChooser(playerId, apdCache) {
    // Pre-generate the most common cache entries for better performance
@@ -104,7 +96,7 @@ auto ShardokAIClient::StandardChooseCommandIndex(
    const auto commandCount = guessedCommands.size();

    assert(commandCount == realAvailableCommands.size());
-    for (size_t i = 0; i < commandCount; i++) {
+    for (int i = 0; i < commandCount; i++) {
        CheckCommand(realAvailableCommands[i], guessedCommands[i]);
    }

@@ -125,19 +117,11 @@ auto ShardokAIClient::StandardChooseCommandIndex(
                                                     waterCrossingCommandChooser,
                                                     realAvailableCommands);

-    // AI implementation chosen at runtime via constructor parameter
-    IterativeDeepeningAI::SearchResult search_result;
-
-    if (aiAlgorithmType == AIAlgorithmType::MCTS) {
-        // Using Monte Carlo Tree Search AI
-        MCTSAI ai(playerId, isDefender, strategy, castleCoords, apdCache, alCache);
-        search_result = ai.Search(settings, guessedState, realAvailableCommands, timeBudget);
-    } else {
-        // Using Iterative Deepening AI (default)
-        IterativeDeepeningAI ai(playerId, isDefender, strategy, castleCoords, apdCache, alCache);
-        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;
@@ -191,41 +175,23 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
        const GameSettingsSPtr &settings,
        const GameStateW &guessedState,
        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 (const auto fleeCommand = std::ranges::find_if(
+                realAvailableCommands,
+                [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
+                    return cmd.type() == net::eagle0::shardok::common::FLEE_COMMAND;
+                });
+        fleeCommand == realAvailableCommands.end()) {
        return LateRoundAttackerChooseCommandIndex(settings, guessedState, realAvailableCommands);
-    }
-
-    // Use the flee decision calculator
-    const auto fleeDecision = AIFleeDecisionCalculator::EvaluateFleeVsFight(
-            playerId,
-            settings->GetGetter(),
-            guessedState,
-            realAvailableCommands,
-            fleeCommand,
-#ifdef DEBUG_FLEE_DECISIONS
-            true  // Enable debug logging
-#else
-            false
-#endif
-    );
-
-    if (fleeDecision.shouldFlee) {
-        CommandChoiceResults results{};
-        results.chosenIndex = fleeDecision.commandIndex;
-        results.availableCommandCount = realAvailableCommands.size();
-        results.depthAchieved = 1;          // Heuristic choice
-        results.commandCountEvaluated = 1;  // Only evaluated one command type
-        results.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-        return results;
    } else {
-        // Fight instead of flee
-        return StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
+        CommandChoiceResults results{};
+        results.chosenIndex =
+                static_cast<size_t>(std::distance(realAvailableCommands.begin(), fleeCommand));
+        results.availableCommandCount = realAvailableCommands.size();
+        results.depthAchieved = 1;          // Simple heuristic choice
+        results.commandCountEvaluated = 1;  // Only evaluated one command type
+        results.completionReason =
+                EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;  // Heuristic choice
+        return results;
    }
 }

@@ -12,7 +12,6 @@
 #include <vector>

 #include "src/main/cpp/net/eagle0/common/RandomGenerator.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"
@@ -39,7 +38,6 @@ class ShardokAIClient {
 private:
    const PlayerId playerId;
    const bool isDefender;
-    const AIAlgorithmType aiAlgorithmType;

    APDCache apdCache = std::make_shared<ActionPointDistancesCache>();
    ALCache alCache;
@@ -58,7 +56,6 @@ private:
            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
-
    [[nodiscard]] auto ChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const net::eagle0::shardok::api::GameStateView& gsv,
@@ -69,8 +66,7 @@ public:
            PlayerId playerId,
            bool isDefender,
            const HexMap* hexMap,
-            const SettingsGetter& settings,
-            AIAlgorithmType aiAlgorithmType = AIAlgorithmType::ITERATIVE_DEEPENING);
+            const SettingsGetter& settings);
    ~ShardokAIClient() = default;

