Fix sysroot .so plugins and registry auth

- Exclude GCC plugin .so files from sysroot (Bazel can't handle them)
- Only copy GCC headers and static libs needed for cross-compilation
- Add tarball structure verification to build script
- Fix DO registry auth by setting DOCKER_CONFIG env var for Bazel

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

.bazelrc

@@ -19,9 +19,9 @@ common --worker_sandboxing
 common --local_test_jobs=64
 common --jobs=64
 
-common --cxxopt="--std=c++20"
+common --cxxopt="--std=c++23"
 common --cxxopt="-Wno-deprecated-non-prototype"
-common --host_cxxopt="--std=c++20"
+common --host_cxxopt="--std=c++23"
 
 common --javacopt="-Xlint:-options"
 
@@ -29,6 +29,9 @@ common --javacopt="-Xlint:-options"
 common --linkopt=-Wl
 common:macos --linkopt=-Wl,-no_warn_duplicate_libraries
 
+# Fix Xcode version caching issue - avoids need for `bazel clean --expunge` after Xcode updates
+common:macos --repo_env=DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
+
 common --java_language_version=17
 common --java_runtime_version=remotejdk_17
 common --tool_java_language_version=17

.clangd

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

.gitattributes

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

.github/workflows/bazel_test.yml

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

.github/workflows/build_sysroot.yml

@@ -0,0 +1,66 @@
+name: Build Linux Sysroot
+
+on:
+  workflow_dispatch:
+    inputs:
+      version:
+        description: 'Sysroot version (e.g., v2, v3)'
+        required: true
+        default: 'v2'
+        type: string
+
+permissions:
+  contents: read
+
+jobs:
+  build-sysroot:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Build sysroot
+        run: ./tools/sysroot/build_sysroot.sh
+
+      - name: Upload sysroot artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: ubuntu-noble-sysroot
+          path: tools/sysroot/output/
+
+      - name: Install AWS CLI
+        run: |
+          if ! command -v aws &> /dev/null; then
+            curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
+            unzip -q awscliv2.zip
+            sudo ./aws/install
+          fi
+
+      - name: Upload to DigitalOcean Spaces
+        env:
+          AWS_ACCESS_KEY_ID: ${{ secrets.ACCESS_KEY_ID }}
+          AWS_SECRET_ACCESS_KEY: ${{ secrets.SECRET_KEY }}
+        run: |
+          # Upload sysroot tarball to DO Spaces (using eagle0-windows bucket, same as other workflows)
+          aws s3 cp tools/sysroot/output/ubuntu_noble_amd64_sysroot.tar.xz \
+            s3://eagle0-windows/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz \
+            --endpoint-url https://sfo3.digitaloceanspaces.com \
+            --acl public-read
+
+          # Upload sha256 file
+          aws s3 cp tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256 \
+            s3://eagle0-windows/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.sha256 \
+            --endpoint-url https://sfo3.digitaloceanspaces.com \
+            --acl public-read
+
+          echo ""
+          echo "=== Sysroot uploaded ==="
+          echo "URL: https://eagle0-windows.sfo3.digitaloceanspaces.com/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz"
+          echo "SHA256: $(cat tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256)"
+          echo ""
+          echo "Update MODULE.bazel with:"
+          echo "sysroot("
+          echo "    name = \"linux_sysroot\","
+          echo "    sha256 = \"$(cat tools/sysroot/output/ubuntu_noble_amd64_sysroot.sha256)\","
+          echo "    urls = [\"https://eagle0-windows.sfo3.digitaloceanspaces.com/sysroot/${{ inputs.version }}/ubuntu_noble_amd64_sysroot.tar.xz\"],"
+          echo ")"

.github/workflows/docker_build.yml

@@ -0,0 +1,82 @@
+name: Docker Build and Push
+
+on:
+  push:
+    branches: [ "main" ]
+    paths:
+      - 'src/main/cpp/**'
+      - 'src/main/scala/**'
+      - 'src/main/protobuf/**'
+      - 'src/main/resources/**'
+      - 'ci/BUILD.bazel'
+      - 'MODULE.bazel'
+      - '.github/workflows/docker_build.yml'
+  workflow_dispatch:
+    inputs:
+      push_images:
+        description: 'Push images to container registry'
+        required: true
+        default: 'false'
+        type: boolean
+
+permissions:
+  contents: read
+
+jobs:
+  build-eagle:
+    runs-on: self-hosted
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          lfs: false
+
+      - name: Build Eagle Docker image
+        run: bazel build //ci:eagle_server_image
+
+      - name: Login to DigitalOcean Container Registry
+        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
+        env:
+          DO_TOKEN: ${{ secrets.DO_REGISTRY_TOKEN }}
+        run: |
+          mkdir -p ~/.docker
+          AUTH=$(echo -n "${DO_TOKEN}:${DO_TOKEN}" | base64)
+          echo "{\"auths\":{\"registry.digitalocean.com\":{\"auth\":\"${AUTH}\"}}}" > ~/.docker/config.json
+          # Also set for current directory in case Bazel uses different home
+          mkdir -p .docker
+          cp ~/.docker/config.json .docker/
+
+      - name: Push Eagle image to DO registry
+        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
+        env:
+          DOCKER_CONFIG: ${{ github.workspace }}/.docker
+        run: bazel run //ci:eagle_server_push
+
+  build-shardok:
+    runs-on: self-hosted
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          lfs: false
+
+      - name: Build Shardok Docker image (cross-compile for Linux)
+        run: bazel build --platforms=//:linux_x86_64 //ci:shardok_server_image
+
+      - name: Login to DigitalOcean Container Registry
+        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
+        env:
+          DO_TOKEN: ${{ secrets.DO_REGISTRY_TOKEN }}
+        run: |
+          mkdir -p ~/.docker
+          AUTH=$(echo -n "${DO_TOKEN}:${DO_TOKEN}" | base64)
+          echo "{\"auths\":{\"registry.digitalocean.com\":{\"auth\":\"${AUTH}\"}}}" > ~/.docker/config.json
+          # Also set for current directory in case Bazel uses different home
+          mkdir -p .docker
+          cp ~/.docker/config.json .docker/
+
+      - name: Push Shardok image to DO registry
+        if: github.event_name == 'push' || (github.event_name == 'workflow_dispatch' && github.event.inputs.push_images == 'true')
+        env:
+          DOCKER_CONFIG: ${{ github.workspace }}/.docker
+        run: bazel run --platforms=//:linux_x86_64 //ci:shardok_server_push

.gitignore

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

.pre-commit-config.yaml

@@ -0,0 +1,44 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.3.0
+    hooks:
+    -   id: check-added-large-files
+    -   id: no-commit-to-branch
+        args: [--branch, main]
+-   repo: https://github.com/pocc/pre-commit-hooks
+    rev: v1.3.5
+    hooks:
+    -   id: clang-format
+        args: [-i, --no-diff]
+        types_or: ["c++", "c#"]
+        exclude: ^src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins
+-   repo: https://github.com/yoheimuta/protolint
+    rev: v0.42.2
+    hooks:
+    -   id: protolint
+        args: [-fix]
+        exclude: ^src/main/protobuf/scalapb/
+-   repo: local
+    hooks:
+    -   id: scalafmt
+        name: scalafmt
+        language: system 
+        entry: scalafmt -i -f 
+        types_or: ["scala"]
+- repo: local
+  hooks:
+      - id: gazelle
+        name: gazelle
+        language: system
+        entry: ./scripts/pre-commit-gazelle.sh
+        files: '(\.go|\.proto|BUILD\.bazel|BUILD|WORKSPACE|WORKSPACE\.bazel|\.bzl)$'
+        pass_filenames: false
+-   repo: local
+    hooks:
+    -   id: update-action-result-types
+        name: update-action-result-types
+        language: system
+        entry: ./scripts/updateActionResultTypes.sh
+        files: 'src/main/protobuf/net/eagle0/eagle/common/action_result_type.proto'

.scalafmt.conf

@@ -1,6 +1,47 @@
 version = "3.9.9"
 runner.dialect = scala3
 rewrite.scala3.convertToNewSyntax = true
+# Keep braces, don't use significant indentation
 # rewrite.scala3.removeOptionalBraces = yes
 rewrite.scala3.insertEndMarkerMinLines = 15
 rewrite.scala3.removeEndMarkerMaxLines = 14
+
+# Strip margin settings
+assumeStandardLibraryStripMargin = false
+align.stripMargin = true
+
+# Code Style & Formatting
+align.preset = more
+align.multiline = true
+align.arrowEnumeratorGenerator = true
+spaces.inImportCurlyBraces = false
+spaces.beforeContextBoundColon = Never
+maxColumn = 120
+docstrings.style = Asterisk
+docstrings.wrap = yes
+
+# Method chaining
+newlines.beforeCurlyLambdaParams = multilineWithCaseOnly
+optIn.breakChainOnFirstMethodDot = true
+includeCurlyBraceInSelectChains = false
+
+# Advanced Scala 3 Features
+rewrite.scala3.countEndMarkerLines = all
+rewrite.redundantBraces.stringInterpolation = true
+rewrite.redundantBraces.parensForOneLineApply = true
+
+# Project-Specific Considerations
+optIn.annotationNewlines = true
+runner.optimizer.forceConfigStyleMinArgCount = 3
+
+# Import sorting configuration
+rewrite.rules = [SortImports, RedundantBraces, RedundantParens]
+rewrite.imports.sort = scalastyle
+rewrite.imports.groups = [
+  ["java\\..*"],
+  ["javax\\..*"],
+  ["scala\\..*"],
+  [".*"]
+]
+rewrite.imports.contiguousGroups = only
+rewrite.trailingCommas.style = never

BUILD.bazel

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

CLAUDE.md

@@ -4,26 +4,32 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.
+Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based
+combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.
 