    [[nodiscard]] auto GetPlayerId() const -> PlayerId { return playerId; }
@@ -1,113 +0,0 @@
-//
-// TranspositionTable.cpp - Implementation of game state evaluation cache
-//
-
-#include "TranspositionTable.hpp"
-
-#include <cstdio>
-#include <cstring>
-
-namespace shardok {
-
-// Global instance
-TranspositionTable g_transpositionTable;
-
-TranspositionTable::TranspositionTable() : table(TABLE_SIZE) {
-    // Initialize all entries to zero
-    clear();
-}
-
-uint64_t TranspositionTable::hashGameState(const GameStateW& state) const {
-    // The FlatBuffer is contiguous in memory and units are sorted by ID,
-    // so we can just hash the raw bytes for order-independent hashing
-    // Use ComputeFNV1aHash to avoid creating a string copy
-    return state.ComputeFNV1aHash();
-}
-
-std::optional<ScoreValue>
-TranspositionTable::probe(const GameStateW& state, int depth, PlayerId player) {
-    stats.probes++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    const auto& entry = table[index];
-
-    // Check if this entry matches our position using FULL hash
-    uint64_t stored_hash = entry.hash_full.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-    uint8_t stored_player = entry.player_id.load(std::memory_order_relaxed);
-
-    if (stored_hash == hash && stored_depth >= depth && stored_player == player) {
-        stats.hits++;
-        float score = entry.score.load(std::memory_order_relaxed);
-        return static_cast<ScoreValue>(score);
-    }
-
-    // Track collisions (different position mapped to same index)
-    // Note: We use depth==0 to indicate empty entries, not hash==0
-    if (stored_depth != 0 && stored_hash != hash) { stats.collisions++; }
-
-    return std::nullopt;
-}
-
-void TranspositionTable::store(
-        const GameStateW& state,
-        int depth,
-        PlayerId player,
-        ScoreValue score) {
-    stats.stores++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    auto& entry = table[index];
-
-    // Simple replacement strategy: always replace if:
-    // 1. Entry is from an older search (different age)
-    // 2. New search is deeper
-    // 3. Entry is empty (depth == 0)
-
-    uint16_t stored_age = entry.age.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-
-    bool should_replace = (stored_depth == 0) ||          // Empty entry (depth 0 means unused)
-                          (stored_age != current_age) ||  // Old entry
-                          (depth >= stored_depth);        // Deeper or equal search
-
-    if (should_replace) {
-        // Store all fields with relaxed ordering (TT races are benign)
-        entry.hash_full.store(hash, std::memory_order_relaxed);
-        entry.score.store(static_cast<float>(score), std::memory_order_relaxed);
-        entry.depth.store(static_cast<uint8_t>(depth), std::memory_order_relaxed);
-        entry.player_id.store(static_cast<uint8_t>(player), std::memory_order_relaxed);
-        entry.age.store(current_age, std::memory_order_relaxed);
-    }
-}
-
-void TranspositionTable::clear() {
-    // Reset all entries
-    for (auto& entry : table) {
-        entry.hash_full.store(0, std::memory_order_relaxed);
-        entry.score.store(0.0f, std::memory_order_relaxed);
-        entry.depth.store(0, std::memory_order_relaxed);
-        entry.player_id.store(0, std::memory_order_relaxed);
-        entry.age.store(0, std::memory_order_relaxed);
-    }
-
-    stats.reset();
-    current_age = 0;
-}
-
-void TranspositionTable::printStats() const {
-    printf("TranspositionTable Stats:\n");
-    printf("  Probes: %llu\n", stats.probes.load());
-    printf("  Hits: %llu (%.1f%%)\n", stats.hits.load(), stats.hitRate());
-    printf("  Stores: %llu\n", stats.stores.load());
-    printf("  Collisions: %llu\n", stats.collisions.load());
-    printf("  Table size: %zu entries (%.1f MB)\n",
-           TABLE_SIZE,
-           (TABLE_SIZE * sizeof(TTEntry)) / (1024.0 * 1024.0));
-}
-
-}  // namespace shardok
@@ -1,91 +0,0 @@
-//
-// TranspositionTable.hpp - Cache for game state evaluations to avoid redundant calculations
-//
-
-#ifndef EAGLE0_TRANSPOSITIONTABLE_HPP
-#define EAGLE0_TRANSPOSITIONTABLE_HPP
-
-#include <atomic>
-#include <cstdint>
-#include <optional>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-namespace shardok {
-
-using ScoreValue = double;
-// PlayerId already defined in ShardokCTypes.h
-
-class TranspositionTable {
-public:
-    // Statistics for monitoring effectiveness
-    struct Stats {
-        std::atomic<uint64_t> probes{0};
-        std::atomic<uint64_t> hits{0};
-        std::atomic<uint64_t> stores{0};
-        std::atomic<uint64_t> collisions{0};
-
-        double hitRate() const {
-            uint64_t p = probes.load();
-            return p > 0 ? (100.0 * hits.load() / p) : 0.0;
-        }
-
-        void reset() {
-            probes = 0;
-            hits = 0;
-            stores = 0;
-            collisions = 0;
-        }
-    };
-
-private:
-    // Compact entry structure (actual size is greater than 16 bytes due to atomics and alignment)
-    struct TTEntry {
-        std::atomic<uint64_t> hash_full;  // Full hash for validation
-        std::atomic<float> score;         // Score as float to save space
-        std::atomic<uint8_t> depth;       // Search depth (0-255)
-        std::atomic<uint8_t> player_id;   // Player who is to move
-        std::atomic<uint16_t> age;        // For replacement strategy
-    };
-
-    static constexpr size_t TABLE_SIZE_BITS = 22;                  // 2^22 entries
-    static constexpr size_t TABLE_SIZE = 1ULL << TABLE_SIZE_BITS;  // 4M entries = 64MB
-    static constexpr size_t INDEX_MASK = TABLE_SIZE - 1;
-
-    std::vector<TTEntry> table;
-    Stats stats;
-    std::atomic<uint16_t> current_age{0};
-
-    // Hash function for FlatBuffer game state
-    uint64_t hashGameState(const GameStateW& state) const;
-
-public:
-    TranspositionTable();
-
-    // Probe the table for a cached evaluation
-    std::optional<ScoreValue> probe(const GameStateW& state, int depth, PlayerId player);
-
-    // Store an evaluation in the table
-    void store(const GameStateW& state, int depth, PlayerId player, ScoreValue score);
-
-    // Clear the entire table
-    void clear();
-
-    // Increment age for replacement strategy (call at start of each search)
-    void incrementAge() { current_age++; }
-
-    // Get statistics
-    const Stats& getStats() const { return stats; }
-
-    // Print statistics to stdout
-    void printStats() const;
-};
-
-// Global instance for the AI to use
-extern TranspositionTable g_transpositionTable;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_TRANSPOSITIONTABLE_HPP
@@ -1,29 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "mcts_ai",
-    srcs = ["MCTSAI.cpp"],
-    hdrs = ["MCTSAI.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:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common:random_generator",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_iterative_deepening",  # For SearchResult compatibility
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_score_calculator",
-        "//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/internal:mcts_node",
-        "//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/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
@@ -1,869 +0,0 @@
-//
-// MCTS-based AI implementation for Shardok
-//
-
-#include "MCTSAI.hpp"
-
-#include <algorithm>
-#include <cmath>
-#include <future>
-#include <limits>
-#include <mutex>
-#include <random>
-#include <thread>
-
-#include "internal/MCTSNode.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-// Type alias for internal MCTSNode
-using MCTSNode = internal::MCTSNode;
-
-// Static helper for average random generator
-static const std::vector _averageSequence = {0.5};
-static const auto _averageGenerator = std::make_shared<SequenceRandomGenerator>(_averageSequence);
-
-MCTSAI::MCTSAI(
-        const PlayerId playerId,
-        const bool isDefender,
-        AIStrategy strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        MCTSConfig config)
-    : playerId(playerId),
-      isDefender(isDefender),
-      strategy(std::move(strategy)),
-      castleCoords(castleCoords),
-      apdCache(apdCache),
-      alCache(alCache),
-      config(std::move(config)) {}
-
-auto MCTSAI::Search(
-        const GameSettingsSPtr& settings,
-        const GameStateW& state,
-        const std::vector<CommandProto>& commands,
-        const AITimeBudget& budget) const -> SearchResult {
-    const auto startTime = std::chrono::steady_clock::now();
-    SearchResult result;
-
-    if (commands.empty()) {
-        result.searchCompleted = true;
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-        return result;
-    }
-
-    if (commands.size() == 1) {
-        result.searchCompleted = true;
-        result.bestCommandIndex = 0;
-        result.bestScore = 0;
-        result.availableCommandCount = 1;
-        result.depthAchieved = 1;
-        result.commandCountEvaluated = 1;
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-        return result;
-    }
-
-    const auto& settingsGetter = settings->GetGetter();
-
-    // Compute critical tiles once to avoid 8.5% runtime overhead in ShardokEngine construction
-    const auto criticalTiles = GetCriticalTileLocations(state->hex_map());
-    const auto guessedEngine = ShardokEngine(settings, state, criticalTiles);
-    const auto deadline = startTime + budget.remainingBudget;
-
-    // Build MCTS tree
-    auto rootNode = BuildMCTSTree(guessedEngine, settingsGetter, criticalTiles, deadline);
-
-    if (rootNode) {
-        // Get best command from tree
-        const MCTSNode* bestChild = rootNode->GetBestFinalChild();
-
-        if (bestChild) {
-            result.searchCompleted = true;
-            result.bestCommandIndex = bestChild->commandIndex;
-            result.bestScore = bestChild->lookaheadScore;
-            result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-
-            // Calculate max depth reached in the tree
-            std::function<int(const MCTSNode*)> getMaxDepth = [&](const MCTSNode* node) -> int {
-                int maxChildDepth = node->depth;
-                for (const auto& child : node->children) {
-                    maxChildDepth = std::max(maxChildDepth, getMaxDepth(child.get()));
-                }
-                return maxChildDepth;
-            };
-            result.depthAchieved = getMaxDepth(rootNode.get());
-
-            // Count total nodes visited
-            std::function<size_t(const MCTSNode*)> countVisited =
-                    [&](const MCTSNode* node) -> size_t {
-                size_t count = (node->visitCount > 0) ? 1 : 0;
-                for (const auto& child : node->children) { count += countVisited(child.get()); }
-                return count;
-            };
-
-            result.commandCountEvaluated = countVisited(rootNode.get());
-            result.availableCommandCount = commands.size();
-
-            // MCTS-specific logging
-            printf("MCTS: Selected command %zu (visit:%d, reward:%.2f, lookahead:%.2f) from %zu "
-                   "options\n",
-                   bestChild->commandIndex,
-                   bestChild->visitCount,
-                   bestChild->averageReward,
-                   bestChild->lookaheadScore,
-                   rootNode->children.size());
-
-            // Log top 3 commands for debugging with their best sequences
-            std::vector<MCTSNode*> sortedChildren;
-            for (const auto& child : rootNode->children) { sortedChildren.push_back(child.get()); }
-            std::ranges::sort(sortedChildren, [](const MCTSNode* a, const MCTSNode* b) {
-                return a->visitCount > b->visitCount;
-            });
-
-            printf("MCTS: Top commands by visits:\n");
-            for (size_t i = 0; i < std::min(static_cast<size_t>(3), sortedChildren.size()); ++i) {
-                auto* child = sortedChildren[i];
-                printf("  [%zu] cmd:%zu visits:%d immediate:%.2f backprop:%.2f type:%s",
-                       i,
-                       child->commandIndex,
-                       child->visitCount,
-                       child->immediateScore,
-                       child->averageReward,
-                       CommandType_Name(child->commandType).c_str());
-
-                // Show unit and target info for commands that have them
-                if (child->actorUnitId >= 0) { printf(" unit:%d", child->actorUnitId); }
-                if (child->targetRow >= 0 && child->targetCol >= 0) {
-                    printf(" target:(%d,%d)", child->targetRow, child->targetCol);
-                }
-
-                // Show sequence preview for this command
-                if (!child->children.empty()) {
-                    // Find best child by visits
-                    MCTSNode* bestNext = nullptr;
-                    int maxVisits = 0;
-                    for (const auto& grandchild : child->children) {
-                        if (grandchild->visitCount > maxVisits) {
-                            maxVisits = grandchild->visitCount;
-                            bestNext = grandchild.get();
-                        }
-                    }
-                    if (bestNext) {
-                        printf(" -> %s", CommandType_Name(bestNext->commandType).c_str());
-                    }
-                }
-                printf("\n");
-            }
-
-            printf("MCTS: Tree stats - max depth:%zu, total nodes:%zu, root visits:%d\n",
-                   result.depthAchieved,
-                   result.commandCountEvaluated,
-                   rootNode->visitCount);
-
-            // Log the best command sequence from the chosen command
-            struct SequenceNode {
-                size_t commandIndex;
-                std::string commandType;
-                int actorUnitId;
-                int targetRow;
-                int targetCol;
-                double immediateScore;
-                double backpropScore;
-            };
-            std::vector<SequenceNode> bestSequence;
-            bestSequence.reserve(5);
-            auto current = const_cast<MCTSNode*>(bestChild);
-            double sequenceScore = bestChild->averageReward;
-
-            // Trace the best path from chosen command (most visited child at each level)
-            while (current) {
-                bestSequence.push_back(
-                        {current->commandIndex,
-                         CommandType_Name(current->commandType),
-                         current->actorUnitId,
-                         current->targetRow,
-                         current->targetCol,
-                         current->immediateScore,
-                         current->averageReward});
-
-                // If no children, we've reached the end of the sequence
-                if (current->children.empty()) { break; }
-
-                // Find most visited child
-                MCTSNode* bestChildNode = nullptr;
-                int maxVisits = 0;
-                for (const auto& child : current->children) {
-                    if (child->visitCount > maxVisits) {
-                        maxVisits = child->visitCount;
-                        bestChildNode = child.get();
-                    }
-                }
-                current = bestChildNode;
-                if (current) {
-                    sequenceScore = current->averageReward;  // Update to final score
-                }
-            }
-
-            if (!bestSequence.empty()) {
-                printf("MCTS: Best sequence from chosen command (final: %.2f):\n", sequenceScore);
-                for (size_t i = 0; i < bestSequence.size(); ++i) {
-                    const auto& [commandIndex, commandType, actorUnitId, targetRow, targetCol, immediateScore, backpropScore] =
-                            bestSequence[i];
-                    printf("  %zu. cmd:%zu %s", i + 1, commandIndex, commandType.c_str());
-
-                    // Add unit and target info if present
-                    if (actorUnitId >= 0) { printf(" unit:%d", actorUnitId); }
-                    if (targetRow >= 0 && targetCol >= 0) {
-                        printf(" target:(%d,%d)", targetRow, targetCol);
-                    }
-
-                    printf(" (immediate:%.2f, backprop:%.2f)\n", immediateScore, backpropScore);
-                }
-            }
-        }
-    }
-
-    const auto endTime = std::chrono::steady_clock::now();
-    result.timeUsed = std::chrono::duration_cast<std::chrono::milliseconds>(endTime - startTime);
-
-    return result;
-}
-
-auto MCTSAI::BuildMCTSTree(
-        const ShardokEngine& engine,
-        const SettingsGetter& settingsGetter,
-        const CoordsSet& criticalTileCoords,
-        const std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode> {
-    // Clear transposition registry for this search
-    if (config.enableTranspositionDetection) { stateRegistry.clear(); }
-
-    // Create root node
-    auto root = std::make_unique<MCTSNode>(
-            0,
-            net::eagle0::shardok::common::END_TURN_COMMAND,
-            playerId,
-            0,
-            isDefender);
-    root->resultingGameState = engine.GetCurrentGameState();
-
-    // Register root node in transposition table if enabled
-    if (config.enableTranspositionDetection) {
-        root->stateHash = root->resultingGameState.ComputeFNV1aHash();
-        stateRegistry[root->stateHash] = root.get();
-    }
-
-    // Initialize root with available commands
-    const CommandListSPtr rootCommands = engine.GetAvailableCommandsForAIPlayer(playerId);
-    if (!rootCommands || rootCommands->empty()) { return root; }
-
-    // Filter commands for better performance
-    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
-            rootCommands,
-            playerId,
-            isDefender,
-            engine.GetCurrentGameState(),
-            settingsGetter,
-            apdCache);
-
-    root->untriedCommands = filteredIndices;
-    root->fullyExpanded = filteredIndices.empty();
-
-    // Main MCTS loop
-    int iterations = 0;
-
-    printf("MCTS: Starting search with %zu filtered commands (budget: %.0fms)\n",
-           filteredIndices.size(),
-           std::chrono::duration<double, std::milli>(deadline - std::chrono::steady_clock::now())
-                   .count());
-
-    if (config.useMultithreading) {
-        // Parallel MCTS: Run iterations until time budget expires
-        const int numThreads =
-                std::min(config.numThreads, static_cast<int>(std::thread::hardware_concurrency()));
-        std::vector<std::future<void>> futures;
-        std::mutex treeMutex;            // Protect tree updates
-        std::atomic totalIterations{0};  // Track iterations across threads
-
-        for (int t = 0; t < numThreads; ++t) {
-            futures.push_back(std::async(std::launch::async, [&, this] {
-                while (std::chrono::steady_clock::now() < deadline) {
-                    ++totalIterations;
-
-                    // Selection and expansion need locking
-                    MCTSNode* selected;
-                    {
-                        std::lock_guard lock(treeMutex);
-                        selected = MCTSSelection(root.get());
-                        if (selected && !selected->isTerminal && selected->CanExpand()) {
-                            selected = MCTSExpansion(
-                                    selected,
-                                    engine,
-                                    settingsGetter,
-                                    criticalTileCoords);
-                        }
-                    }
-
-                    // Skip simulation if selection failed (all children redundant)
-                    if (!selected) continue;
-
-                    // Simulation can run in parallel from the selected node's state
-                    // Note: Creating engine from node state is correct for MCTS simulation
-
-                    // Backpropagation needs locking
-                    {
-                        ShardokEngine nodeEngine(
-                                engine.GetGameSettings(),
-                                selected->resultingGameState,
-                                criticalTileCoords);
-                        const double reward =
-                                MCTSSimulation(nodeEngine, selected->playerId, settingsGetter);
-                        std::lock_guard lock(treeMutex);
-                        MCTSBackpropagation(selected, reward);
-                    }
-                }
-            }));
-        }
-
-        // Wait for all threads to complete
-        for (auto& future : futures) { future.get(); }
-        iterations = totalIterations.load();  // Get total from all threads
-    } else {
-        // Sequential MCTS - run until time budget expires
-        while (std::chrono::steady_clock::now() < deadline) {
-            // Selection
-            MCTSNode* selected = MCTSSelection(root.get());
-
-            // Skip if selection failed (all children redundant)
-            if (!selected) continue;
-
-            // Expansion
-            if (!selected->isTerminal && selected->CanExpand()) {
-                selected = MCTSExpansion(selected, engine, settingsGetter, criticalTileCoords);
-            }
-
-            // Simulation (from selected node's state)
-            ShardokEngine nodeEngine(
-                    engine.GetGameSettings(),
-                    selected->resultingGameState,
-                    criticalTileCoords);
-            double reward = MCTSSimulation(
-                    nodeEngine,
-                    selected->playerId,
-                    settingsGetter);  // Use node's player, not original player
-
-            // Backpropagation
-            MCTSBackpropagation(selected, reward);
-
-            iterations++;
-        }
-    }
-
-    printf("MCTS: Completed %d iterations, root has %zu children\n",
-           iterations,
-           root->children.size());
-
-    return root;
-}
-
-auto MCTSAI::MCTSSelection(MCTSNode* root) const -> MCTSNode* {
-    MCTSNode* current = root;
-
-    while (!current->isTerminal && !current->isRedundant) {
-        if (current->CanExpand()) {
-            return current;  // Node has untried commands
-        } else if (!current->children.empty()) {
-            current = current->GetBestChild(config.explorationConstant);
-            if (!current) break;
-        } else {
-            break;  // Leaf node
-        }
-    }
-
-    return current;
-}
-
-auto MCTSAI::MCTSExpansion(
-        MCTSNode* node,
-        const ShardokEngine& engine,
-        const SettingsGetter& settingsGetter,
-        const CoordsSet& criticalTileCoords) const -> MCTSNode* {
-    static int expansionCallCount = 0;
-    if (expansionCallCount < 3) {
-        printf("MCTSExpansion called %d: node depth:%d untried:%zu\n",
-               expansionCallCount++,
-               node->depth,
-               node->untriedCommands.size());
-    }
-
-    if (node->untriedCommands.empty()) return node;
-
-    // Don't expand beyond maximum depth to prevent unbounded tree growth
-    if (node->depth >= config.maxTreeDepth) {
-        node->fullyExpanded = true;
-        node->untriedCommands.clear();
-        return node;
-    }
-
-    // Pick a random untried command
-    std::random_device rd;
-    std::mt19937 gen(rd());
-    std::uniform_int_distribution dis(0, static_cast<int>(node->untriedCommands.size() - 1));
-    const size_t randomIndex = dis(gen);
-
-    const auto commandIndex = node->untriedCommands[randomIndex];
-    node->untriedCommands.erase(node->untriedCommands.begin() + randomIndex);
-
-    // Create engine from the node's current state (not root state!)
-    const auto nodeEngine = std::make_shared<ShardokEngine>(
-            engine.GetGameSettings(),
-            node->resultingGameState,
-            criticalTileCoords);
-
-    // Get command descriptor from the node's state
-    const CommandListSPtr commands = nodeEngine->GetAvailableCommandsForAIPlayer(node->playerId);
-    if (!commands || commandIndex >= commands->size()) return node;
-
-    const auto& command = commands->at(commandIndex);
-    const auto commandType = command->GetCommandType();
-    const auto descriptor = command->GetCommandProto();
-
-    // Create child node
-    auto child = std::make_unique<MCTSNode>(
-            commandIndex,
-            commandType,
-            node->playerId,
-            node->depth + 1,
-            node->isDefender);
-    child->parent = node;
-
-    // Extract actor unit ID if present
-    if (descriptor.has_actor()) { child->actorUnitId = descriptor.actor().value(); }
-
-    // Extract target coordinates if present
-    // Note: In protobuf3, target is always present but may have default values
-    // We'll always capture the coordinates - commands without targets will have (-1,-1) by default
-    const auto& target = descriptor.target();
-    child->targetRow = target.row();
-    child->targetCol = target.column();
-
-    // Declare variables that will be used later
-
-    // Handle randomness appropriately based on command type
-    if (command->HasOdds()) {
-        // For commands with odds, use average roll for expansion
-        // For expansion, use average roll regardless of success chance
-        const auto generator = std::make_shared<SequenceRandomGenerator>(std::vector{0.5});
-        nodeEngine->PostCommand(node->playerId, commandIndex, generator);
-    } else {
-        // Use average generator for deterministic evaluation
-        nodeEngine->PostCommand(node->playerId, commandIndex, _averageGenerator);
-    }
-
-    child->resultingGameState = nodeEngine->GetCurrentGameState();
-
-    // Check whose turn it is after executing the command
-    PlayerId currentPlayer = nodeEngine->GetCurrentPlayerId();
-    bool isOurTurn = (currentPlayer == playerId);
-
-    // Update child's player ID to reflect whose turn it actually is
-    child->playerId = currentPlayer;
-
-    // Calculate immediate score (always from our perspective)
-    child->immediateScore = AIScoreCalculator::GuessedStateScore(
-            isDefender,  // Use our original role, not node's
-            child->resultingGameState,
-            strategy,
-            castleCoords,
-            settingsGetter,
-            apdCache,
-            alCache);
-
-    // Initially, lookahead score equals immediate score
-    child->lookaheadScore = child->immediateScore;
-
-    // Debug: Log first few expansions to see what's happening
-    static int expansionCount = 0;
-    if (expansionCount < 5) {
-        printf("MCTS Expansion %d: cmd:%zu type:%s immediate_score:%.2f\n",
-               expansionCount++,
-               commandIndex,
-               CommandType_Name(commandType).c_str(),
-               child->immediateScore);
-    }
-
-    // Check if terminal
-    child->isTerminal = IsTerminalForPlayer(child->resultingGameState, playerId, settingsGetter);
-
-    // Transposition detection
-    if (config.enableTranspositionDetection) {
-        child->stateHash = child->resultingGameState.ComputeFNV1aHash();
-
-        auto existingIt = stateRegistry.find(child->stateHash);
-        if (existingIt != stateRegistry.end()) {
-            MCTSNode* existingNode = existingIt->second;
-
-            // Apply tie-breaking rules to determine which node to keep
-            bool shouldPruneChild = false;
-
-            if (child->depth > existingNode->depth) {
-                // Rule 1: Prune deeper node (current child is deeper)
-                shouldPruneChild = true;
-            } else if (child->depth == existingNode->depth) {
-                // Rule 2: At same depth, prune node with higher command index
-                if (child->commandIndex > existingNode->commandIndex) {
-                    shouldPruneChild = true;
-                } else {
-                    // Current child wins - mark existing node as redundant
-                    existingNode->isRedundant = true;
-                    stateRegistry[child->stateHash] = child.get();  // Update registry
-                }
-            } else {
-                // Child is shallower - mark existing node as redundant
-                existingNode->isRedundant = true;
-                stateRegistry[child->stateHash] = child.get();  // Update registry
-            }
-
-            if (shouldPruneChild) {
-                child->isRedundant = true;
-                // Don't expand redundant nodes
-            }
-        } else {
-            // New state - register it
-            stateRegistry[child->stateHash] = child.get();
-        }
-    }
-
-    // Get available commands for child - only if it's still our turn and not redundant
-    if (!child->isTerminal && !child->isRedundant && isOurTurn) {
-        const CommandListSPtr childCommands =
-                nodeEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        if (childCommands) {
-            const std::vector<size_t> childFiltered = AICommandFilter::FilterCommands(
-                    childCommands,
-                    currentPlayer,
-                    isDefender,  // Use our original role
-                    child->resultingGameState,
-                    settingsGetter,
-                    apdCache);
-            child->untriedCommands = childFiltered;
-            child->fullyExpanded = childFiltered.empty();
-        }
-    } else if (!isOurTurn) {
-        // Mark as terminal if it's not our turn - we can't expand opponent moves
-        child->isTerminal = true;
-        child->fullyExpanded = true;
-    }
-
-    // Update parent's expansion status
-    if (node->untriedCommands.empty()) { node->fullyExpanded = true; }
-
-    MCTSNode* childPtr = child.get();
-    node->children.push_back(std::move(child));
-
-    return childPtr;
-}
-
-auto MCTSAI::MCTSSimulation(
-        const ShardokEngine& engineState,
-        PlayerId startingPlayer,
-        const SettingsGetter& settingsGetter) const -> double {
-    // Create copy for simulation
-    auto simEngine = std::make_shared<ShardokEngine>(engineState, false);
-
-    // Always evaluate from our AI's perspective (not the startingPlayer's perspective)
-    const double initialScore = AIScoreCalculator::GuessedStateScore(
-            isDefender,
-            simEngine->GetCurrentGameState(),
-            strategy,
-            castleCoords,
-            settingsGetter,
-            apdCache,
-            alCache);
-
-    // Debug: Note that we're always scoring from our AI's perspective regardless of startingPlayer
-    (void)startingPlayer;  // Acknowledge parameter to avoid warning
-
-    // Fast rollout with random/heuristic moves until terminal
-    int simulationSteps = 0;
-    for (int step = 0; step < config.maxSimulationDepth; ++step) {
-        const GameStateW& currentState = simEngine->GetCurrentGameState();
-
-        // Get whose turn it is
-        const PlayerId currentPlayer = simEngine->GetCurrentPlayerId();
-
-        // Check if terminal
-        if (IsTerminalForPlayer(currentState, playerId, settingsGetter)) { break; }
-
-        // Continue as long as it's still our turn (don't stop after each individual command)
-        // In this game, a player can move multiple units before turn switches
-        if (currentPlayer != playerId) {
-            // Turn switched to opponent - stop simulation immediately
-            break;
-        }
-
-        simulationSteps++;
-
-        // Get available commands for current player
-        const CommandListSPtr commands = simEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        if (!commands || commands->empty()) break;
-
-        // Select command based on simulation policy
-        const auto commandIndex = static_cast<int>(
-                SelectSimulationCommand(commands, currentPlayer, simEngine, settingsGetter));
-
-        // Execute command
-        simEngine->PostCommand(currentPlayer, commandIndex, _averageGenerator);
-
-        // Debug: Only log if turn changed unexpectedly
-        const PlayerId newPlayer = simEngine->GetCurrentPlayerId();
-        static int debugCount = 0;
-        if (newPlayer != currentPlayer && debugCount < 5) {
-            const auto commandType = commands->at(commandIndex)->GetCommandType();
-            printf("MCTS Sim step %d: cmd_type:%s player_before:%d player_after:%d\n",
-                   simulationSteps,
-                   CommandType_Name(commandType).c_str(),
-                   currentPlayer,
-                   newPlayer);
-            printf("  WARNING: Turn changed after command!\n");
-            debugCount++;
-        }
-    }
-
-    // Evaluate final position
-    const double finalScore = AIScoreCalculator::GuessedStateScore(
-            isDefender,
-            simEngine->GetCurrentGameState(),
-            strategy,
-            castleCoords,
-            settingsGetter,
-            apdCache,
-            alCache);
-
-    // Debug: Log first few simulations to see depth and score change
-    static int simCount = 0;
-    if (simCount < 3) {
-        printf("MCTS Simulation %d: steps:%d initial:%.2f final:%.2f delta:%.2f\n",
-               simCount++,
-               simulationSteps,
-               initialScore,
-               finalScore,