 ## Architecture
 
 **Three-Tier Game System:**
+
 - **Unity Client (C#)**: Real-time strategy game client with integrated tactical combat UI
 - **Eagle (Scala)**: Strategic layer managing turn-based gameplay, diplomacy, hero progression, and province control
-- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle resolution
+- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle
+  resolution
 
 **Communication Flow:**
+
 ```
 Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC) 
 ```
 
 **Key Entry Points:**
+
 - `/src/main/csharp/net/eagle0/clients/unity/eagle0/` - Unity C# game client
 - `/src/main/scala/net/eagle0/eagle/Main.scala` - Eagle strategic game server
 - `/src/main/cpp/net/eagle0/shardok/shardok_server_main.cpp` - Shardok tactical server
 
 **Protocol Buffer Architecture:**
+
 - Extensive use of protobuf for type-safe communication
 - Separate packages: `api/` (client-facing), `internal/` (server state), `views/` (client projections)
 - Event sourcing pattern with immutable action history
@@ -31,13 +37,17 @@ Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC)
 ## Essential Commands
 
 ### Building
+
 ```bash
 # Build Eagle server (Scala strategic layer)
 bazel build //src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar
 
-# Build Shardok server (C++ tactical layer) 
+# Build Shardok server (C++ tactical layer)
 bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server
 
+# Shardok server includes both AI algorithms
+bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
+
 # Build Unity/C# client
 ./scripts/build_protos.sh         # Protocol buffer generation for Unity
 ./scripts/build_plugins.sh        # Native plugins for all platforms  
@@ -46,6 +56,7 @@ bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server
 ```
 
 ### Running Services
+
 ```bash
 # Eagle server (port 40032)
 bazel run //src/main/scala/net/eagle0/eagle:eagle_server -- --eagle-grpc-port 40032
@@ -57,6 +68,7 @@ bazel run //src/main/cpp/net/eagle0/shardok:shardok-server --compilation_mode=op
 ```
 
 ### Testing
+
 ```bash
 # Run all tests
 bazel test //src/test/... //src/main/go/...
@@ -67,12 +79,24 @@ bazel test //src/test/cpp/...    # C++ Shardok tests
 ```
 
 ### Code Generation
+
 ```bash
 bazel run gazelle              # Update Go build files
 ./scripts/updateActionResultTypes.sh   # Update protocol buffer mappings
 ```
 
+### Pre-Commit Checklist
+
+**MANDATORY: Before running `git commit`, verify:**
+
+1. **If you modified any BUILD.bazel file:** Run `bazel run gazelle` and stage any changes it makes
+2. **If you modified C++ or C# files:** Run `clang-format -i` on the modified files
+3. **If you modified Scala files:** scalafmt will run automatically via pre-commit hook
+
+The pre-commit hook runs gazelle but only checks if it succeeds - it does NOT verify the BUILD files are in canonical format. The `gazelle_test` will fail if deps are not alphabetically sorted. **Always run gazelle manually after BUILD file changes.**
+
 ### Code Formatting
+
 ```bash
 # ALWAYS run clang-format after making any C++ or C# code changes
 clang-format -i <modified_files>
@@ -85,35 +109,94 @@ 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
+bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' <file_path> -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
 
 # Example for AI files:
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' /Users/dancrosby/CodingProjects/github/eagle0/src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.cpp -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++20
+bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' /Users/dancrosby/CodingProjects/github/eagle0/src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.cpp -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
 ```
 
+## AI Algorithm Selection
+
+Eagle0 supports two AI algorithms for tactical combat decision-making:
+
+### Iterative Deepening AI (Default)
+
+The original minimax-based AI with sophisticated randomness handling:
+
+- **Advantages**: Proven, sophisticated randomness evaluation, comprehensive lookahead
+- **Use cases**: Production builds, scenarios requiring precise evaluation
+- **Performance**: Single-threaded, thorough evaluation
+
+### Monte Carlo Tree Search AI (MCTS)
+
+Modern MCTS-based AI with multithreading support:
+
+- **Advantages**: Multithreaded, better performance on modern CPUs, anytime algorithm
+- **Use cases**: Performance testing, scenarios requiring fast decisions
+- **Performance**: Multithreaded, adaptive depth based on time budget
+
+### Switching Between Algorithms
+
+The algorithm is selected at **runtime** via the ShardokAIClient constructor:
+
+```cpp
+// Using Iterative Deepening AI (default)
+ShardokAIClient client(playerId, isDefender, hexMap, settings);
+// OR explicitly:
+ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::ITERATIVE_DEEPENING);
+
+// Using MCTS AI
+ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::MCTS);
+```
+
+```bash
+# Build the server (includes both AI algorithms)
+bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
+
+# Test both algorithms
+bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_iterative_deepening_test
+bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_mcts_test  # If available
+
+# Performance tests
+./scripts/ai_perf_test.sh  # Uses whatever algorithm the server is configured to use
+```
+
+Both implementations are compatible with all existing interfaces and produce the same `SearchResult` structure.
+
+**Note**: Both implementations are documented in `src/main/cpp/net/eagle0/shardok/ai/AI_SCORING_SYSTEM.md`, including
+recommendations for improving MCTS randomness handling.
+
+The AI algorithm selection is made at runtime when creating ShardokAIClient instances, allowing different AI strategies
+to be used for different players or game situations within the same server process.
+
 ## Language-Specific Patterns
 
 **Scala (Strategic Layer):**
+
 - Use `EngineImpl.scala` for core game logic modifications
 - Follow event sourcing pattern - all changes through immutable actions
 - gRPC streaming for real-time client updates via `EagleServiceImpl.scala`
 - LLM integration in `/common/llm_integration/` for narrative generation
 
 **C++ (Tactical Layer):**
+
 - Performance-critical combat in `ShardokEngine.hpp/.cpp`
 - FlatBuffers for efficient serialization in `/flatbuffer/` directory
 - AI systems in `/ai/` subdirectory with pluggable strategy selectors
 - Extensive unit testing with Google Test framework
 
 **Protocol Buffers:**
+
 - Three-layer structure: `api/` (client), `internal/` (server), `views/` (projections)
 - Use `shardok_internal_interface.proto` for Eagle-Shardok communication
 - Maintain backward compatibility when modifying existing messages
 
 **C# (Unity Client):**
+
 - Located in `/src/main/csharp/net/eagle0/clients/unity/eagle0/`
 - Uses Unity 6 (6000.0.32f1) with comprehensive protobuf integration (100+ .proto files)
 - Key components: `EagleConnection.cs` (gRPC client), `EagleGameController.cs` (main game logic)
@@ -122,6 +205,7 @@ bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,cla
 - Seamless transition between strategic gameplay and hex-based tactical combat
 
 **Go (Build Tools):**
+
 - Build automation and code generation utilities
 - AWS S3 integration for deployment artifacts
 
@@ -132,6 +216,31 @@ bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,cla
 - Map validation tests ensure game content integrity
 - Use `GameSettings_test_utils.cpp` and `ShardokEngineBasedTestData.cpp` for C++ test helpers
 
+### Scala Testing Patterns
+
+**Use `inside()` instead of `asInstanceOf` for type matching in tests:**
+
+Never use `asInstanceOf` in tests. Instead, use ScalaTest's `inside()` pattern for safe type matching:
+
+```scala
+// BAD - don't do this
+val changedHero = result.changedHeroes.head.asInstanceOf[ChangedHeroC]
+changedHero.heroId shouldBe 19
+
+// GOOD - use inside() pattern
+import org.scalatest.Inside.inside
+
+inside(result.changedHeroes.head) { case changedHero: ChangedHeroC =>
+  changedHero.heroId shouldBe 19
+  changedHero.vigorChange shouldBe StatDelta(17.2)
+}
+```
+
+The `inside()` pattern:
+- Provides better error messages when the type doesn't match
+- Is idiomatic ScalaTest
+- Works with pattern matching for more complex assertions
+
 ## Performance Testing
 