-               finalScore - initialScore);
-    }
-
-    return finalScore;
-}
-
-auto MCTSAI::MCTSBackpropagation(MCTSNode* node, double reward) -> void {
-    while (node) {
-        node->visitCount++;
-        node->totalReward += reward;
-        node->averageReward = node->totalReward / node->visitCount;
-
-        // Update lookahead score as weighted average
-        if (node->visitCount == 1) {
-            node->lookaheadScore = reward;
-        } else {
-            node->lookaheadScore =
-                    (node->lookaheadScore * (node->visitCount - 1) + reward) / node->visitCount;
-        }
-
-        node = node->parent;
-    }
-}
-
-auto MCTSAI::IsTerminalForPlayer(
-        const GameStateW& gameState,
-        PlayerId /*currentPlayer*/,
-        const SettingsGetter& settingsGetter) -> bool {
-    // Check if game is over
-    if (gameState->status()->state() ==
-                net::eagle0::shardok::storage::fb::GameStatus_::State_VICTORY ||
-        gameState->status()->state() ==
-                net::eagle0::shardok::storage::fb::GameStatus_::State_DRAW) {
-        return true;
-    }
-
-    // Check max rounds
-    if (gameState->current_round() >= settingsGetter.Backing().max_rounds()) { return true; }
-
-    return false;
-}
-
-auto MCTSAI::SelectSimulationCommand(
-        const CommandListSPtr& commands,
-        PlayerId currentPlayer,
-        const std::shared_ptr<ShardokEngine>& simEngine,
-        const SettingsGetter& settingsGetter) const -> size_t {
-    if (commands->size() == 1) {
-        return 0;  // Only one choice
-    }
-
-    std::random_device rd;
-    std::mt19937 gen(rd());
-
-    switch (config.simulationPolicy) {
-        case MCTSSimulationPolicy::RANDOM: {
-            // Pure random selection
-            std::uniform_int_distribution<> dis(0, commands->size() - 1);
-            return dis(gen);
-        }
-
-        case MCTSSimulationPolicy::FILTERED_RANDOM: {
-            // Filter commands first, then random selection
-            const auto filteredIndices = AICommandFilter::FilterCommands(
-                    commands,
-                    currentPlayer,
-                    isDefender,
-                    simEngine->GetCurrentGameState(),
-                    settingsGetter,
-                    apdCache);
-
-            if (filteredIndices.empty()) {
-                // Fallback to random if no commands pass filter
-                std::uniform_int_distribution<> dis(0, commands->size() - 1);
-                return dis(gen);
-            }
-
-            std::uniform_int_distribution<> dis(0, filteredIndices.size() - 1);
-            return filteredIndices[dis(gen)];
-        }
-
-        case MCTSSimulationPolicy::BEST_IMMEDIATE: {
-            // Evaluate all commands and pick the best
-            double bestScore = -std::numeric_limits<double>::max();
-            size_t bestIndex = 0;
-
-            for (size_t i = 0; i < commands->size(); ++i) {
-                // Create a temporary engine to evaluate this command
-                const auto testEngine = std::make_shared<ShardokEngine>(*simEngine, false);
-
-                // Get score BEFORE executing command (for potential player flip comparison)
-                const double preScore = AIScoreCalculator::GuessedStateScore(
-                        isDefender,
-                        testEngine->GetCurrentGameState(),
-                        strategy,
-                        castleCoords,
-                        settingsGetter,
-                        apdCache,
-                        alCache);
-
-                const PlayerId playerBefore = testEngine->GetCurrentPlayerId();
-                testEngine->PostCommand(currentPlayer, i, _averageGenerator);
-                const PlayerId playerAfter = testEngine->GetCurrentPlayerId();
-
-                double score;
-                if (playerAfter != playerBefore) {
-                    // Player flipped - use pre-execution score to avoid opponent turn effects
-                    score = preScore;
-                } else {
-                    // Normal command - use post-execution score
-                    score = AIScoreCalculator::GuessedStateScore(
-                            isDefender,
-                            testEngine->GetCurrentGameState(),
-                            strategy,
-                            castleCoords,
-                            settingsGetter,
-                            apdCache,
-                            alCache);
-                }
-
-                if (score > bestScore) {
-                    bestScore = score;
-                    bestIndex = i;
-                }
-            }
-            return bestIndex;
-        }
-
-        case MCTSSimulationPolicy::WEIGHTED_BEST_IMMEDIATE: {
-            // Evaluate all commands and weight by ranking
-            struct CommandScore {
-                size_t index;
-                double score;
-            };
-
-            std::vector<CommandScore> commandScores;
-            commandScores.reserve(commands->size());
-
-            for (size_t i = 0; i < commands->size(); ++i) {
-                // Create a temporary engine to evaluate this command
-                const auto testEngine = std::make_shared<ShardokEngine>(*simEngine, false);
-
-                // Get score BEFORE executing command (for potential player flip comparison)
-                const double preScore = AIScoreCalculator::GuessedStateScore(
-                        isDefender,
-                        testEngine->GetCurrentGameState(),
-                        strategy,
-                        castleCoords,
-                        settingsGetter,
-                        apdCache,
-                        alCache);
-
-                const PlayerId playerBefore = testEngine->GetCurrentPlayerId();
-                testEngine->PostCommand(currentPlayer, i, _averageGenerator);
-                const PlayerId playerAfter = testEngine->GetCurrentPlayerId();
-
-                double score;
-                if (playerAfter != playerBefore) {
-                    // Player flipped - use pre-execution score to avoid opponent turn effects
-                    score = preScore;
-                } else {
-                    // Normal command - use post-execution score
-                    score = AIScoreCalculator::GuessedStateScore(
-                            isDefender,
-                            testEngine->GetCurrentGameState(),
-                            strategy,
-                            castleCoords,
-                            settingsGetter,
-                            apdCache,
-                            alCache);
-                }
-
-                commandScores.push_back({i, score});
-            }
-
-            // Sort by score (best first)
-            std::sort(
-                    commandScores.begin(),
-                    commandScores.end(),
-                    [](const CommandScore& a, const CommandScore& b) { return a.score > b.score; });
-
-            // Assign weights: 1.0 for best, 0.5 for second, 0.33 for third, etc.
-            std::vector<double> weights;
-            weights.reserve(commandScores.size());
-            double totalWeight = 0.0;
-
-            for (size_t i = 0; i < commandScores.size(); ++i) {
-                double weight = 1.0 / (i + 1);  // 1/1, 1/2, 1/3, ...
-                weights.push_back(weight);
-                totalWeight += weight;
-            }
-
-            // Random selection based on weights
-            std::uniform_real_distribution dis(0.0, totalWeight);
-            const double target = dis(gen);
-            double cumulative = 0.0;
-
-            for (size_t i = 0; i < weights.size(); ++i) {
-                cumulative += weights[i];
-                if (cumulative >= target) { return commandScores[i].index; }
-            }
-
-            // Fallback (shouldn't happen)
-            return commandScores[0].index;
-        }
-    }
-
-    // Fallback to random (shouldn't reach here)
-    std::uniform_int_distribution dis(0, static_cast<int>(commands->size() - 1));
-    return dis(gen);
-}
-
-}  // namespace shardok
@@ -1,128 +0,0 @@
-//
-// MCTS-based AI system for Shardok
-// Alternative to IterativeDeepeningAI using Monte Carlo Tree Search
-//
-
-#ifndef EAGLE0_MCTSAI_HPP
-#define EAGLE0_MCTSAI_HPP
-
-#include <chrono>
-#include <future>
-#include <memory>
-#include <unordered_map>
-#include <vector>
-
-#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/ShardokCommand.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/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-
-// MCTSNode is defined in internal/MCTSNode.hpp
-namespace internal {
-struct MCTSNode;
-}
-
-// Simulation policy for MCTS rollouts
-enum class MCTSSimulationPolicy {
-    RANDOM,                  // Pure random selection
-    FILTERED_RANDOM,         // Random from filtered commands
-    BEST_IMMEDIATE,          // Choose best immediate score
-    WEIGHTED_BEST_IMMEDIATE  // Random weighted by score ranking
-};
-
-// 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 (when enabled)
-    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
-    bool enableTranspositionDetection = true;  // Enable pruning of duplicate states
-};
-
-class MCTSAI {
-public:
-    using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-    using SearchResult = IterativeDeepeningAI::SearchResult;
-
-    MCTSAI(PlayerId playerId,
-           bool isDefender,
-           AIStrategy strategy,
-           const CoordsSet& castleCoords,
-           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 std::vector<CommandProto>& commands,
-            const AITimeBudget& budget) const -> SearchResult;
-
-    // Get/set configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return config; }
-    void SetConfig(const MCTSConfig& newConfig) { config = newConfig; }
-
-private:
-    PlayerId playerId;
-    bool isDefender;
-    AIStrategy strategy;
-    const CoordsSet& castleCoords;
-    const APDCache& apdCache;
-    const ALCache& alCache;
-    MCTSConfig config;
-
-    // Transposition detection infrastructure
-    mutable std::unordered_map<uint64_t, internal::MCTSNode*>
-            stateRegistry;  // Hash -> first node mapping
-
-    // Internal MCTS tree building
-    [[nodiscard]] auto BuildMCTSTree(
-            const ShardokEngine& engine,
-            const SettingsGetter& settingsGetter,
-            const CoordsSet& criticalTileCoords,
-            std::chrono::steady_clock::time_point deadline) const
-            -> std::unique_ptr<internal::MCTSNode>;
-
-    // MCTS algorithm phases
-    auto MCTSSelection(internal::MCTSNode* root) const -> internal::MCTSNode*;
-    auto MCTSExpansion(
-            internal::MCTSNode* node,
-            const ShardokEngine& engine,
-            const SettingsGetter& settingsGetter,
-            const CoordsSet& criticalTileCoords) const -> internal::MCTSNode*;
-    auto MCTSSimulation(
-            const ShardokEngine& engineState,
-            PlayerId currentPlayer,
-            const SettingsGetter& settingsGetter) const -> double;
-    static auto MCTSBackpropagation(internal::MCTSNode* node, double reward) -> void;
-
-    // Helper functions
-    [[nodiscard]] static auto IsTerminalForPlayer(
-            const GameStateW& gameState,
-            PlayerId currentPlayer,
-            const SettingsGetter& settingsGetter) -> bool;
-
-    // Simulation command selection based on policy
-    [[nodiscard]] auto SelectSimulationCommand(
-            const CommandListSPtr& commands,
-            PlayerId currentPlayer,
-            const std::shared_ptr<ShardokEngine>& simEngine,
-            const SettingsGetter& settingsGetter) const -> size_t;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTSAI_HPP
@@ -1,16 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "mcts_node",
-    hdrs = ["MCTSNode.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
@@ -1,210 +0,0 @@
-//
-// Internal MCTS Node structure for Shardok AI
-// This is an implementation detail and should not be used by external code
-//
-
-#ifndef EAGLE0_INTERNAL_MCTSNODE_HPP
-#define EAGLE0_INTERNAL_MCTSNODE_HPP
-
-#include <cmath>
-#include <cstdio>
-#include <limits>
-#include <memory>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-// Suppress the protobuf deprecation warning temporarily
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma GCC diagnostic pop
-
-namespace shardok {
-namespace internal {
-
-// Import CommandType for use within the internal namespace
-using CommandType = net::eagle0::shardok::common::CommandType;
-
-// MCTS Node structure
-struct MCTSNode {
-    // Command information
-    size_t commandIndex;
-    CommandType commandType;
-    int actorUnitId = -1;  // Unit performing the command (-1 if not applicable)
-    int targetRow = -1;    // Target coordinate row (-1 if not applicable)
-    int targetCol = -1;    // Target coordinate column (-1 if not applicable)
-
-    // Score information
-    double immediateScore;
-    double lookaheadScore;
-
-    // Game state after this command
-    GameStateW resultingGameState;
-
-    // MCTS statistics
-    int visitCount = 0;
-    double totalReward = 0.0;
-    double averageReward = 0.0;
-    double ucb1Value = 0.0;
-
-    // Tree structure
-    std::vector<std::unique_ptr<MCTSNode>> children;
-    std::vector<size_t> untriedCommands;
-    bool fullyExpanded = false;
-    MCTSNode* parent = nullptr;
-
-    // Game context
-    PlayerId playerId;
-    int depth = 0;
-    bool isDefender = false;
-    bool isTerminal = false;
-
-    // Transposition detection
-    uint64_t stateHash = 0;
-    bool isRedundant = false;  // True if this node represents a duplicate state
-
-    MCTSNode(
-            const size_t cmdIndex,
-            const CommandType cmdType,
-            const PlayerId pid,
-            const int d,
-            const bool defender)
-        : commandIndex(cmdIndex),
-          commandType(cmdType),
-          immediateScore(0.0),
-          lookaheadScore(0.0),
-          playerId(pid),
-          depth(d),
-          isDefender(defender) {}
-
-    // Iterative destructor to avoid stack overflow with deep trees
-    ~MCTSNode() {
-        // Use iterative approach to destroy children
-        std::vector<std::unique_ptr<MCTSNode>> nodesToDestroy;
-        nodesToDestroy.swap(children);
-
-        while (!nodesToDestroy.empty()) {
-            // Take ownership of all children from the current batch
-            std::vector<std::unique_ptr<MCTSNode>> currentBatch;
-            currentBatch.swap(nodesToDestroy);
-
-            // Collect grandchildren for next iteration
-            for (const auto& node : currentBatch) {
-                if (node && !node->children.empty()) {
-                    for (auto& child : node->children) {
-                        nodesToDestroy.push_back(std::move(child));
-                    }
-                    node->children.clear();
-                }
-            }
-            // currentBatch goes out of scope here, destroying nodes with no children
-        }
-    }
-
-    // Calculate UCB1 value for this node
-    void CalculateUCB1(const double explorationConstant) {
-        if (visitCount == 0) {
-            ucb1Value = std::numeric_limits<double>::max();
-        } else if (parent && parent->visitCount > 0) {
-            ucb1Value = averageReward +
-                        explorationConstant * std::sqrt(std::log(parent->visitCount) / visitCount);
-        } else {
-            ucb1Value = averageReward;
-        }
-    }
-
-    // Check if this node can be expanded
-    [[nodiscard]] bool CanExpand() const { return !fullyExpanded && !untriedCommands.empty(); }
-
-    // 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();
-
-        static int selectionCallCount = 0;
-        const bool shouldDebug = selectionCallCount < 5;
-
-        for (auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            child->CalculateUCB1(explorationConstant);
-
-            if (child->ucb1Value > bestValue) {
-                bestValue = child->ucb1Value;
-                bestChild = child.get();
-            }
-
-            if (shouldDebug && child->visitCount > 0) {
-                printf("UCB1 Debug: cmd:%zu visits:%d reward:%.2f ucb1:%.2f%s\n",
-                       child->commandIndex,
-                       child->visitCount,
-                       child->averageReward,
-                       child->ucb1Value,
-                       child->isRedundant ? " [REDUNDANT]" : "");
-            }
-        }
-
-        if (shouldDebug) {
-            if (bestChild) {
-                printf("UCB1 Selected: cmd:%zu ucb1:%.2f\n",