 When making performance-related changes to the AI or engine:
@@ -163,10 +272,38 @@ done
 ```
 
 **Important notes:**
+
 - Run tests multiple times (3-5) to account for performance variance
 - Focus on commands evaluated at each depth rather than total commands
 - Commands at different depths aren't directly comparable (depth 3 is more valuable than depth 2)
-- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or behavior changes.
+- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or
+  behavior changes.
+
+## Troubleshooting Scala Build Errors
+
+### MissingType Errors
+
+When you see errors like:
+```
+dotty.tools.dotc.core.MissingType: Cannot resolve reference to type net.eagle0.eagle.internal.game_state.type.GameState
+```
+
+**This is NOT a Scala compiler crash.** This is a missing dependency in BUILD.bazel.
+
+**How to fix:**
+1. Identify the missing type from the error message (e.g., `game_state.GameState`)
+2. Find the Bazel target that provides this type (e.g., `//src/main/protobuf/net/eagle0/eagle/internal:game_state_scala_proto`)
+3. Add it to the `deps` of the failing target
+4. If the type appears in a public method signature, also add it to `exports` so downstream targets can see it
+
+**Common pattern:** When adding a method to a class that takes or returns a proto type, the proto dependency often needs to be added to both `deps` AND `exports`.
+
+### Bazel Clean
+
+**NEVER run `bazel clean` without asking first.** It rarely fixes actual issues and wastes significant rebuild time. The issues that seem like they need `bazel clean` are usually:
+- Missing imports in Scala code
+- Missing dependencies in BUILD.bazel
+- Missing exports for types used in public signatures
 
 ## Game Content
 

MODULE.bazel

@@ -26,56 +26,75 @@ 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 = "1.6.0")
 
 llvm = use_extension("@toolchains_llvm//toolchain/extensions:llvm.bzl", "llvm")
 
+# Native toolchain (macOS -> macOS, Linux -> Linux)
 llvm.toolchain(
     name = "llvm_toolchain",
     llvm_version = "20.1.2",
 )
 
-use_repo(llvm, "llvm_toolchain")
+# Cross-compilation toolchain (macOS -> Linux x86_64)
+# Uses the same LLVM distribution but with a Linux sysroot
+llvm.toolchain(
+    name = "llvm_toolchain_linux",
+    llvm_version = "20.1.2",
+)
+
+# Linux sysroot for cross-compilation (Chromium's Debian sysroot)
+llvm.sysroot(
+    name = "llvm_toolchain_linux",
+    label = "@linux_sysroot//sysroot",
+    targets = ["linux-x86_64"],
+)
+
+use_repo(llvm, "llvm_toolchain", "llvm_toolchain_linux")
+
+# Download the Linux sysroot (Ubuntu 24.04 Noble for C++23 support)
+# Built by: .github/workflows/build_sysroot.yml
+# To rebuild: Run the "Build Linux Sysroot" workflow with a new version, then update sha256 and URL
+sysroot = use_repo_rule("@toolchains_llvm//toolchain:sysroot.bzl", "sysroot")
+sysroot(
+    name = "linux_sysroot",
+    sha256 = "aadb60a2e2c776ac000bb2e29f3039fd81b5b031500cf4a1651b365712819d1f",
+    urls = ["https://eagle0-windows.sfo3.digitaloceanspaces.com/sysroot/v2/ubuntu_noble_amd64_sysroot.tar.xz"],
+)
 
 #
 # Language Support - Go
 #
 
-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_go", version = "0.56.1", repo_name = "io_bazel_rules_go")
+bazel_dep(name = "gazelle", version = "0.45.0", repo_name = "bazel_gazelle")
 
 go_sdk = use_extension("@io_bazel_rules_go//go:extensions.bzl", "go_sdk")
-
 go_sdk.download(version = "1.23.3")
 
 go_deps = use_extension("@bazel_gazelle//:extensions.bzl", "go_deps")
-
 go_deps.from_file(go_mod = "//:go.mod")
-
 use_repo(
     go_deps,
     "com_github_aws_aws_sdk_go_v2",
     "com_github_aws_aws_sdk_go_v2_config",
     "com_github_aws_aws_sdk_go_v2_credentials",
     "com_github_aws_aws_sdk_go_v2_service_s3",
+    "org_golang_google_grpc",
     "org_golang_google_protobuf",
 )
 
@@ -83,15 +102,15 @@ use_repo(
 # 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")
+bazel_dep(name = "apple_support", version = "1.21.1", repo_name = "build_bazel_apple_support")
+bazel_dep(name = "rules_apple", version = "3.16.1", repo_name = "build_bazel_rules_apple")
+bazel_dep(name = "rules_swift", version = "2.3.1", repo_name = "build_bazel_rules_swift")
 
 #
 # Protocol Buffers & RPC
 #
 
-bazel_dep(name = "protobuf", repo_name = "com_google_protobuf", version = "29.2")
+bazel_dep(name = "protobuf", version = "29.2", repo_name = "com_google_protobuf")
 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")
@@ -102,6 +121,32 @@ bazel_dep(name = "flatbuffers", version = "25.2.10")
 
 bazel_dep(name = "googletest", version = "1.17.0")
 
+#
+# Container Images (OCI)
+#
+
+bazel_dep(name = "rules_oci", version = "2.2.6")
+bazel_dep(name = "aspect_bazel_lib", version = "2.16.0")
+
+oci = use_extension("@rules_oci//oci:extensions.bzl", "oci")
+
+# Base image for Eagle (Java 17)
+oci.pull(
+    name = "eclipse_temurin_17",
+    digest = "sha256:d286b5352d98777bbf727f54038b04f0145cd9b76ca83f38a67aa111d4303748",
+    image = "docker.io/library/eclipse-temurin",
+    platforms = ["linux/amd64"],
+)
+
+# Base image for Shardok (Ubuntu 24.04 for C++ runtime)
+oci.pull(
+    name = "ubuntu_24_04",
+    image = "docker.io/library/ubuntu",
+    platforms = ["linux/amd64"],
+    tag = "24.04",
+)
+use_repo(oci, "eclipse_temurin_17", "eclipse_temurin_17_linux_amd64", "ubuntu_24_04", "ubuntu_24_04_linux_amd64")
+
 #
 # Java/Scala Dependencies
 #
@@ -109,7 +154,6 @@ bazel_dep(name = "googletest", version = "1.17.0")
 bazel_dep(name = "rules_jvm_external", version = "6.3")
 
 maven = use_extension("@rules_jvm_external//:extensions.bzl", "maven")
-
 maven.install(
     artifacts = [
         # Netty
@@ -160,6 +204,10 @@ maven.install(
         # Other
         "org.reactivestreams:reactive-streams:1.0.4",
         "javax.xml.bind:jaxb-api:2.3.1",
+
+        # OkHttp (for SSE with read timeout support)
+        "com.squareup.okhttp3:okhttp:4.12.0",
+        "com.squareup.okhttp3:okhttp-sse:4.12.0",
     ],
     duplicate_version_warning = "error",
     fail_if_repin_required = True,
@@ -168,7 +216,6 @@ maven.install(
         "https://repo1.maven.org/maven2",
     ],
 )
-
 use_repo(maven, "maven", "unpinned_maven")
 
 #
@@ -216,5 +263,6 @@ register_toolchains(
 # Set dev_dependency so we can turn this off for swift MacOS builds
 register_toolchains(
     "@llvm_toolchain//:all",
+    "@llvm_toolchain_linux//:all",
     dev_dependency = True,
 )

MODULE.bazel.lock

@@ -26,7 +26,11 @@
     "https://bcr.bazel.build/modules/aspect_bazel_lib/1.38.0/MODULE.bazel": "6307fec451ba9962c1c969eb516ebfe1e46528f7fa92e1c9ac8646bef4cdaa3f",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/1.40.3/MODULE.bazel": "668e6bcb4d957fc0e284316dba546b705c8d43c857f87119619ee83c4555b859",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.11.0/MODULE.bazel": "cb1ba9f9999ed0bc08600c221f532c1ddd8d217686b32ba7d45b0713b5131452",
-    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.11.0/source.json": "92494d5aa43b96665397dd13ee16023097470fa85e276b93674d62a244de47ee",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.14.0/MODULE.bazel": "2b31ffcc9bdc8295b2167e07a757dbbc9ac8906e7028e5170a3708cecaac119f",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.16.0/MODULE.bazel": "852f9ebbda017572a7c113a2434592dd3b2f55cd9a0faea3d4be5a09a59e4900",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.19.3/MODULE.bazel": "253d739ba126f62a5767d832765b12b59e9f8d2bc88cc1572f4a73e46eb298ca",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.19.3/source.json": "ffab9254c65ba945f8369297ad97ca0dec213d3adc6e07877e23a48624a8b456",
+    "https://bcr.bazel.build/modules/aspect_bazel_lib/2.7.2/MODULE.bazel": "780d1a6522b28f5edb7ea09630748720721dfe27690d65a2d33aa7509de77e07",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.7.7/MODULE.bazel": "491f8681205e31bb57892d67442ce448cda4f472a8e6b3dc062865e29a64f89c",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.8.1/MODULE.bazel": "812d2dd42f65dca362152101fbec418029cc8fd34cbad1a2fde905383d705838",
     "https://bcr.bazel.build/modules/aspect_bazel_lib/2.9.3/MODULE.bazel": "66baf724dbae7aff4787bf2245cc188d50cb08e07789769730151c0943587c14",
@@ -51,8 +55,11 @@
     "https://bcr.bazel.build/modules/bazel_features/1.19.0/MODULE.bazel": "59adcdf28230d220f0067b1f435b8537dd033bfff8db21335ef9217919c7fb58",