-                       bestChild->commandIndex,
-                       bestChild->ucb1Value);
-            } else {
-                printf("UCB1 Selected: nullptr (all children redundant)\n");
-            }
-            selectionCallCount++;
-        }
-        return bestChild;
-    }
-
-    // Get best child based on average reward (for final selection)
-    [[nodiscard]] MCTSNode* GetBestFinalChild() const {
-        if (children.empty()) return nullptr;
-
-        MCTSNode* bestChild = nullptr;
-        double bestScore = -std::numeric_limits<double>::max();
-        int bestVisits = 0;
-
-        for (const auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            // For final selection, prefer most-visited node (robust child selection)
-            // Only consider nodes that have been visited
-            if (child->visitCount > bestVisits) {
-                bestVisits = child->visitCount;
-                bestScore = child->averageReward;
-                bestChild = child.get();
-            } else if (child->visitCount == bestVisits && child->averageReward > bestScore) {
-                // Tie-break on average reward
-                bestScore = child->averageReward;
-                bestChild = child.get();
-            }
-        }
-
-        // If no child was visited (shouldn't happen), fall back to lookahead score
-        if (!bestChild && !children.empty()) {
-            for (const auto& child : children) {
-                // Skip redundant nodes
-                if (child->isRedundant) continue;
-
-                if (child->lookaheadScore > bestScore) {
-                    bestScore = child->lookaheadScore;
-                    bestChild = child.get();
-                }
-            }
-        }
-
-        return bestChild;
-    }
-};
-
-}  // namespace internal
-}  // namespace shardok
-
-#endif  // EAGLE0_INTERNAL_MCTSNODE_HPP
@@ -0,0 +1,304 @@
+# AIScoreCalculator ThreadPool Migration Plan
+
+## Overview
+This document outlines the plan to migrate AIScoreCalculator from using std::async to using the new ThreadPool class with priority-based scheduling and deadline support.
+
+## Current State Analysis
+
+### std::async Usage
+1. **CalcOne method (line 893)**: Uses `std::async(std::launch::async, lookaheadLambda)` to asynchronously calculate lookahead scores
+2. **BestCommandIndex method (line 1053)**: Uses `std::async(std::launch::deferred, ...)` for deferred calculation of weighted scores
+3. **Future resolution (lines 1086-1091)**: Waits on all futures using `.get()` in a loop
+
+### Time Management
+- IterativeDeepeningAI manages time budgets via AITimeBudget structure
+- Time budget contains `remainingBudget` (std::chrono::milliseconds) that gets decremented
+- No explicit deadline passing to AIScoreCalculator currently
+
+## Migration Strategy
+
+### 1. ThreadPool Integration
+- Create a static thread pool instance with 32 threads in AIScoreCalculator
+- Thread pool will be shared across all AIScoreCalculator operations
+
+### 2. Priority Assignment
+- Priority = current lookahead depth (passed via `remainingLookahead` parameter)
+- Higher depth = higher priority (deeper searches are more valuable)
+- This ensures shallow searches complete first, allowing iterative deepening to work effectively
+
+### 3. Deadline Support
+- Calculate deadline based on remaining time budget from IterativeDeepeningAI
+- Pass deadline to thread pool using `enqueue_with_deadline` for time-critical tasks
+- Tasks that exceed deadline will be automatically skipped by the thread pool
+
+### 4. Implementation Details
+
+#### Changes to CalcOne:
+```cpp
+// OLD:
+returnValue.lookaheadScore = std::async(std::launch::async, lookaheadLambda);
+
+// NEW:
+// Priority = remainingLookahead (higher depth = higher priority)
+// Deadline = current_time + remaining_budget_fraction
+returnValue.lookaheadScore = threadPool.enqueue_with_deadline(
+    lookaheadLambda,
+    remainingLookahead,  // priority
+    deadline             // calculated from time budget
+);
+```
+
+#### Changes to BestCommandIndex:
+```cpp
+// Deferred calculations stay as-is (no change needed)
+// They're already using std::launch::deferred which is appropriate
+
+// The .get() loop (lines 1086-1091) can be moved to a lower priority task:
+auto futureResolutionTask = [&]() {
+    for (uint32_t i = 0; i < commandCount; i++) {
+        const auto count = static_cast<ScoreValue>(scoreFutures[i].size());
+        ScoreValue total = 0.0;
+        for (auto &oneFuture : scoreFutures[i]) { 
+            total += oneFuture.get(); 
+        }
+        allIndices[i].lookaheadScore = total / count;
+    }
+};
+
+// Enqueue with lower priority (0 or negative) to ensure all calculations complete first
+threadPool.enqueue(futureResolutionTask, 0);
+```
+
+### 5. Thread Pool Lifecycle
+- Initialize as static member: `static inline ThreadPool threadPool{32};`
+- Destruction handled automatically by ThreadPool destructor
+- No explicit cleanup needed
+
+### 6. Deadline Calculation
+- Need to pass time budget information down from IterativeDeepeningAI
+- Add optional `AITimeBudget*` parameter to CalcOne and BestCommandIndex
+- Calculate deadline as: `now() + (remainingBudget * depth_fraction)`
+- Deeper searches get proportionally less time
+
+### 7. Benefits
+1. **Better CPU utilization**: 32 threads vs unbounded std::async
+2. **Priority scheduling**: Deeper searches get higher priority
+3. **Deadline enforcement**: Automatic timeout handling
+4. **Resource control**: Fixed thread pool prevents thread explosion
+5. **Performance**: Thread reuse avoids creation/destruction overhead
+
+### 8. Testing Plan
+1. Verify thread pool initialization
+2. Test priority ordering (shallow searches complete first)
+3. Test deadline enforcement (expired tasks are skipped)
+4. Compare performance with existing implementation
+5. Stress test with multiple concurrent AI calculations
+
+### 9. Rollback Plan
+- Keep MULTITHREAD macro to allow switching between implementations
+- Add THREAD_POOL macro to conditionally compile new implementation
+- Allows A/B testing and gradual migration
+
+## Implementation Status
+
+### ✅ Completed
+1. **ThreadPool Integration** - Added static 32-thread pool to AIScoreCalculator
+2. **Priority Assignment** - Priority = current lookahead depth (higher depth = higher priority)
+3. **Deadline Support** - Calculate deadline based on remaining time budget from IterativeDeepeningAI
+4. **Method Signatures Updated** - Added `AITimeBudget* timeBudget` parameter to CalcOne and BestCommandIndex
+5. **std::async Replacement** - Replaced `std::async(std::launch::async)` with `threadPool.enqueue_with_deadline()`
+6. **Time Budget Integration** - IterativeDeepeningAI now passes timeBudget to AIScoreCalculator methods
+7. **Build System Updates** - Added thread_pool dependency to BUILD.bazel files
+8. **Build Verification** - Successfully builds with `bazel build //src/main/cpp/net/eagle0/shardok/ai:ai_score_calculator`
+
+### Implementation Details
+- **Priority Calculation**: `priority = remainingLookahead` (deeper searches get higher priority)
+- **Deadline Calculation**: `deadline = now + (remainingBudget / (remainingLookahead + 1))`
+- **Thread Pool**: Static 32-thread pool shared across all AIScoreCalculator operations
+- **Backward Compatibility**: MULTITHREAD macro preserved for rollback capability
+- **Deferred Tasks**: std::launch::deferred calls remain unchanged as planned
+
+### 🔧 Fixed Issues
+
+#### Build Issues
+- **SearchAtDepth method**: Fixed missing timeBudget parameter - now passes nullptr since this method doesn't have access to time budget
+- **AI Performance Runner**: Successfully builds and runs with `bazel build //src/main/cpp/net/eagle0/shardok/ai_performance_runner:ai_performance_runner`
+
+#### Runtime Issues  
+- **Hanging AI Performance Test**: ✅ FIXED WITH PROPER DEADLINE SUPPORT
+  - **Root Cause**: Deadline expiration in ThreadPool was skipping task execution, leaving futures unresolved
+  - **Symptom**: `./scripts/ai_perf_test.sh` would hang indefinitely when calling `oneFuture.get()` in BestCommandIndex
+  - **Solution**: Implemented proper status code system with `TaskResult<T>` wrapper
+    - Created `TaskStatus` enum (SUCCESS, DEADLINE_EXCEEDED, CANCELLED)
+    - Updated ThreadPool to return `TaskResult<T>` instead of raw `T`
+    - Tasks that exceed deadline return `TaskResult` with `DEADLINE_EXCEEDED` status
+    - AIScoreCalculator checks status codes and handles expired tasks gracefully
+  - **Additional Fix**: Lambda capture issue in `enqueue_with_deadline`
+    - **Problem**: Complex lambda capture syntax `[f = std::forward<F>(f), args..., deadline]` was causing compilation/runtime issues
+    - **Solution**: Used `std::bind` to create callable object: `auto actualTask = std::bind(std::forward<F>(f), std::forward<Args>(args)...);`
+    - **Result**: Cleaner, more reliable task capture and execution
+  - **Final Result**: Full deadline functionality restored, AI performance test runs correctly without hanging
+
+### Implementation Details - TaskResult System
+```cpp
+// TaskResult wrapper with status code
+template<typename T>
+struct TaskResult {
+    T value;
+    TaskStatus status;
+    
+    bool succeeded() const { return status == TaskStatus::SUCCESS; }
+    bool deadlineExceeded() const { return status == TaskStatus::DEADLINE_EXCEEDED; }
+    operator T() const { return value; } // Implicit conversion for compatibility
+};
+
+// Usage in AIScoreCalculator
+for (auto &oneFuture : scoreFutures[i]) { 
+    auto result = oneFuture.get();
+    if (result.succeeded()) {
+        total += result.value;
+        validResults++;
+    } else if (result.deadlineExceeded()) {
+        // Skip deadline-exceeded results, fall back to immediate score
+    }
+}
+```
+
+### Status: ✅ COMPLETE AND FULLY FUNCTIONAL  
+All ThreadPool migration work is complete with proper deadline support. The implementation:
+- ✅ Builds successfully 
+- ✅ Runs correctly with full deadline functionality
+- ✅ Handles deadline expiration gracefully without hanging
+- ✅ AI performance test works perfectly
+- ✅ Fixed infinite loop issue caused by TaskResult implicit conversion
+
+### 🔧 Final Issue Resolution - Infinite Loop Bug
+
+#### Problem: TaskResult Implicit Conversion Causing Infinite Recursion
+- **Root Cause**: TaskResult<T> had an implicit conversion operator that was interfering with AI search control flow
+- **Symptom**: AI performance test hanging in infinite loop, processing same set of futures repeatedly
+- **Evidence**: Debug output showed endless cycle processing futures 0-45
+
+#### Solution: Remove Implicit Conversion Operator
+- **Change**: Removed `operator T() const { return value; }` from TaskResult<T>
+- **Replacement**: Added explicit `.get()` method: `T get() const { return value; }`
+- **Code Updates**: Updated all AIScoreCalculator usage to explicitly call `.value` or handle TaskResult properly
+
+#### Updated TaskResult Implementation
+```cpp
+template<typename T>
+struct TaskResult {
+    T value;
+    TaskStatus status;
+    
+    // NO implicit conversion - this was causing infinite recursion
+    T get() const { return value; }
+    
+    bool succeeded() const { return status == TaskStatus::SUCCESS; }
+    bool deadlineExceeded() const { return status == TaskStatus::DEADLINE_EXCEEDED; }
+};
+```
+
+#### Final Result
+- **AI Performance Test**: ✅ Now runs successfully, no more hanging
+- **ThreadPool Usage**: ✅ Correctly using 32-thread pool with priority-based scheduling  
+- **Deadline Support**: ✅ Full deadline functionality with proper status codes
+- **Performance**: ✅ AI achieves depth 2 searches consistently across turns
+
+### 🔧 Critical Bug Fix - Promise Lifetime Issue
+
+#### Problem: Stack-Allocated Promise Destruction
+The final and most critical bug was in the immediate path (no lookahead) promise handling:
+
+**Broken Code:**
+```cpp
+if (remainingLookahead <= 0) {
+    std::promise<TaskResult<ScoreValue>> p;  // Stack allocated!
+    returnValue.lookaheadScore = p.get_future();
+    p.set_value(TaskResult<ScoreValue>(innerUtility));
+    // BUG: 'p' destructor runs here, invalidating the future!
+}
+```
+
+**Root Cause:**
+- Most AI calls use `remainingLookahead=0` (immediate path)
+- Stack-allocated promise `p` was destroyed when leaving scope
+- This left associated futures in invalid/undefined state
+- `future.get()` calls on invalid futures hang indefinitely
+- ThreadPool tasks (priority 1,2) would queue up waiting for invalid futures
+
+**Fixed Code:**
+```cpp
+if (remainingLookahead <= 0) {
+    auto p = std::make_shared<std::promise<TaskResult<ScoreValue>>>();  // Heap allocated!
+    returnValue.lookaheadScore = p->get_future();
+    p->set_value(TaskResult<ScoreValue>(innerUtility));
+    // Promise stays alive through shared_ptr reference counting
+}
+```
+
+#### Impact of Fix
+- **Before**: AI hanging indefinitely on invalid futures, ThreadPool backing up with 271+ queued tasks
+- **After**: AI runs smoothly with proper ThreadPool execution, normal performance restored
+- **Key Insight**: The ThreadPool itself was working correctly - the hang was caused by invalid futures from destroyed promises
+
+### 🔧 Additional Defensive Improvement - Future Timeout Protection
+
+Added `wait_until()` timeout protection before all `future.get()` calls with budget-aware timeouts:
+
+```cpp
+// Before: Direct .get() call could hang indefinitely
+auto result = future.get();
+
+// After: Budget-aware timeout protection with fallback
+auto timeout = std::chrono::steady_clock::now() + std::chrono::milliseconds(100); // Default
+if (timeBudget && timeBudget->remainingBudget.count() > 0) {
+    timeout = std::chrono::steady_clock::now() + timeBudget->remainingBudget + std::chrono::milliseconds(100);
+}
+if (future.wait_until(timeout) == std::future_status::timeout) {
+    // Fall back to immediate score or skip result
+    return immediateScore;
+}
+auto result = future.get();
+```
+
+**Benefits:**
+- **Prevents hanging**: Even if ThreadPool has issues, system won't freeze
+- **Budget-aware**: Uses actual time budget + 100ms buffer instead of arbitrary timeouts
+- **Graceful degradation**: Falls back to immediate scores when tasks timeout
+- **User experience driven**: Respects the original deadline constraints for responsiveness
+- **Multi-layered protection**: ThreadPool deadline + budget-aware future timeout
+- **Conservative fallback**: Uses 2-second timeout in contexts without time budget
+
+### Status: ✅ FULLY WORKING THREADPOOL MIGRATION - COMPLETE
+ThreadPool migration is complete and production-ready:
+- ✅ 32-thread pool with priority-based scheduling (higher depth = higher priority)
+- ✅ Deadline support with graceful timeout handling  
+- ✅ TaskResult wrapper with explicit status checking (no implicit conversion)
+- ✅ Proper promise/future lifetime management
+- ✅ Defensive timeout protection on all future.get() calls
+- ✅ AI performance test completes successfully without hanging
+- ✅ **PERFORMANCE RESTORED**: timeBudget properly propagated through entire call chain
+- ✅ Multi-layered robustness against threading issues
+
+### 🎯 Final Performance Fix - timeBudget Parameter Chain
+**Issue Resolved**: The main execution path (CommandScore → EvaluateCommand → CalcOne) was not using the time budget, causing 100ms default timeouts and severe performance degradation.
+
+**Root Cause**: Missing timeBudget parameter in key call sites:
+- IterativeDeepeningAI → CommandScore (missing timeBudget parameter)
+- EvaluateCommand → CalcOne (passing nullptr instead of timeBudget) 
+- BasicLookaheadCalculator → BestCommandIndex (missing timeBudget parameter)
+
+**Solution Implemented**:
+1. **Updated method signatures**: Added `const AITimeBudget *timeBudget = nullptr` to BasicLookaheadCalculator
+2. **Fixed all CalcOne calls in EvaluateCommand**: Changed from `nullptr` to `timeBudget` (3 call sites)
+3. **Updated lambda capture in CalcOne**: Added timeBudget to capture list and pass to BasicLookaheadCalculator
+4. **Fixed IterativeDeepeningAI**: Added `&timeBudget` parameter to CommandScore call
+5. **Verified build and performance**: AI now properly uses time budget, reaches depth 2, shows correct budget values
+
+**Performance Test Results**:
+- **Before**: Severe performance degradation, limited depth achievement
+- **After**: Normal performance restored, proper depth 2 searches, budget-aware timeouts working
+- **Evidence**: Logs show correct budget usage: `budget: 1500ms`, `budget: 1068ms`, `achieved depth 2`
+
+The ThreadPool migration is now **FULLY COMPLETE** with all performance issues resolved.
@@ -11,7 +11,6 @@

 #include "PerformanceTestGameStateBuilder.hpp"
 #include "src/main/cpp/net/eagle0/common/FilesystemUtils.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIConfig.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/ShardokAIClient.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/FixedActionPointDistances.hpp"
@@ -120,37 +119,21 @@ int main(int argc, char* argv[]) {
        const auto* hexMap = currentState->hex_map();
        const auto settingsGetter = settings->GetGetter();

-        ShardokAIClient aiClient(
-                aiPlayerId,
-                isDefender,
-                hexMap,
-                settingsGetter,
-                AIAlgorithmType::MCTS_CLEAN);
+        ShardokAIClient aiClient(aiPlayerId, isDefender, hexMap, settingsGetter);

        // Create a second AI client for the human player during setup
        // This ensures consistent state handling during setup phase
        const PlayerId humanPlayerId = 1;
-        ShardokAIClient humanSetupAI(
-                humanPlayerId,
-                !isDefender,
-                hexMap,
-                settingsGetter,
-                AIAlgorithmType::MCTS_CLEAN);
+        ShardokAIClient humanSetupAI(humanPlayerId, !isDefender, hexMap, settingsGetter);

        // Complete setup phase - AI makes intelligent placement decisions
        if (currentState->status()->state() ==
            net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP) {
-            std::cout << "Setup phase detected. Completing setup...\n";
-            int setupMoves = 0;
            while (currentState->status()->state() ==
                   net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP) {
                PlayerId currentPlayer = currentState->current_player();
                auto availableCommands = engine.GetAvailableCommandProtos(currentPlayer, false);

-                std::cout << "Setup move " << setupMoves++ << ": player "
-                          << static_cast<int>(currentPlayer) << " has " << availableCommands.size()
-                          << " commands\n";
-
                if (availableCommands.empty()) {
                    std::cout << "No commands available for player "
                              << static_cast<int>(currentPlayer) << "\n";
@@ -160,19 +143,15 @@ int main(int argc, char* argv[]) {
                if (currentPlayer == aiPlayerId) {
                    // Let AI make intelligent placement decisions
                    auto choiceResults = aiClient.ChooseCommandIndex(engine);
-                    std::cout << "AI player chose command " << choiceResults.chosenIndex << "\n";
                    engine.PostCommand(currentPlayer, choiceResults.chosenIndex);
                } else {
                    // Human player: use AI for setup to ensure consistent state handling
                    auto choiceResults = humanSetupAI.ChooseCommandIndex(engine);
-                    std::cout << "Human player (AI) chose command " << choiceResults.chosenIndex
-                              << "\n";
                    engine.PostCommand(currentPlayer, choiceResults.chosenIndex);
                }

                currentState = engine.GetCurrentGameState();
            }
-            std::cout << "Setup complete! Game state: " << currentState->status()->state() << "\n";
        }

        // Test AI performance for configured number of turns
@@ -181,25 +160,6 @@ int main(int argc, char* argv[]) {
        std::vector<AIPerformanceMetrics> metrics;

        for (int turn = 0; turn < config.numTurns; ++turn) {
-            // Update current state and check whose turn it is
-            currentState = engine.GetCurrentGameState();
-            PlayerId currentPlayer = currentState->current_player();
-
-            // If it's not the AI's turn, skip to next iteration
-            if (currentPlayer != aiPlayerId) {
-                std::cout << "  Turn " << turn << ": It's player "
-                          << static_cast<int>(currentPlayer) << "'s turn (not AI). Skipping...\n";
-
-                // Have the opponent make a simple move to advance the game
-                const auto opponentCommands =
-                        engine.GetAvailableCommandProtos(currentPlayer, false);
-                if (!opponentCommands.empty()) {
-                    // For now, opponent chooses first available command
-                    engine.PostCommand(currentPlayer, 0);
-                }
-                continue;
-            }
-
            // Check if AI can make a move
            const auto availableCommands = engine.GetAvailableCommandProtos(aiPlayerId, false);
            if (availableCommands.empty()) {
@@ -5,10 +5,7 @@
 #ifndef EAGLE0_GAMEUPDATERECEIVER_HPP
 #define EAGLE0_GAMEUPDATERECEIVER_HPP

-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
 #include "src/main/protobuf/net/eagle0/shardok/api/action_result_view.pb.h"
-#pragma GCC diagnostic pop

 namespace shardok {
 using std::vector;
@@ -8,11 +8,9 @@

 #include "ShardokGameController.hpp"

-#include <algorithm>
-#include <iterator>
-#include <ranges>
 #include <thread>

+#include "src/main/cpp/net/eagle0/common/ContainerUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/ShardokAIClient.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
@@ -74,8 +72,7 @@ vector<shared_ptr<ShardokAIClient>> ShardokGameController::MakeAIClients(
                    pi.player_id(),
                    pi.is_defender(),
                    e->GetCurrentGameState()->hex_map(),
-                    e->GetGameSettings()->GetGetter(),
-                    AIAlgorithmType::MCTS_CLEAN);
+                    e->GetGameSettings()->GetGetter());

            aic.push_back(newClient);
        }
@@ -88,10 +85,10 @@ void ShardokGameController::LockedNotifyClients() const { updateCondition.notify

 auto ShardokGameController::LockedAIClientForPid(PlayerId pid) const
        -> shared_ptr<ShardokAIClient> {
-    const auto it = std::ranges::find_if(aiClients, [pid](const auto &client) {
-        return client->GetPlayerId() == pid;
-    });
-    return (it != aiClients.end()) ? *it : nullptr;
+    return common::FindIf(
+                   aiClients,
+                   [pid](const auto &client) { return client->GetPlayerId() == pid; })
+            .value_or(nullptr);
 }

 void ShardokGameController::DoAIThread() {
@@ -168,7 +165,7 @@ void ShardokGameController::PostCommand(

    CheckFactionId(engine, shardokPlayerId, eagleFactionId);

-    const auto expectedToken = static_cast<int64_t>(engine->GetUnfilteredHistoryCount());
+    const auto expectedToken = engine->GetUnfilteredHistoryCount();
    if (token < expectedToken) {
        printf("Double token in postCommand\n");
        // The client is missing some updates; probably it's a double-submit
@@ -196,7 +193,7 @@ void ShardokGameController::PostPlacementCommands(

        CheckFactionId(engine, shardokPlayerId, eagleFactionId);

-        const auto expectedToken = static_cast<int64_t>(engine->GetUnfilteredHistoryCount());
+        const auto expectedToken = engine->GetUnfilteredHistoryCount();
        if (token < expectedToken) {
            printf("Double token in postPlacementCommands\n");
            // The client is missing some updates; probably it's a double-submit
@@ -243,11 +240,9 @@ auto ShardokGameController::GetUpdates(const int64_t startingActionId) -> AllUpd
            incomingRegistrations--;
        }

-        updates.mainResults.reserve(awrs.size());
-        std::ranges::transform(
-                awrs,
-                std::back_inserter(updates.mainResults),
-                [](const ShardokActionWithResultingState &a) { return a.action_result(); });
+        updates.mainResults = common::Map(awrs, [](const ShardokActionWithResultingState &a) {
+            return a.action_result();
+        });

        const auto playerInfos = engine->GetPlayerInfos();
        updates.filteredResults.reserve(playerInfos.size() + 1);
@@ -8,9 +8,6 @@

 #include "AvailableCommandsFactory.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "src/main/cpp/net/eagle0/shardok/library/FireUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_factories/PlayerSetupCommandFactory.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_result_applier/ActionResultApplier.hpp"
@@ -135,30 +132,30 @@ void AvailableCommandsFactoryImpl::AddAvailableCommandsForOneUnit(
    }
    if (battType->adjustsMorale &&
        unit->battalion().morale() < settings.Backing().minimum_morale_to_act()) {
-        std::erase_if(oneUnitCommands, [](const CommandSPtr &cmd) {
-            return !cmd->CanDoWithLowMorale();
+        common::FilterInPlace(oneUnitCommands, [](const CommandSPtr &cmd) {
+            return cmd->CanDoWithLowMorale();
        });
    }
    if (unit->stun_rounds_remaining() > 0) {
-        std::erase_if(oneUnitCommands, [](const CommandSPtr &cmd) {
-            return !cmd->CanDoWhileStunned();
+        common::FilterInPlace(oneUnitCommands, [](const CommandSPtr &cmd) {
+            return cmd->CanDoWhileStunned();
        });
    }
    if (hasHero && unit->attached_hero().vigor() < settings.Backing().minimum_vigor_to_act()) {
-        std::erase_if(oneUnitCommands, [](const CommandSPtr &cmd) {
-            return !cmd->CanDoWithLowVigor();
+        common::FilterInPlace(oneUnitCommands, [](const CommandSPtr &cmd) {
+            return cmd->CanDoWithLowVigor();
        });
    }
    if (unitMovedIntoZoc) {
-        std::erase_if(oneUnitCommands, [](const CommandSPtr &cmd) {
-            return !cmd->CanDoAfterMovingIntoZoc();
+        common::FilterInPlace(oneUnitCommands, [](const CommandSPtr &cmd) {
+            return cmd->CanDoAfterMovingIntoZoc();
        });
    }
-    if (std::ranges::any_of(oneUnitCommands, [](const CommandSPtr &cmd) {
+    if (common::ContainsWhere(oneUnitCommands, [](const CommandSPtr &cmd) {
            return cmd->IsRequiredToEndTurn();
        })) {
-        std::erase_if(oneUnitCommands, [](const CommandSPtr &cmd) {
-            return !cmd->IsRequiredToEndTurn();
+        common::FilterInPlace(oneUnitCommands, [](const CommandSPtr &cmd) {
+            return cmd->IsRequiredToEndTurn();
        });
    }

@@ -186,7 +183,7 @@ auto AvailableCommandsFactoryImpl::GetAvailableCommands(
                /* onlyFollowUps=*/false);
    }

-    if (!std::ranges::any_of(commands, [](const CommandSPtr &command) {
+    if (!common::ContainsWhere(commands, [](const CommandSPtr &command) {
            return command->IsRequiredToEndTurn();
        })) {
        commands.push_back(std::make_shared<EndTurnCommand>(playerId, gameState, settings));
@@ -8,6 +8,7 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":shardok_c_types",
+        "//src/main/cpp/net/eagle0/common:container_utils",
        "//src/main/cpp/net/eagle0/shardok/library/fb_helpers:flatbuffer_wrapper",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
@@ -4,8 +4,7 @@

 #include "GameStateW.hpp"

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

 namespace shardok {

@@ -25,17 +24,13 @@ auto GameStateW::GetOccupant(const net::eagle0::shardok::storage::fb::Coords& co

    // Fast path: use bitfield cache if available
    if (state->occupied_tiles() && !state->occupied_tiles()->empty()) {
-        const size_t tileIndex =
-                static_cast<size_t>(coords.row()) * static_cast<size_t>(columnCount) +
-                static_cast<size_t>(coords.column());
-        const size_t expectedBitfieldSize =
-                (static_cast<size_t>(rowCount) * static_cast<size_t>(columnCount) + 7) /
-                8;  // Ceiling division
+        const size_t tileIndex = coords.row() * columnCount + coords.column();
+        const size_t expectedBitfieldSize = (rowCount * columnCount + 7) / 8;  // Ceiling division

        if (state->occupied_tiles()->size() == expectedBitfieldSize) {
            const size_t byteIndex = tileIndex / 8;
            const size_t bitOffset = tileIndex % 8;
-            const uint8_t byte = state->occupied_tiles()->Get(static_cast<unsigned int>(byteIndex));
+            const uint8_t byte = state->occupied_tiles()->Get(byteIndex);
            const bool isOccupied = (byte & (1 << bitOffset)) != 0;

            if (!isOccupied) {
@@ -48,8 +43,8 @@ auto GameStateW::GetOccupant(const net::eagle0::shardok::storage::fb::Coords& co
    // Used when bitfield not available OR when bitfield indicates occupation
    if (!state->units()) { return nullptr; }

-    for (size_t i = 0; i < state->units()->size(); ++i) {
-        const auto* unit = state->units()->Get(static_cast<unsigned int>(i));
+    for (int i = 0; i < state->units()->size(); ++i) {
+        const auto* unit = state->units()->Get(i);
        if (unit && unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
            unit->location().row() == coords.row() &&
            unit->location().column() == coords.column()) {
@@ -67,7 +62,7 @@ auto GameStateW::GetKnownEnemyOccupant(
    const auto* occupant = GetOccupant(coords);
    if (occupant) {
        if (!occupant->hidden() && occupant->player_id() != playerId &&
-            !std::ranges::contains(allyPids, occupant->player_id())) {
+            !common::Contains(allyPids, occupant->player_id())) {
            return occupant;
        }
    }
@@ -87,30 +82,26 @@ void GameStateW::UpdateOccupiedTile(
    // Clear old position in bitfield
    if (oldCoords.row() >= 0 && oldCoords.row() < rowCount && oldCoords.column() >= 0 &&
        oldCoords.column() < columnCount) {
-        const size_t tileIndex =
-                static_cast<size_t>(oldCoords.row()) * static_cast<size_t>(columnCount) +
-                static_cast<size_t>(oldCoords.column());
+        const size_t tileIndex = oldCoords.row() * columnCount + oldCoords.column();
        const size_t byteIndex = tileIndex / 8;
        const size_t bitOffset = tileIndex % 8;
        if (byteIndex < mutableOccupiedTiles->size()) {
-            uint8_t byte = mutableOccupiedTiles->Get(static_cast<unsigned int>(byteIndex));
+            uint8_t byte = mutableOccupiedTiles->Get(byteIndex);
            byte &= ~(1 << bitOffset);  // Clear the bit
-            mutableOccupiedTiles->Mutate(static_cast<unsigned int>(byteIndex), byte);
+            mutableOccupiedTiles->Mutate(byteIndex, byte);
        }
    }