     "https://bcr.bazel.build/modules/bazel_features/1.21.0/MODULE.bazel": "675642261665d8eea09989aa3b8afb5c37627f1be178382c320d1b46afba5e3b",
     "https://bcr.bazel.build/modules/bazel_features/1.27.0/MODULE.bazel": "621eeee06c4458a9121d1f104efb80f39d34deff4984e778359c60eaf1a8cb65",
-    "https://bcr.bazel.build/modules/bazel_features/1.27.0/source.json": "ed8cf0ef05c858dce3661689d0a2b110ff398e63994e178e4f1f7555a8067fed",
+    "https://bcr.bazel.build/modules/bazel_features/1.28.0/MODULE.bazel": "4b4200e6cbf8fa335b2c3f43e1d6ef3e240319c33d43d60cc0fbd4b87ece299d",
     "https://bcr.bazel.build/modules/bazel_features/1.3.0/MODULE.bazel": "cdcafe83ec318cda34e02948e81d790aab8df7a929cec6f6969f13a489ccecd9",
+    "https://bcr.bazel.build/modules/bazel_features/1.34.0/MODULE.bazel": "e8475ad7c8965542e0c7aac8af68eb48c4af904be3d614b6aa6274c092c2ea1e",
+    "https://bcr.bazel.build/modules/bazel_features/1.38.0/MODULE.bazel": "f9b8a9c890ebd216b4049fd12a31d3c2602e3403c7af636b04fbbd7453edc9c9",
+    "https://bcr.bazel.build/modules/bazel_features/1.38.0/source.json": "31ba776c122b54a2885e23651642e32f087a87bf025465f8040751894b571277",
     "https://bcr.bazel.build/modules/bazel_features/1.4.1/MODULE.bazel": "e45b6bb2350aff3e442ae1111c555e27eac1d915e77775f6fdc4b351b758b5d7",
     "https://bcr.bazel.build/modules/bazel_features/1.9.0/MODULE.bazel": "885151d58d90d8d9c811eb75e3288c11f850e1d6b481a8c9f766adee4712358b",
     "https://bcr.bazel.build/modules/bazel_features/1.9.1/MODULE.bazel": "8f679097876a9b609ad1f60249c49d68bfab783dd9be012faf9d82547b14815a",
@@ -69,7 +76,8 @@
     "https://bcr.bazel.build/modules/bazel_skylib/1.7.0/MODULE.bazel": "0db596f4563de7938de764cc8deeabec291f55e8ec15299718b93c4423e9796d",
     "https://bcr.bazel.build/modules/bazel_skylib/1.7.1/MODULE.bazel": "3120d80c5861aa616222ec015332e5f8d3171e062e3e804a2a0253e1be26e59b",
     "https://bcr.bazel.build/modules/bazel_skylib/1.8.1/MODULE.bazel": "88ade7293becda963e0e3ea33e7d54d3425127e0a326e0d17da085a5f1f03ff6",
-    "https://bcr.bazel.build/modules/bazel_skylib/1.8.1/source.json": "7ebaefba0b03efe59cac88ed5bbc67bcf59a3eff33af937345ede2a38b2d368a",
+    "https://bcr.bazel.build/modules/bazel_skylib/1.8.2/MODULE.bazel": "69ad6927098316848b34a9142bcc975e018ba27f08c4ff403f50c1b6e646ca67",
+    "https://bcr.bazel.build/modules/bazel_skylib/1.8.2/source.json": "34a3c8bcf233b835eb74be9d628899bb32999d3e0eadef1947a0a562a2b16ffb",
     "https://bcr.bazel.build/modules/bazel_worker_api/0.0.6/MODULE.bazel": "fd1f9432ca04c947e91b500df69ce7c5b6dbfe1bc45ab1820338205dae3383a6",
     "https://bcr.bazel.build/modules/bazel_worker_api/0.0.6/source.json": "5d68545f224904745a3cabd35aea6bc2b6cc5a78b7f49f3f69660eab2eeeb273",
     "https://bcr.bazel.build/modules/boringssl/0.0.0-20211025-d4f1ab9/MODULE.bazel": "6ee6353f8b1a701fe2178e1d925034294971350b6d3ac37e67e5a7d463267834",
@@ -98,6 +106,8 @@
     "https://bcr.bazel.build/modules/envoy_api/0.0.0-20250128-4de3c74/source.json": "028519164a2e24563f4b43d810fdedc702daed90e71e7042d45ba82ad807b46f",
     "https://bcr.bazel.build/modules/flatbuffers/25.2.10/MODULE.bazel": "dab15cafe8512d2c4a8daa44c2d7968c5c79f01e220d40076cdc260bf58605e2",
     "https://bcr.bazel.build/modules/flatbuffers/25.2.10/source.json": "7eae7ea3eb913b9802426e4d5df11d6c6072a3573a548f8cabf1e965f5cca4d0",
+    "https://bcr.bazel.build/modules/gawk/5.3.2.bcr.1/MODULE.bazel": "cdf8cbe5ee750db04b78878c9633cc76e80dcf4416cbe982ac3a9222f80713c8",
+    "https://bcr.bazel.build/modules/gawk/5.3.2.bcr.1/source.json": "fa7b512dfcb5eafd90ce3959cf42a2a6fe96144ebbb4b3b3928054895f2afac2",
     "https://bcr.bazel.build/modules/gazelle/0.27.0/MODULE.bazel": "3446abd608295de6d90b4a8a118ed64a9ce11dcb3dda2dc3290a22056bd20996",
     "https://bcr.bazel.build/modules/gazelle/0.30.0/MODULE.bazel": "f888a1effe338491f35f0e0e85003b47bb9d8295ccba73c37e07702d8d31c65b",
     "https://bcr.bazel.build/modules/gazelle/0.32.0/MODULE.bazel": "b499f58a5d0d3537f3cf5b76d8ada18242f64ec474d8391247438bf04f58c7b8",
@@ -137,6 +147,10 @@
     "https://bcr.bazel.build/modules/grpc/1.70.1/MODULE.bazel": "b800cd8e3e7555c1e61cba2e02d3a2fcf0e91f66e800db286d965d3b7a6a721a",
     "https://bcr.bazel.build/modules/grpc/1.71.0/MODULE.bazel": "7fcab2c05530373f1a442c362b17740dd0c75b6a2a975eec8f5bf4c70a37928a",
     "https://bcr.bazel.build/modules/grpc/1.71.0/source.json": "60ef8c4c72c8280ae94c05b4f38bf67785acb25477ab8dbac096a9604449ff90",
+    "https://bcr.bazel.build/modules/helly25_bzl/0.3.1/MODULE.bazel": "3a4be20f6fc13be32ad44643b8252ef5af09eee936f1d943cd4fd7867fa92826",
+    "https://bcr.bazel.build/modules/helly25_bzl/0.3.1/source.json": "b129ab1828492de2c163785bbeb4065c166de52d932524b4317beb5b7f917994",
+    "https://bcr.bazel.build/modules/jq.bzl/0.1.0/MODULE.bazel": "2ce69b1af49952cd4121a9c3055faa679e748ce774c7f1fda9657f936cae902f",
+    "https://bcr.bazel.build/modules/jq.bzl/0.1.0/source.json": "746bf13cac0860f091df5e4911d0c593971cd8796b5ad4e809b2f8e133eee3d5",
     "https://bcr.bazel.build/modules/jsoncpp/1.9.5/MODULE.bazel": "31271aedc59e815656f5736f282bb7509a97c7ecb43e927ac1a37966e0578075",
     "https://bcr.bazel.build/modules/jsoncpp/1.9.5/source.json": "4108ee5085dd2885a341c7fab149429db457b3169b86eb081fa245eadf69169d",
     "https://bcr.bazel.build/modules/libpfm/4.11.0/MODULE.bazel": "45061ff025b301940f1e30d2c16bea596c25b176c8b6b3087e92615adbd52902",
@@ -161,6 +175,7 @@
     "https://bcr.bazel.build/modules/opentelemetry-proto/1.5.0/source.json": "046b721ce203e88cdaad44d7dd17a86b7200eab9388b663b234e72e13ff7b143",
     "https://bcr.bazel.build/modules/opentracing-cpp/1.6.0/MODULE.bazel": "b3925269f63561b8b880ae7cf62ccf81f6ece55b62cd791eda9925147ae116ec",
     "https://bcr.bazel.build/modules/opentracing-cpp/1.6.0/source.json": "da1cb1add160f5e5074b7272e9db6fd8f1b3336c15032cd0a653af9d2f484aed",
+    "https://bcr.bazel.build/modules/package_metadata/0.0.2/MODULE.bazel": "fb8d25550742674d63d7b250063d4580ca530499f045d70748b1b142081ebb92",
     "https://bcr.bazel.build/modules/package_metadata/0.0.5/MODULE.bazel": "ef4f9439e3270fdd6b9fd4dbc3d2f29d13888e44c529a1b243f7a31dfbc2e8e4",
     "https://bcr.bazel.build/modules/package_metadata/0.0.5/source.json": "2326db2f6592578177751c3e1f74786b79382cd6008834c9d01ec865b9126a85",
     "https://bcr.bazel.build/modules/platforms/0.0.10/MODULE.bazel": "8cb8efaf200bdeb2150d93e162c40f388529a25852b332cec879373771e48ed5",
@@ -225,12 +240,14 @@
     "https://bcr.bazel.build/modules/rules_cc/0.0.15/MODULE.bazel": "6704c35f7b4a72502ee81f61bf88706b54f06b3cbe5558ac17e2e14666cd5dcc",
     "https://bcr.bazel.build/modules/rules_cc/0.0.16/MODULE.bazel": "7661303b8fc1b4d7f532e54e9d6565771fea666fbdf839e0a86affcd02defe87",
     "https://bcr.bazel.build/modules/rules_cc/0.0.17/MODULE.bazel": "2ae1d8f4238ec67d7185d8861cb0a2cdf4bc608697c331b95bf990e69b62e64a",
-    "https://bcr.bazel.build/modules/rules_cc/0.0.17/source.json": "4db99b3f55c90ab28d14552aa0632533e3e8e5e9aea0f5c24ac0014282c2a7c5",
     "https://bcr.bazel.build/modules/rules_cc/0.0.2/MODULE.bazel": "6915987c90970493ab97393024c156ea8fb9f3bea953b2f3ec05c34f19b5695c",
     "https://bcr.bazel.build/modules/rules_cc/0.0.5/MODULE.bazel": "be41f87587998fe8890cd82ea4e848ed8eb799e053c224f78f3ff7fe1a1d9b74",
     "https://bcr.bazel.build/modules/rules_cc/0.0.6/MODULE.bazel": "abf360251023dfe3efcef65ab9d56beefa8394d4176dd29529750e1c57eaa33f",
     "https://bcr.bazel.build/modules/rules_cc/0.0.8/MODULE.bazel": "964c85c82cfeb6f3855e6a07054fdb159aced38e99a5eecf7bce9d53990afa3e",
     "https://bcr.bazel.build/modules/rules_cc/0.0.9/MODULE.bazel": "836e76439f354b89afe6a911a7adf59a6b2518fafb174483ad78a2a2fde7b1c5",
+    "https://bcr.bazel.build/modules/rules_cc/0.1.1/MODULE.bazel": "2f0222a6f229f0bf44cd711dc13c858dad98c62d52bd51d8fc3a764a83125513",
+    "https://bcr.bazel.build/modules/rules_cc/0.2.14/MODULE.bazel": "353c99ed148887ee89c54a17d4100ae7e7e436593d104b668476019023b58df8",
+    "https://bcr.bazel.build/modules/rules_cc/0.2.14/source.json": "55d0a4587c5592fad350f6e698530f4faf0e7dd15e69d43f8d87e220c78bea54",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.10.1/MODULE.bazel": "b9527010e5fef060af92b6724edb3691970a5b1f76f74b21d39f7d433641be60",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.10.1/source.json": "9300e71df0cdde0952f10afff1401fa664e9fc5d9ae6204660ba1b158d90d6a6",