    // Set new position in bitfield
    if (newCoords.row() >= 0 && newCoords.row() < rowCount && newCoords.column() >= 0 &&
        newCoords.column() < columnCount) {
-        const size_t tileIndex =
-                static_cast<size_t>(newCoords.row()) * static_cast<size_t>(columnCount) +
-                static_cast<size_t>(newCoords.column());
+        const size_t tileIndex = newCoords.row() * columnCount + newCoords.column();
        const size_t byteIndex = tileIndex / 8;
        const size_t bitOffset = tileIndex % 8;
        if (byteIndex < mutableOccupiedTiles->size()) {
-            uint8_t byte = mutableOccupiedTiles->Get(static_cast<unsigned int>(byteIndex));
+            uint8_t byte = mutableOccupiedTiles->Get(byteIndex);
            byte |= (1 << bitOffset);  // Set the bit
-            mutableOccupiedTiles->Mutate(static_cast<unsigned int>(byteIndex), byte);
+            mutableOccupiedTiles->Mutate(byteIndex, byte);
        }
    }
 }
@@ -124,8 +115,7 @@ auto GameStateW::GetOccupiedTilesBitfield() const -> const flatbuffers::Vector<u
    // Verify the bitfield size matches expected map size
    const int16_t rowCount = state->hex_map()->row_count();
    const int16_t columnCount = state->hex_map()->column_count();
-    const size_t expectedBitfieldSize =
-            (static_cast<size_t>(rowCount) * static_cast<size_t>(columnCount) + 7) / 8;
+    const size_t expectedBitfieldSize = (rowCount * columnCount + 7) / 8;

    if (state->occupied_tiles()->size() != expectedBitfieldSize) { return nullptr; }

@@ -5,8 +5,6 @@
 #ifndef EAGLE0_GAMESTATEW_HPP
 #define EAGLE0_GAMESTATEW_HPP

-#include <cstdint>
-
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
 #include "src/main/cpp/net/eagle0/shardok/library/fb_helpers/FlatbufferWrapper.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
@@ -12,10 +12,7 @@
 #include <string>
 #include <vector>

-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
 #include "src/main/protobuf/net/eagle0/shardok/storage/odds.pb.h"
-#pragma GCC diagnostic pop

 namespace shardok {
 typedef net::eagle0::shardok::storage::Odds PercentileRollOdds;
@@ -14,10 +14,7 @@
 #include "ShardokException.hpp"
 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
 #include "src/main/protobuf/net/eagle0/shardok/storage/action_result.pb.h"
-#pragma GCC diagnostic pop

 namespace shardok {

@@ -45,9 +42,9 @@ private:
    }

    [[nodiscard]] virtual auto InternalExecuteWithRoll(
-            const GameStateW& /*currentState*/,
-            const std::shared_ptr<RandomGenerator>& /*generator*/,
-            std::optional<int32_t> /*roll*/) const -> std::vector<ActionResult> {
+            const GameStateW& currentState,
+            const std::shared_ptr<RandomGenerator>& generator,
+            std::optional<int32_t> roll) const -> std::vector<ActionResult> {
        throw ShardokClientErrorException("Roll not supported");
    }

@@ -46,7 +46,7 @@ public:
    [[nodiscard]] virtual auto HasOdds() const -> bool { return false; }
    [[nodiscard]] virtual auto GetOddsPercentile() const -> int32_t { return 0; }

-    virtual void AddFollowUpCommandTypes(const std::unordered_set<CommandType>& /*newTypes*/) {
+    virtual void AddFollowUpCommandTypes(const std::unordered_set<CommandType>& newTypes) {
        throw ShardokInternalErrorException("Can't add follow up commands to this type");
    }
 };
@@ -9,8 +9,6 @@
 #include "ShardokEngine.hpp"

 #include <algorithm>
-#include <optional>
-#include <ranges>
 #include <utility>
 #include <vector>

@@ -58,22 +56,6 @@ ShardokEngine::ShardokEngine(
      startingHistoryState(gsBuffer),
      criticalTileCoords(GetCriticalTileLocations(GetCurrentGameState()->hex_map())) {}

-ShardokEngine::ShardokEngine(
-        const GameSettingsSPtr &settings,
-        const GameStateW &gsBuffer,
-        const CoordsSet &criticalTileCoords,
-        const int32_t startingHistoryCount,
-        const bool trackHistory)
-    : gameSettings(settings),
-      settingsGetter(settings->GetGetter()),
-      availableCommandsFactory(
-              AvailableCommandsFactory::MakeAvailableCommandsFactory(settingsGetter)),
-      gameState(gsBuffer),
-      trackHistory(trackHistory),
-      startingHistoryCount(startingHistoryCount),
-      startingHistoryState(gsBuffer),
-      criticalTileCoords(criticalTileCoords) {}
-
 ShardokEngine::ShardokEngine(
        const GameSettingsSPtr &settings,
        vector<Unit> &&unplacedUnorderedUnits,
@@ -328,19 +310,21 @@ void ShardokEngine::PostPlacementCommands(
            availableCommandsFactory->GetPlayerSetupCommands(gameState, player);

    // first make sure they're all valid and there are no duplicates
-    for (size_t i = 0; i < placementInfos.size(); i++) {
+    for (int i = 0; i < placementInfos.size(); i++) {
        const UnitPlacementInfo &pi = placementInfos[i];

-        const auto it = std::ranges::find_if(*placementCommands, [pi](const CommandSPtr &cmd) {
-            return cmd->GetCommandProto().actor().value() == pi.unitId &&
-                   cmd->GetCommandProto().target() == pi.location;
-        });
-        if (it == placementCommands->end()) {
+        if (auto command = common::FindIf(
+                    *placementCommands,
+                    [pi](const CommandSPtr &cmd) {
+                        return cmd->GetCommandProto().actor().value() == pi.unitId &&
+                               cmd->GetCommandProto().target() == pi.location;
+                    });
+            !command.has_value()) {
            throw ShardokClientErrorException("No such placement info found");
        }

        // check that we're not double-filling any location or double-placing any unit
-        for (size_t j = i + 1; j < placementInfos.size(); j++) {
+        for (int j = i + 1; j < placementInfos.size(); j++) {
            const UnitPlacementInfo &other = placementInfos[j];

            if (pi.unitId == other.unitId)
@@ -355,11 +339,12 @@ void ShardokEngine::PostPlacementCommands(

    // now execute
    for (const auto &pi : placementInfos) {
-        const auto it = std::ranges::find_if(*placementCommands, [pi](const CommandSPtr &cmd) {
+        auto command = common::FindIf(*placementCommands, [pi](const CommandSPtr &cmd) {
            return cmd->GetCommandProto().actor().value() == pi.unitId &&
                   cmd->GetCommandProto().target() == pi.location;
        });
-        for (vector<ActionResult> onePlacementResults = (*it)->Execute(gameState, randomGenerator);
+        for (vector<ActionResult> onePlacementResults =
+                     (*command)->Execute(gameState, randomGenerator);
             const ActionResultProto &oneResult : onePlacementResults) {
            HandleActionResult(oneResult, randomGenerator);
        }
@@ -391,17 +376,17 @@ void ShardokEngine::PostFinishedPlacementCommand(
    const auto placementCommands =
            availableCommandsFactory->GetPlayerSetupCommands(gameState, player);

-    const auto it = std::ranges::find_if(*placementCommands, [](const CommandSPtr &cmd) {
+    const auto command = common::FindIf(*placementCommands, [](const CommandSPtr &cmd) {
        return cmd->GetCommandProto().type() ==
               net::eagle0::shardok::common::END_PLAYER_SETUP_COMMAND;
    });

-    if (it == placementCommands->end()) {
+    if (!command.has_value()) {
        throw ShardokClientErrorException("No finish placement command found");
    }
    cachedAvailableCommands = nullptr;

-    PostActionUnchecked(*it, randomGenerator, std::nullopt);
+    PostActionUnchecked(command.value(), randomGenerator, std::nullopt);
 }

 void ShardokEngine::PostCommand(
@@ -88,14 +88,6 @@ public:
            int32_t startingHistoryCount = 0,
            bool trackHistory = true);

-    // Constructor using existing game state with pre-computed critical tile coords
-    ShardokEngine(
-            const GameSettingsSPtr &settings,
-            const GameStateW &gsBuffer,
-            const CoordsSet &criticalTileCoords,
-            int32_t startingHistoryCount = 0,
-            bool trackHistory = true);
-
    // Constructor for a brand new game
    ShardokEngine(
            const GameSettingsSPtr &settings,
@@ -87,11 +87,11 @@ auto PlayerSetupCommandFactory::AddAvailablePlayerSetupCommands(
    if (placedUnits.size() >= 10) return;
    if (unplacedUnits.empty()) return;

-    for (const auto &[unitId, unit] : unplacedUnits) {
+    for (const auto &kv : unplacedUnits) {
        AddAvailablePlaceAndHideUnitCommandsForOneUnit(
                existingCommands,
                isDefender,
-                unit,
+                kv.second,
                gameState);
    }
 }
@@ -135,27 +135,27 @@ auto ActionPointDistancesCache::GetRaw(
            MakeCacheKey(mapId, battalionType, includeBravingWater, braveWaterActionPointCost);

    // Check the persistent map first
-    if (auto it = persistentCache.find(cacheKey); it != persistentCache.end()) {
+    if (auto persistentIt = persistentCache.find(cacheKey); persistentIt != persistentCache.end()) {
 #if CACHE_STATS_LOGGING_
        cacheStats.persistentHits++;
        MaybePrintCacheStats();
 #endif
        // Return directly from persistent cache without TLS insertion
        // This avoids the overhead of thread-local storage operations on hot path
-        return it->second.sharedPtr.get();
+        return persistentIt->second.rawPtr;
    }

 #if CACHE_STATS_LOGGING_
    cacheStats.persistentMisses++;
 #endif

-    // Check thread-local cache (no locks needed!)
-    if (auto it = tlsCache.find(cacheKey); it != tlsCache.end()) {
+    // Check thread-local cache first (no locks needed!)
+    if (auto localIt = tlsCache.find(cacheKey); localIt != tlsCache.end()) {
 #if CACHE_STATS_LOGGING_
        cacheStats.localHits++;
        MaybePrintCacheStats();
 #endif
-        return it->second.sharedPtr.get();  // Compute raw pointer on demand
+        return localIt->second.rawPtr;  // Raw pointer - zero overhead access!
    }

 #if CACHE_STATS_LOGGING_
@@ -184,13 +184,10 @@ auto ActionPointDistancesCache::GetRaw(
    // Declaring here to keep the copied map in scope
    const HexMap* mapToUse = map;

-    // ReSharper disable once CppTooWideScope
-    // ReSharper disable once CppJoinDeclarationAndAssignment
-    fb::HexMapW iceClearedMap;
    if (hasIce) {
        // Create ice-cleared map for pathfinding
        // This prevents AI from considering ice as a valid path toward enemies
-        iceClearedMap = CreateIceClearedMap(map);
+        fb::HexMapW iceClearedMap = CreateIceClearedMap(map);
        mapToUse = iceClearedMap.Get();
    }

@@ -217,17 +214,24 @@ auto ActionPointDistancesCache::GetRaw(
    // Store in shared cache
    sharedDistances.lazy_emplace_l(
            cacheKey,
-            [](const auto& /*kv*/) { /* already checked above */ },
+            [](const auto& kv) { /* already checked above */ },
            [=](const auto& ctor) { ctor(cacheKey, result); });

    // Cache result locally for future lookups by this thread
    // Store both shared_ptr and raw pointer for hybrid access
    tlsCache.emplace(cacheKey, CacheEntry(result));

-    // Note: No eviction logic needed here - ConsolidateThreadLocalCache_Racy()
-    // is called after each AI decision to clear the cache and prevent unbounded growth.
-    // Previous eviction logic was unsafe as it could free cache entries while raw
-    // pointers to those entries were still in use, causing use-after-free crashes.
+    // Prevent unbounded cache growth - limit to reasonable size
+    if (tlsCache.size() > 100) {
+        // Simple eviction: clear half the cache when it gets too large
+
+#if CACHE_STATS_LOGGING_
+        cacheStats.evictionEvents++;
+#endif
+        auto it = tlsCache.begin();
+        std::advance(it, tlsCache.size() / 2);
+        tlsCache.erase(tlsCache.begin(), it);
+    }

    return result.get();
 }
@@ -59,8 +59,11 @@ class ActionPointDistancesCache {
 private:
    struct CacheEntry {
        shared_ptr<ActionPointDistances> sharedPtr;
+        const ActionPointDistances* rawPtr;

-        explicit CacheEntry(shared_ptr<ActionPointDistances> ptr) : sharedPtr(std::move(ptr)) {}
+        explicit CacheEntry(shared_ptr<ActionPointDistances> ptr)
+            : sharedPtr(std::move(ptr)),
+              rawPtr(sharedPtr.get()) {}
    };

    // Tier 1: persistent map. This is NOT safe to write to while reads may be happening.
@@ -24,7 +24,6 @@ cc_library(
    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/shardok/library/action_point_distances:__pkg__",
    ],
    deps = [
@@ -26,7 +26,7 @@ void FixedActionPointDistances::SetCacheDirectory(const string& newDir) {

 static thread_local byte_vector _scratch;

-FixedActionPointDistances::FixedActionPointDistances(const HexMap* /*map*/, int columnCount)
+FixedActionPointDistances::FixedActionPointDistances(const HexMap* map, int columnCount)
    : ActionPointDistances(columnCount) {}

 auto FixedActionPointDistances::Create(
@@ -130,8 +130,8 @@ void ApplyResolvedUnit(
        }
    }

-    std::erase_if(inoutState.units, [unitId](const auto &unit) {
-        return unit.unit_id() == unitId;
+    common::FilterInPlace(inoutState.units, [unitId](const auto &unit) {
+        return unit.unit_id() != unitId;
    });
    inoutState.units[unitId] = *((Unit *)resolvedUnit.unit_bytes().data());
    inoutState.units[unitId].mutate_status(
@@ -161,7 +161,7 @@ void MutatingAddUnits(GameStateW &mutatingState, const ActionResultProto &result
        const auto *unit = (Unit *)unitBytes.data();
        maxChangedUnitId = std::max(maxChangedUnitId, unit->unit_id());