     "https://bcr.bazel.build/modules/rules_foreign_cc/0.9.0/MODULE.bazel": "c9e8c682bf75b0e7c704166d79b599f93b72cfca5ad7477df596947891feeef6",
@@ -289,6 +306,8 @@
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.0/MODULE.bazel": "45345e4aba35dd6e4701c1eebf5a4e67af4ed708def9ebcdc6027585b34ee52d",
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.3/MODULE.bazel": "b66eadebd10f1f1b25f52f95ab5213a57e82c37c3f656fcd9a57ad04d2264ce7",
     "https://bcr.bazel.build/modules/rules_nodejs/6.3.3/source.json": "45bd343155bdfed2543f0e39b80ff3f6840efc31975da4b5795797f4c94147ad",
+    "https://bcr.bazel.build/modules/rules_oci/2.2.6/MODULE.bazel": "2ba6ddd679269e00aeffe9ca04faa2d0ca4129650982c9246d0d459fe2da47d9",
+    "https://bcr.bazel.build/modules/rules_oci/2.2.6/source.json": "94e7decb8f95d9465b0bbea71c65064cd16083be1350c7468f131818641dc4a5",
     "https://bcr.bazel.build/modules/rules_pkg/0.7.0/MODULE.bazel": "df99f03fc7934a4737122518bb87e667e62d780b610910f0447665a7e2be62dc",
     "https://bcr.bazel.build/modules/rules_pkg/1.0.1/MODULE.bazel": "5b1df97dbc29623bccdf2b0dcd0f5cb08e2f2c9050aab1092fd39a41e82686ff",
     "https://bcr.bazel.build/modules/rules_pkg/1.1.0/MODULE.bazel": "9db8031e71b6ef32d1846106e10dd0ee2deac042bd9a2de22b4761b0c3036453",
@@ -321,7 +340,8 @@
     "https://bcr.bazel.build/modules/rules_scala/7.1.1/source.json": "5038cb231d4020c5965c920681cf961a7bf137b40315025e40f3a7b6a0ac1f0f",
     "https://bcr.bazel.build/modules/rules_shell/0.2.0/MODULE.bazel": "fda8a652ab3c7d8fee214de05e7a9916d8b28082234e8d2c0094505c5268ed3c",
     "https://bcr.bazel.build/modules/rules_shell/0.3.0/MODULE.bazel": "de4402cd12f4cc8fda2354fce179fdb068c0b9ca1ec2d2b17b3e21b24c1a937b",
-    "https://bcr.bazel.build/modules/rules_shell/0.3.0/source.json": "c55ed591aa5009401ddf80ded9762ac32c358d2517ee7820be981e2de9756cf3",
+    "https://bcr.bazel.build/modules/rules_shell/0.4.1/MODULE.bazel": "00e501db01bbf4e3e1dd1595959092c2fadf2087b2852d3f553b5370f5633592",
+    "https://bcr.bazel.build/modules/rules_shell/0.4.1/source.json": "4757bd277fe1567763991c4425b483477bb82e35e777a56fd846eb5cceda324a",
     "https://bcr.bazel.build/modules/rules_swift/1.16.0/MODULE.bazel": "4a09f199545a60d09895e8281362b1ff3bb08bbde69c6fc87aff5b92fcc916ca",
     "https://bcr.bazel.build/modules/rules_swift/1.18.0/MODULE.bazel": "a6aba73625d0dc64c7b4a1e831549b6e375fbddb9d2dde9d80c9de6ec45b24c9",
     "https://bcr.bazel.build/modules/rules_swift/2.1.1/MODULE.bazel": "494900a80f944fc7aa61500c2073d9729dff0b764f0e89b824eb746959bc1046",
@@ -339,14 +359,19 @@
     "https://bcr.bazel.build/modules/stardoc/0.7.2/source.json": "58b029e5e901d6802967754adf0a9056747e8176f017cfe3607c0851f4d42216",
     "https://bcr.bazel.build/modules/swift_argument_parser/1.3.1.1/MODULE.bazel": "5e463fbfba7b1701d957555ed45097d7f984211330106ccd1352c6e0af0dcf91",
     "https://bcr.bazel.build/modules/swift_argument_parser/1.3.1.1/source.json": "32bd87e5f4d7acc57c5b2ff7c325ae3061d5e242c0c4c214ae87e0f1c13e54cb",
-    "https://bcr.bazel.build/modules/toolchains_llvm/1.4.0/MODULE.bazel": "05239402b7374293359c2f22806f420b75aa5d6f4b15a2eaa809a2c214d58b31",
-    "https://bcr.bazel.build/modules/toolchains_llvm/1.4.0/source.json": "229a516d282b17a82be54c6e3ae220a1b750fb55a8495567e5c7a9d09423f3e2",
+    "https://bcr.bazel.build/modules/tar.bzl/0.2.1/MODULE.bazel": "52d1c00a80a8cc67acbd01649e83d8dd6a9dc426a6c0b754a04fe8c219c76468",
+    "https://bcr.bazel.build/modules/tar.bzl/0.6.0/MODULE.bazel": "a3584b4edcfafcabd9b0ef9819808f05b372957bbdff41601429d5fd0aac2e7c",
+    "https://bcr.bazel.build/modules/tar.bzl/0.6.0/source.json": "4a620381df075a16cb3a7ed57bd1d05f7480222394c64a20fa51bdb636fda658",
+    "https://bcr.bazel.build/modules/toolchains_llvm/1.6.0/MODULE.bazel": "39603859cafb1c6830160fcd6370552e836790e6abb2bfb8d13bff53c0c10a64",
+    "https://bcr.bazel.build/modules/toolchains_llvm/1.6.0/source.json": "6bd3ef95a288dd2bb1582eca332af850c9a5428a23bb92cb1c57c2dfe6cb7369",
     "https://bcr.bazel.build/modules/upb/0.0.0-20211020-160625a/MODULE.bazel": "6cced416be2dc5b9c05efd5b997049ba795e5e4e6fafbe1624f4587767638928",
     "https://bcr.bazel.build/modules/upb/0.0.0-20220923-a547704/MODULE.bazel": "7298990c00040a0e2f121f6c32544bab27d4452f80d9ce51349b1a28f3005c43",
     "https://bcr.bazel.build/modules/upb/0.0.0-20230516-61a97ef/MODULE.bazel": "c0df5e35ad55e264160417fd0875932ee3c9dda63d9fccace35ac62f45e1b6f9",
     "https://bcr.bazel.build/modules/upb/0.0.0-20230907-e7430e6/MODULE.bazel": "3a7dedadf70346e678dc059dbe44d05cbf3ab17f1ce43a1c7a42edc7cbf93fd9",
     "https://bcr.bazel.build/modules/xds/0.0.0-20240423-555b57e/MODULE.bazel": "cea509976a77e34131411684ef05a1d6ad194dd71a8d5816643bc5b0af16dc0f",
     "https://bcr.bazel.build/modules/xds/0.0.0-20240423-555b57e/source.json": "7227e1fcad55f3f3cab1a08691ecd753cb29cc6380a47bc650851be9f9ad6d20",
+    "https://bcr.bazel.build/modules/yq.bzl/0.1.1/MODULE.bazel": "9039681f9bcb8958ee2c87ffc74bdafba9f4369096a2b5634b88abc0eaefa072",
+    "https://bcr.bazel.build/modules/yq.bzl/0.1.1/source.json": "2d2bad780a9f2b9195a4a370314d2c17ae95eaa745cefc2e12fbc49759b15aa3",
     "https://bcr.bazel.build/modules/zlib/1.2.11/MODULE.bazel": "07b389abc85fdbca459b69e2ec656ae5622873af3f845e1c9d80fe179f3effa0",
     "https://bcr.bazel.build/modules/zlib/1.2.12/MODULE.bazel": "3b1a8834ada2a883674be8cbd36ede1b6ec481477ada359cd2d3ddc562340b27",
     "https://bcr.bazel.build/modules/zlib/1.2.13/MODULE.bazel": "aa6deb1b83c18ffecd940c4119aff9567cd0a671d7bba756741cb2ef043a29d5",
@@ -388,7 +413,7 @@
     },
     "@@aspect_rules_esbuild~//esbuild:extensions.bzl%esbuild": {
       "general": {
-        "bzlTransitiveDigest": "8iOqbPY5ve3DvjzaI1mJZ8XTiJypN2PeWvcKOvmZLy8=",
+        "bzlTransitiveDigest": "8jv3p0xDR/oitFeH8y0+Y5xlyrUbfsTRlc9TSwYkwl8=",
         "usagesDigest": "iDVoyPxUeADmfK8ssoyG3Ehq1bj6p7A43LpEiE266os=",
         "recordedFileInputs": {},
         "recordedDirentsInputs": {},
@@ -1265,6 +1290,247 @@
         "recordedRepoMappingEntries": []
       }
     },
+    "@@rules_oci~//oci:extensions.bzl%oci": {
+      "general": {
+        "bzlTransitiveDigest": "FaY+7xb13bB3hmxqwAWaGp3Tf3Q4Nfdlr+F38CP5mcg=",
+        "usagesDigest": "BuciKSozbpJMD9EP+j0RG5ZgrYMeDPsQyiOnLUni2V8=",
+        "recordedFileInputs": {},
+        "recordedDirentsInputs": {},
+        "envVariables": {},
+        "generatedRepoSpecs": {
+          "eclipse_temurin_17_linux_amd64": {
+            "bzlFile": "@@rules_oci~//oci/private:pull.bzl",
+            "ruleClassName": "oci_pull",
+            "attributes": {
+              "www_authenticate_challenges": {},
+              "scheme": "https",
+              "registry": "index.docker.io",
+              "repository": "library/eclipse-temurin",
+              "identifier": "sha256:d286b5352d98777bbf727f54038b04f0145cd9b76ca83f38a67aa111d4303748",
+              "platform": "linux/amd64",
+              "target_name": "eclipse_temurin_17_linux_amd64",
+              "bazel_tags": []
+            }
+          },
+          "eclipse_temurin_17": {
+            "bzlFile": "@@rules_oci~//oci/private:pull.bzl",
+            "ruleClassName": "oci_alias",
+            "attributes": {
+              "target_name": "eclipse_temurin_17",
+              "www_authenticate_challenges": {},
+              "scheme": "https",
+              "registry": "index.docker.io",
+              "repository": "library/eclipse-temurin",
+              "identifier": "sha256:d286b5352d98777bbf727f54038b04f0145cd9b76ca83f38a67aa111d4303748",
+              "platforms": {
+                "@@platforms//cpu:x86_64": "@eclipse_temurin_17_linux_amd64"
+              },
+              "bzlmod_repository": "eclipse_temurin_17",
+              "reproducible": true
+            }
+          },
+          "ubuntu_24_04_linux_amd64": {
+            "bzlFile": "@@rules_oci~//oci/private:pull.bzl",
+            "ruleClassName": "oci_pull",
+            "attributes": {
+              "www_authenticate_challenges": {},
+              "scheme": "https",
+              "registry": "index.docker.io",
+              "repository": "library/ubuntu",
+              "identifier": "24.04",
+              "platform": "linux/amd64",
+              "target_name": "ubuntu_24_04_linux_amd64",