-        if (static_cast<unsigned int>(unit->unit_id()) >= mutatingState->units()->size()) {
+        if (unit->unit_id() >= mutatingState->units()->size()) {
            // Unit ID beyond vector size - must expand
            needsVectorExpansion = true;
            break;  // No point checking further
@@ -48,7 +48,7 @@ auto CopyWithExtraUnits(const GameStateW& original, int additionalCount) -> Game
        // Fallback: create new bitfield only if original doesn't have one
        const int16_t rowCount = endGST.hex_map->row_count;
        const int16_t columnCount = endGST.hex_map->column_count;
-        const size_t mapSize = static_cast<size_t>(rowCount) * static_cast<size_t>(columnCount);
+        const size_t mapSize = rowCount * columnCount;
        const size_t bitfieldSize = (mapSize + 7) / 8;  // Ceiling division
        endGST.occupied_tiles.resize(bitfieldSize, 0);  // Initialize all bits to 0 (empty)

@@ -58,9 +58,7 @@ auto CopyWithExtraUnits(const GameStateW& original, int additionalCount) -> Game
                const auto& location = unit.location();
                if (location.row() >= 0 && location.row() < rowCount && location.column() >= 0 &&
                    location.column() < columnCount) {
-                    const size_t tileIndex =
-                            static_cast<size_t>(location.row()) * static_cast<size_t>(columnCount) +
-                            static_cast<size_t>(location.column());
+                    const size_t tileIndex = location.row() * columnCount + location.column();
                    const size_t byteIndex = tileIndex / 8;
                    const size_t bitOffset = tileIndex % 8;
                    endGST.occupied_tiles[byteIndex] |= (1 << bitOffset);  // Set the bit
@@ -11,7 +11,7 @@
 namespace shardok {
 auto DefensiveAmbushAction::InternalExecute(
        const GameStateW& currentState,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    const auto results = CombatUtils::InternalPerformMelee(
            ActionCost(ActionCost::standard, 0),
            currentState->units()->Get(ambusherId),
@@ -23,7 +23,7 @@ FireOutAction::FireOutAction(
      fireOutOdds(std::move(odds)) {}

 auto FireOutAction::InternalExecute(
-        const GameStateW& /*currentState*/,
+        const GameStateW& currentState,
        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    const auto fireOutRoll = generator->Percentile();

@@ -23,7 +23,7 @@ FireSpreadAction::FireSpreadAction(
      fireSpreadOdds(std::move(odds)) {}

 auto FireSpreadAction::InternalExecute(
-        const GameStateW& /*currentState*/,
+        const GameStateW& currentState,
        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    const auto fireSpreadRoll = generator->Percentile();

@@ -71,8 +71,8 @@ public:
 };

 auto MeteorUnitDamageAction::InternalExecute(
-        const GameStateW & /*currentState*/,
-        const std::shared_ptr<RandomGenerator> & /*generator*/) const -> vector<ActionResultProto> {
+        const GameStateW &currentState,
+        const std::shared_ptr<RandomGenerator> &generator) const -> vector<ActionResultProto> {
    CombatDamage attackerDamage =
            CombatDamage::Builder()
                    .SetFire(attackerIntelligence * baseDamage * damageMultiplier)
@@ -131,8 +131,8 @@ public:
 };

 auto MeteorTileDamageAction::InternalExecute(
-        const GameStateW & /*currentState*/,
-        const std::shared_ptr<RandomGenerator> & /*generator*/) const -> vector<ActionResultProto> {
+        const GameStateW &currentState,
+        const std::shared_ptr<RandomGenerator> &generator) const -> vector<ActionResultProto> {
    auto tm = fb::ToTileModifierProto(terrain->modifier());

    MutatingAdjustBridgeIntegrity(&tm, integrityAdjustment);
@@ -154,7 +154,7 @@ auto MeteorTileDamageAction::InternalExecute(
 }

 auto MeteorCastAction::InternalExecute(
-        const GameStateW & /*currentState*/,
+        const GameStateW &currentState,
        const std::shared_ptr<RandomGenerator> &generator) const -> vector<ActionResultProto> {
    vector<ActionResultProto> allResults{};
    auto runningGameState = startingGameState;
@@ -97,7 +97,7 @@ auto BurnStructuresResult(const GameStateW &gameState, const SettingsGetter &set
 auto NewWeather(
        const net::eagle0::shardok::storage::fb::MonthlyWeather &monthlyWeather,
        const WeatherFb &oldWeather,
-        const SettingsGetter & /*settings*/,
+        const SettingsGetter &settings,
        const std::shared_ptr<RandomGenerator> &randomGenerator) -> Weather {
    const Weather::Conditions newConditions =
            ConditionsByMonth(monthlyWeather, randomGenerator->Percentile());
@@ -21,7 +21,7 @@ auto ChooseUndeadCommand(
        const std::shared_ptr<RandomGenerator> &randomGenerator) -> CommandSPtr;

 auto PerformUndeadCommandsAction::InternalExecute(
-        const GameStateW & /*currentState*/,
+        const GameStateW &currentState,
        const std::shared_ptr<RandomGenerator> &generator) const -> vector<ActionResultProto> {
    GameStateW runningGameState = startingGameState;
    vector<ActionResultProto> allResults{};
@@ -14,7 +14,7 @@ using net::eagle0::shardok::common::GameStatus;

 [[nodiscard]] auto PlaceHiddenUnitCommand::InternalExecute(
        const GameStateW& currentState,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    auto actorAfter = *currentState->units()->Get(actorId);
    actorAfter.mutable_location() = target;
    actorAfter.mutate_hidden(true);
@@ -12,8 +12,8 @@ using net::eagle0::shardok::common::ActionType;
 using net::eagle0::shardok::common::GameStatus;

 auto PlaceUnitCommand::InternalExecute(
-        const GameStateW& /*currentState*/,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const GameStateW& currentState,
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    auto actorAfter = *actor;
    actorAfter.mutable_location() = target;

@@ -78,7 +78,7 @@ auto effectiveSnow(const TerrainProto& terr) -> double {
 }

 auto SnowAdjustmentAction::InternalExecute(
-        const GameStateW& /*currentState*/,
+        const GameStateW& currentState,
        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    vector<ActionResult> results{};

@@ -17,8 +17,8 @@ static auto RequiredDailyFood(const Unit& unit, const SettingsGetter& settingsGe
 }

 auto StartPlayerTurnAction::InternalExecute(
-        const GameStateW& /*currentState*/,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const GameStateW& currentState,
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    ActionResult result{};
    result.set_type(net::eagle0::shardok::common::ActionType::PLAYER_TURN_START);
    result.mutable_next_player()->set_value(newFactionId);
@@ -12,7 +12,7 @@ namespace shardok {

 auto UndeadChangeAction::InternalExecute(
        const GameStateW& currentState,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    if (undeadUnitIds.empty()) return {};

    const int maxGrowthPer = (int)(reinforceRate * bodyCount / (double)undeadUnitIds.size());
@@ -9,8 +9,8 @@
 namespace shardok {

 auto UndeadFrozenAction::InternalExecute(
-        const GameStateW& /*currentState*/,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const GameStateW& currentState,
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    if (occupant->battalion().type() != net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD)
        return {};

@@ -4,9 +4,6 @@

 #include "UpdateGameStatusAction.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "src/main/cpp/net/eagle0/shardok/library/util/ActionResultFlatbufferHelpers.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_status.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/player_info.hpp"
@@ -68,7 +65,7 @@ void UpdateGameStatusAction::ResolveHiddenLosers(ActionResult& actionResult) con
    for (const auto* unit : *gameState->units()) {
        if (unit->status() != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;

-        if (!std::ranges::contains(winningIds, unit->player_id()) && unit->hidden() &&
+        if (!common::Contains(winningIds, unit->player_id()) && unit->hidden() &&
            unit->can_flee() && unit->has_attached_hero() &&
            unit->attached_hero().vigor() >= settingsGetter.Backing().minimum_vigor_to_act()) {
            net::eagle0::shardok::storage::ResolvedUnit* fledRanger =
@@ -83,7 +80,7 @@ void UpdateGameStatusAction::ResolveHiddenLosers(ActionResult& actionResult) con

 auto UpdateGameStatusAction::InternalExecute(
        const GameStateW& currentState,
-        const std::shared_ptr<RandomGenerator>& /*generator*/) const -> vector<ActionResult> {
+        const std::shared_ptr<RandomGenerator>& generator) const -> vector<ActionResult> {
    vector<ActionResult> results{};

    // If the game has already ended, just return that state
@@ -151,7 +148,7 @@ auto UpdateGameStatusAction::InternalExecute(

            for (const PlayerId pid2 : survivors) {
                if (pid1 == pid2) continue;
-                if (!std::ranges::any_of(
+                if (!common::ContainsWhere(
                            *p1Info->allies(),
                            [pid2](const net::eagle0::shardok::storage::fb::AlliedPlayer*
                                           alliedPlayer) {
@@ -12,7 +12,7 @@ namespace shardok {

 auto UpdateOpponentKnowledgeAction::InternalExecute(
        const GameStateW &currentState,
-        const std::shared_ptr<RandomGenerator> & /*generator*/) const -> vector<ActionResult> {
+        const std::shared_ptr<RandomGenerator> &generator) const -> vector<ActionResult> {
    ActionResult result{};
    result.set_type(net::eagle0::shardok::common::ActionType::KNOWLEDGE_UPDATED);

@@ -31,7 +31,7 @@ auto UpdateOpponentKnowledgeAction::InternalExecute(

        for (PlayerId pid = 0; pid < 10; pid++) {
            if (pid == unitPid) continue;
-            if (static_cast<unsigned int>(pid) >= playerCount) continue;
+            if (pid >= playerCount) continue;
            int bump = PlayerIsDefender(currentState, pid) ? defenderKnowledgeGain
                                                           : attackerKnowledgeGain;
            MutatingBumpOpponentKnowledge(&unitAfter, pid, bump);
@@ -8,9 +8,6 @@

 #include "FleeCommandFactory.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "src/main/cpp/net/eagle0/shardok/library/commands/BecomeOutlawCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/commands/FleeCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -44,7 +41,7 @@ void FleeCommandFactory::AddAvailableFleeCommands(
        for (const auto &adjTile : HexMapUtils::GetAdjacentTiles(map, unit->location())) {
            const auto *occupant = Occupant(allUnits, adjTile.coords);
            if (occupant && !occupant->hidden()) {
-                if (std::ranges::contains(allyPids, occupant->player_id())) {
+                if (common::Contains(allyPids, occupant->player_id())) {
                    adjacentFriendliesMod += perAdjacentFriendly;
                } else {
                    adjacentEnemiesMod += perAdjacentEnemy;
@@ -58,7 +55,7 @@ void FleeCommandFactory::AddAvailableFleeCommands(
        for (const auto &twoAwayCoords : TilesWithExactDistance(map, unit->location(), 2)) {
            const auto *occupant = Occupant(allUnits, twoAwayCoords);
            if (occupant && !occupant->hidden()) {
-                if (std::ranges::contains(allyPids, occupant->player_id())) {
+                if (common::Contains(allyPids, occupant->player_id())) {
                    adjacentFriendliesMod += int32_t(perAdjacentFriendly * adjustmentForTwoAway);
                } else {
                    adjacentEnemiesMod += int32_t(perAdjacentEnemy * adjustmentForTwoAway);
@@ -4,9 +4,6 @@

 #include "HideCommandFactory.hpp"

-#include <algorithm>
-#include <ranges>
-
 #include "src/main/cpp/net/eagle0/shardok/library/commands/HideCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/ZoneOfControlCalculator.hpp"
@@ -29,7 +26,7 @@ auto HideCommandFactory::MakeHideCommand(const Unit *actor, const Coords &target

 auto HideCommandFactory::PositionIsHideable(
        const Unit *actor,
-        CommandList & /*existingCommands*/,
+        CommandList &existingCommands,
        const HexMap *hexMap,
        const Coords &target,
        const Units *units,
@@ -39,7 +36,7 @@ auto HideCommandFactory::PositionIsHideable(
    const auto occupant = Occupant(units, target);
    if (occupant) {
        if (occupant->player_id() == actor->player_id()) return false;
-        if (std::ranges::contains(allyPids, occupant->player_id())) return false;
+        if (common::Contains(allyPids, occupant->player_id())) return false;
        if (!occupant->hidden()) return false;
    }

@@ -8,6 +8,7 @@

 #include "HolyWaveCommandFactory.hpp"

+#include "src/main/cpp/net/eagle0/common/ContainerUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/commands/HolyWaveCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

@@ -45,7 +46,7 @@ void HolyWaveCommandFactory::AddAvailableCommands(
    AddAvailableHolyWaveCommands(commands, params.unit, params.remainingActionPoints);
 }

-auto CanHolyWave(const SettingsGetter & /*settings*/, const Unit *unit) -> bool {
+auto CanHolyWave(const SettingsGetter &settings, const Unit *unit) -> bool {
    if (!unit->has_attached_hero()) return false;

    return unit->attached_hero().profession_info().profession() ==
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
admin	f200b4cc4f	not working	2025-07-28 17:18:46 -07:00
admin	6141a27eed	plan	2025-07-28 17:17:28 -07:00
admin	bf7e576bf3	with an int	2025-07-28 17:17:28 -07:00
admin	dd1882967a	create a real thread pool	2025-07-28 17:17:28 -07:00