+              "bazel_tags": []
+            }
+          },
+          "ubuntu_24_04": {
+            "bzlFile": "@@rules_oci~//oci/private:pull.bzl",
+            "ruleClassName": "oci_alias",
+            "attributes": {
+              "target_name": "ubuntu_24_04",
+              "www_authenticate_challenges": {},
+              "scheme": "https",
+              "registry": "index.docker.io",
+              "repository": "library/ubuntu",
+              "identifier": "24.04",
+              "platforms": {
+                "@@platforms//cpu:x86_64": "@ubuntu_24_04_linux_amd64"
+              },
+              "bzlmod_repository": "ubuntu_24_04",
+              "reproducible": true
+            }
+          },
+          "oci_crane_darwin_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "darwin_amd64",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_darwin_arm64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "darwin_arm64",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_linux_arm64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "linux_arm64",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_linux_armv6": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "linux_armv6",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_linux_i386": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "linux_i386",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_linux_s390x": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "linux_s390x",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_linux_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "linux_amd64",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_windows_armv6": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "windows_armv6",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_windows_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "crane_repositories",
+            "attributes": {
+              "platform": "windows_amd64",
+              "crane_version": "v0.18.0"
+            }
+          },
+          "oci_crane_toolchains": {
+            "bzlFile": "@@rules_oci~//oci/private:toolchains_repo.bzl",
+            "ruleClassName": "toolchains_repo",
+            "attributes": {
+              "toolchain_type": "@rules_oci//oci:crane_toolchain_type",
+              "toolchain": "@oci_crane_{platform}//:crane_toolchain"
+            }
+          },
+          "oci_regctl_darwin_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "darwin_amd64"
+            }
+          },
+          "oci_regctl_darwin_arm64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "darwin_arm64"
+            }
+          },
+          "oci_regctl_linux_arm64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "linux_arm64"
+            }
+          },
+          "oci_regctl_linux_s390x": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "linux_s390x"
+            }
+          },
+          "oci_regctl_linux_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "linux_amd64"
+            }
+          },
+          "oci_regctl_windows_amd64": {
+            "bzlFile": "@@rules_oci~//oci:repositories.bzl",
+            "ruleClassName": "regctl_repositories",
+            "attributes": {
+              "platform": "windows_amd64"
+            }
+          },
+          "oci_regctl_toolchains": {
+            "bzlFile": "@@rules_oci~//oci/private:toolchains_repo.bzl",
+            "ruleClassName": "toolchains_repo",
+            "attributes": {
+              "toolchain_type": "@rules_oci//oci:regctl_toolchain_type",
+              "toolchain": "@oci_regctl_{platform}//:regctl_toolchain"
+            }
+          }
+        },
+        "moduleExtensionMetadata": {
+          "explicitRootModuleDirectDeps": [
+            "eclipse_temurin_17",
+            "eclipse_temurin_17_linux_amd64",
+            "ubuntu_24_04",
+            "ubuntu_24_04_linux_amd64"
+          ],
+          "explicitRootModuleDirectDevDeps": [],
+          "useAllRepos": "NO",
+          "reproducible": false
+        },
+        "recordedRepoMappingEntries": [
+          [
+            "aspect_bazel_lib~",
+            "bazel_tools",
+            "bazel_tools"
+          ],
+          [
+            "bazel_features~",
+            "bazel_tools",
+            "bazel_tools"
+          ],
+          [
+            "rules_oci~",
+            "aspect_bazel_lib",
+            "aspect_bazel_lib~"
+          ],
+          [
+            "rules_oci~",
+            "bazel_features",
+            "bazel_features~"
+          ],
+          [
+            "rules_oci~",
+            "bazel_skylib",
+            "bazel_skylib~"
+          ]
+        ]
+      }
+    },
     "@@rules_scala~//scala/extensions:config.bzl%scala_config": {
       "general": {
         "bzlTransitiveDigest": "TdBxhkZTM7VU6teIFS+KoonKU7wmb5BL7leCWWx7yX8=",
@@ -1293,7 +1559,7 @@
     },
     "@@rules_scala~//scala/extensions:deps.bzl%scala_deps": {
       "general": {
-        "bzlTransitiveDigest": "F2PMm61fmZ/IE+VSw1rigJ71hBDD7k3vqyYR1/GgXeA=",
+        "bzlTransitiveDigest": "5SDZrXQHW6tI/VEw+La2OPOK4ZWm0LGTxnChXOXBCag=",
         "usagesDigest": "kwo8oolISmSSITnit4b4S0vBiUtHlHK0WLDUwScxmOg=",
         "recordedFileInputs": {},
         "recordedDirentsInputs": {},
@@ -4904,85 +5170,6 @@
           ]
         ]
       }
-    },
-    "@@toolchains_llvm~//toolchain/extensions:llvm.bzl%llvm": {
-      "general": {
-        "bzlTransitiveDigest": "afRF0aFOIUrkYl3o040WQ606ep1qciEXzjnAxT3Kek8=",
-        "usagesDigest": "sYVuhiCAQehFTnGTv0bNtTBR4WorebpWBNxF0mRusyw=",
-        "recordedFileInputs": {},
-        "recordedDirentsInputs": {},
-        "envVariables": {},
-        "generatedRepoSpecs": {
-          "llvm_toolchain_llvm": {
-            "bzlFile": "@@toolchains_llvm~//toolchain:rules.bzl",
-            "ruleClassName": "llvm",
-            "attributes": {
-              "alternative_llvm_sources": [],
-              "auth_patterns": {},
-              "distribution": "auto",
-              "exec_arch": "",
-              "exec_os": "",
-              "libclang_rt": {},
-              "llvm_mirror": "",
-              "llvm_version": "20.1.2",
-              "llvm_versions": {},
-              "netrc": "",
-              "sha256": {},
-              "strip_prefix": {},
-              "urls": {}
-            }
-          },
-          "llvm_toolchain": {
-            "bzlFile": "@@toolchains_llvm~//toolchain:rules.bzl",
-            "ruleClassName": "toolchain",
-            "attributes": {
-              "absolute_paths": false,
-              "archive_flags": {},
-              "compile_flags": {},
-              "conly_flags": {},
-              "coverage_compile_flags": {},
-              "coverage_link_flags": {},
-              "cxx_builtin_include_directories": {},
-              "cxx_flags": {},
-              "cxx_standard": {},
-              "dbg_compile_flags": {},
-              "exec_arch": "",
-              "exec_os": "",
-              "extra_exec_compatible_with": {},
-              "extra_target_compatible_with": {},
-              "link_flags": {},
-              "link_libs": {},
-              "llvm_versions": {
-                "": "20.1.2"
-              },
-              "opt_compile_flags": {},
-              "opt_link_flags": {},
-              "stdlib": {},
-              "target_settings": {},
-              "unfiltered_compile_flags": {},
-              "toolchain_roots": {},
-              "sysroot": {}
-            }
-          }
-        },
-        "recordedRepoMappingEntries": [
-          [
-            "toolchains_llvm~",
-            "bazel_skylib",
-            "bazel_skylib~"
-          ],
-          [
-            "toolchains_llvm~",
-            "bazel_tools",
-            "bazel_tools"
-          ],
-          [
-            "toolchains_llvm~",
-            "toolchains_llvm",
-            "toolchains_llvm~"
-          ]
-        ]
-      }
     }
   }
 }

ci/BUILD.bazel

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

ci/unity_version.sh

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

docker-compose.prod.yml

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

docs/COMMAND_PROTO_USAGE_ANALYSIS.md

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

docs/DEPROTO_PLAN.md

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

docs/PRODUCTIONIZATION.md

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

go.mod

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

go.sum

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

maven_install.json

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

scripts/build_mac_plugin.sh

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

scripts/build_plugins.sh

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

scripts/dlSettings.sh

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

scripts/downloadTsvs.sh

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

scripts/generate_changelog.sh

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

scripts/pre-commit-gazelle.sh

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

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

@@ -18,11 +18,31 @@ static inline auto MixIn(uint64_t& hash, const uint8_t byte) {
 }
 
 // Hash an entire buffer using FNV-1a
+// Fast word-at-a-time implementation - processes 8 bytes at once for better performance
+// while maintaining good distribution properties for hash table use
 static inline auto HashBuffer(const uint8_t* data, size_t size) -> uint64_t {
+    if (data == nullptr) { return FNV_OFFSET_BASIS; }
+
     uint64_t hash = FNV_OFFSET_BASIS;
-    if (data != nullptr) {
-        for (size_t i = 0; i < size; ++i) { MixIn(hash, data[i]); }
+    const uint8_t* end = data + size;
+
+    // Process 8 bytes at a time
+    while (data + 8 <= end) {
+        uint64_t word;
+        // Use memcpy to avoid alignment issues and let compiler optimize
+        __builtin_memcpy(&word, data, sizeof(word));
+        hash ^= word;
+        hash *= FNV_PRIME;
+        data += 8;
     }
+
+    // Process remaining bytes
+    while (data < end) {
+        hash ^= static_cast<uint64_t>(*data);
+        hash *= FNV_PRIME;
+        data++;
+    }
+
     return hash;
 }
 

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

@@ -30,7 +30,7 @@ auto rloc(const string& execPath) -> string {
     const std::unique_ptr<Runfiles> runfiles(Runfiles::Create(execPath, &error));
 
     if (runfiles == nullptr) {
-        printf("Error! %s\n", error.c_str());
+        fprintf(stderr, "Error! %s\n", error.c_str());
         abort();
         // error handling
     }
@@ -67,9 +67,9 @@ auto FilesystemUtils::MapFilesDirectory() -> string {
 
 void FilesystemUtils::MakeDirectoryIfNecessary(const string& directoryPath) {
     if (fs::create_directories(directoryPath))
-        printf("Directory %s created\n", directoryPath.c_str());
+        fprintf(stderr, "Directory %s created\n", directoryPath.c_str());
     else
-        printf("No new directory created for %s\n", directoryPath.c_str());
+        fprintf(stderr, "No new directory created for %s\n", directoryPath.c_str());
 }
 
 auto FilesystemUtils::SaveFilesDirectory() -> string {
@@ -129,11 +129,11 @@ auto FilesystemUtils::AtomicallySaveToPath(const string& path, const byte_vector
     if (ostr.good()) {
         const int err = rename(tempPath.c_str(), path.c_str());
         if (err == -1) {
-            printf("Failed to move file to %s! Errno %d\n", path.c_str(), errno);
+            fprintf(stderr, "Failed to move file to %s! Errno %d\n", path.c_str(), errno);
             return false;
         }
     } else {
-        printf("Failed writing to %s!\n", tempPath.c_str());
+        fprintf(stderr, "Failed writing to %s!\n", tempPath.c_str());
         return false;
     }
 

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

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

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

@@ -0,0 +1,139 @@
+# MCTS (Monte Carlo Tree Search) Framework
+
+This directory contains a game-agnostic Monte Carlo Tree Search implementation that can be used with any turn-based game. The framework separates the MCTS algorithm from game-specific logic through abstract interfaces.
+
+## Core Abstract Classes
+
+### `MCTSAction` (abstract/MCTSAction.hpp)
+Abstract interface for representing game actions/moves.
+
+**Key Methods:**
+- `getIndex()` - Returns the action's unique identifier
+- `getDescription()` - Human-readable description for debugging/logging
+- `clone()` - Creates a deep copy of the action
+- `equals()` - Compares actions for equality
+
+### `MCTSGameState` (abstract/MCTSGameState.hpp)
+Abstract interface for representing game states.
+
+**Key Methods:**
+- `hash()` - Returns a hash for transposition table lookups
+- `score(playerId)` - Evaluates the state's value for a given player
+- `currentPlayerId()` - Returns whose turn it is
+- `isTerminal()` - Checks if the game has ended
+- `getWinner()` - Returns the winning player (if terminal)
+- `clone()` - Creates a deep copy of the state
+- `equals()` - Compares states for equality
+
+### `MCTSGameEngine` (abstract/MCTSGameEngine.hpp)
+Abstract interface for game rule enforcement and state transitions. Many methods have efficient default implementations.
+
+**Must Override (Pure Virtual):**
+- `applyAction(state, action)` - Applies an action to create a new state
+- `getLegalActions(state)` - Returns all valid moves from a state
+- `isTerminal(state)` - Checks if a state is game-ending
+- `evaluateState(state, playerId)` - Scores a state for a player
+
+**Optional Overrides (Have Default Implementations):**
+- `applyActionMutable(state, action)` - Apply action in-place for efficiency (default: calls applyAction)
+- `filterActions(actions, state)` - Applies heuristic filtering (default: no filtering)
+- `simulateRandomPlayout(state, playerId, maxDepth, policy)` - Runs simulation (default: efficient mutable implementation)
+- `getActionScore(state, action, playerId)` - Scores an action (default: apply and evaluate)
+- `shouldStopSearch(state, iterations, startTime)` - Early termination (default: no early stop)
+
+**Performance Features:**
+- The default `simulateRandomPlayout` clones the state once and mutates it throughout simulation for efficiency
+- Games can override `applyActionMutable` to provide even more efficient in-place updates
+- Games can override `simulateRandomPlayout` for custom optimizations (e.g., using internal engine state)
+
+## MCTS Algorithm Implementation
+
+### `AbstractMCTSAI` (abstract/AbstractMCTSAI.hpp)
+The main MCTS algorithm implementation that works with any game implementing the abstract interfaces.
+
+**Key Features:**
+- **Selection**: Uses UCB1 (Upper Confidence Bound) for node selection
+- **Expansion**: Adds new nodes to the search tree
+- **Simulation**: Runs random playouts to estimate node values
+- **Backpropagation**: Updates node statistics with simulation results
+- **Multithreading**: Supports parallel MCTS with configurable thread count
+- **Path Compression**: Optimizes move sequences for better performance
+
+**Configuration Options:**
+- `explorationConstant` - UCB1 exploration parameter (default: √2)
+- `maxSimulationDepth` - Maximum depth for random playouts
+- `maxTreeDepth` - Maximum tree depth to prevent stack overflow
+- `useMultithreading` - Enable parallel search
+- `numThreads` - Number of worker threads
+- `simulationPolicy` - Strategy for action selection during simulation
+
+### `MCTSNode` (abstract/MCTSNode.hpp)
+Represents nodes in the MCTS search tree.
+
+**Core Data:**
+- `action` - The action that led to this node
+- `actionIndex` - Index in the original actions array
+- `gameState` - The game state at this node
+- `visitCount` - Number of times this node was visited
+- `totalReward` - Sum of simulation rewards
+- `averageReward` - Average reward (totalReward / visitCount)
+- `children` - Child nodes in the search tree
+- `parent` - Parent node reference
+
+**Key Methods:**
+- `CanExpand()` - Checks if node has untried actions
+- `GetBestChild(explorationConstant)` - UCB1-based child selection
+- `GetBestFinalChild()` - Most-visited child (for final move selection)
+- `CalculateUCB1(explorationConstant)` - Computes UCB1 value
+
+## Simulation Policies
+
+The framework supports multiple strategies for action selection during random playouts:
+
+- **RANDOM** - Uniform random selection
+- **FILTERED_RANDOM** - Random selection from filtered action set
+- **BEST_IMMEDIATE** - Always choose the highest-scoring immediate action
+- **WEIGHTED_BEST_IMMEDIATE** - Weighted random selection based on action scores
+
+## Type Definitions
+
+### `MCTSTypes` (abstract/MCTSTypes.hpp)
+- `MCTSPlayerId` - Player identifier type (int)
+- `MCTSSimulationPolicy` - Enumeration of simulation strategies
+- `MCTSConfig` - Configuration structure for MCTS parameters
+
+## Usage Pattern
+
+To use this framework with your game:
+
+1. **Implement the abstract interfaces** for your game:
+   ```cpp
+   class MyGameAction : public MCTSAction { /* ... */ };
+   class MyGameState : public MCTSGameState { /* ... */ };
+   class MyGameEngine : public MCTSGameEngine { /* ... */ };
+   ```
+
+2. **Create and configure the AI**:
+   ```cpp
+   MCTSConfig config;
+   config.explorationConstant = 1.414;
+   config.maxSimulationDepth = 100;
+   AbstractMCTSAI ai(playerId, config);
+   ```
+
+3. **Run the search**:
+   ```cpp
+   auto actions = engine.getLegalActions(currentState);
+   auto result = ai.Search(engine, currentState, actions, timeLimit);
+   auto bestAction = actions[result.bestActionIndex];
+   ```
+
+## Testing
+
+The framework includes comprehensive tests using a Tic-Tac-Toe implementation:
+- `MockTicTacToe.hpp` - Example implementation of all abstract interfaces
+- `AbstractMCTSAI_test.cpp` - Unit tests for the core algorithm
+- `MCTSIntegration_test.cpp` - Integration tests with complete games
+- `MCTSNode_test.cpp` - Tests for the node data structure
+
+This demonstrates how to implement the interfaces and validates that the MCTS algorithm works correctly with any turn-based game.

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

@@ -0,0 +1,106 @@
+//
+// Abstract MCTS AI implementation - game agnostic
+//
+
+#ifndef EAGLE0_ABSTRACT_MCTSAI_HPP
+#define EAGLE0_ABSTRACT_MCTSAI_HPP
+
+#include <chrono>
+#include <memory>
+#include <unordered_map>
+#include <vector>
+
+#include "MCTSAction.hpp"
+#include "MCTSGameEngine.hpp"
+#include "MCTSGameState.hpp"
+#include "MCTSNode.hpp"
+#include "MCTSTypes.hpp"
+
+namespace shardok {
+namespace mcts {
+
+class AbstractMCTSAI {
+public:
+    // Search result structure
+    struct SearchResult {
+        size_t bestActionIndex = 0;
+        double bestScore = 0.0;
+        int searchDepth = 0;
+        int nodesEvaluated = 0;
+        std::chrono::milliseconds searchTime{0};
+        bool foundWinningMove = false;
+    };
+
+    explicit AbstractMCTSAI(MCTSPlayerId playerId, MCTSConfig config = MCTSConfig{});
+
+    // Main search interface
+    [[nodiscard]] auto Search(
+            const MCTSGameEngine& engine,
+            const MCTSGameState& initialState,
+            std::chrono::milliseconds timeLimit) const -> SearchResult;
+
+    // Configuration
+    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return config_; }
+    void SetConfig(const MCTSConfig& newConfig) { config_ = newConfig; }
+
+    [[nodiscard]] auto FindNodeAtDepthWithHash(
+            const MCTSNode* root,
+            int maxDepth,
+            uint64_t targetHash) -> const MCTSNode*;
+
+private:
+    MCTSPlayerId playerId_;
+    MCTSConfig config_;
+
+    // Transposition table: maps state hash -> minimum depth at which state was reached
+    // Used to detect and penalize longer paths to the same game state
+    // Cleared at the start of each Search() call
+    mutable std::unordered_map<uint64_t, int> transpositionTable_;
+
+    // Core MCTS algorithm
+    [[nodiscard]] auto BuildMCTSTree(
+            const MCTSGameEngine& engine,
+            const MCTSGameState& initialState,
+            std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode>;
+
+    // MCTS phases
+    [[nodiscard]] auto MCTSSelection(MCTSNode* root) const -> MCTSNode*;
+
+    [[nodiscard]] auto MCTSExpansion(MCTSNode* node, const MCTSGameEngine& engine) const
+            -> MCTSNode*;
+
+    [[nodiscard]] auto MCTSSimulation(
+            const MCTSGameEngine& engine,
+            const MCTSGameState& state,
+            MCTSPlayerId startingPlayer,
+            int startingPlayerFlips = 0) const -> double;
+
+    auto MCTSBackpropagation(MCTSNode* node, double reward, MCTSBackpropagationPolicy policy) const
+            -> void;
+
+    // Helper functions
+    [[nodiscard]] auto SelectSimulationAction(
+            const MCTSGameEngine& engine,
+            const MCTSGameState& state,
+            const std::vector<std::unique_ptr<MCTSAction>>& actions,
+            bool isMaximizing) const -> size_t;
+
+    // Logging
+    static auto LogSearchResults(
+            const MCTSNode* rootNode,
+            const MCTSNode* bestChild,
+            const SearchResult& result) -> void;
+
+    // Debug tree dumping
+    static auto DumpTreeToFile(const MCTSNode* root, const std::string& filepath) -> void;
+
+private:
+    static auto
+    DumpNodeRecursive(const MCTSNode* node, std::ostream& out, int indentLevel, bool isLastChild)
+            -> void;
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_ABSTRACT_MCTSAI_HPP

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

@@ -0,0 +1,94 @@
+load("//tools:copts.bzl", "COPTS")
+
+cc_library(
+    name = "mcts_types",
+    hdrs = ["MCTSTypes.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+)
+
+cc_library(
+    name = "mcts_action",
+    hdrs = ["MCTSAction.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+)
+
+cc_library(
+    name = "mcts_game_state",
+    hdrs = ["MCTSGameState.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+    deps = [
+        ":mcts_types",
+    ],
+)
+
+cc_library(
+    name = "mcts_game_engine",
+    srcs = ["MCTSGameEngine.cpp"],
+    hdrs = ["MCTSGameEngine.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+    deps = [
+        ":mcts_action",
+        ":mcts_game_state",
+        ":mcts_types",
+    ],
+)
+
+cc_library(
+    name = "mcts_node",
+    hdrs = ["MCTSNode.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+    deps = [
+        ":mcts_action",
+        ":mcts_game_state",
+        ":mcts_types",
+    ],
+)
+
+cc_library(
+    name = "abstract_mcts_ai",
+    srcs = ["AbstractMCTSAI.cpp"],
+    hdrs = ["AbstractMCTSAI.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
+    ],
+    deps = [
+        ":mcts_action",
+        ":mcts_game_engine",
+        ":mcts_game_state",
+        ":mcts_node",
+        ":mcts_types",
+        "//src/main/cpp/net/eagle0/common/mcts/util:tree_indent_util",
+    ],
+)
+
+# Individual targets are exposed above - no need for a catch-all target
+# Each component should be imported explicitly by its consumers

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

@@ -0,0 +1,40 @@
+//
+// Abstract action interface for MCTS
+//
+
+#ifndef EAGLE0_MCTS_ACTION_HPP
+#define EAGLE0_MCTS_ACTION_HPP
+
+#include <memory>
+#include <string>
+
+namespace shardok {
+namespace mcts {
+
+// Abstract interface for game actions
+class MCTSAction {
+public:
+    virtual ~MCTSAction() = default;
+
+    // Get a unique index for this action (used for command indexing)
+    [[nodiscard]] virtual size_t getIndex() const = 0;
+
+    // Get a human-readable description for debugging/logging
+    [[nodiscard]] virtual std::string getDescription() const = 0;
+
+    // Create a deep copy of this action
+    [[nodiscard]] virtual std::unique_ptr<MCTSAction> clone() const = 0;
+
+    // Check if two actions are equivalent
+    [[nodiscard]] virtual bool equals(const MCTSAction& other) const = 0;
+
+    // Check if this action requires a chance node (binary success/failure outcome)
+    // Examples: START_FIRE, RAISE_DEAD, EXTINGUISH_FIRE
+    // If true, the game engine should provide outcome probabilities
+    [[nodiscard]] virtual bool requiresChanceNode() const = 0;
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_MCTS_ACTION_HPP

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

@@ -0,0 +1,148 @@
+//
+// Default implementations for MCTSGameEngine
+//
+
+#include "MCTSGameEngine.hpp"
+
+#include <algorithm>
+#include <limits>
+#include <random>
+#include <vector>
+
+#include "MCTSTypes.hpp"  // For MCTSInternalError
+
+namespace shardok {
+namespace mcts {
+
+double MCTSGameEngine::simulateRandomPlayout(
+        const MCTSGameState& state,
+        MCTSPlayerId playerId,
+        int maxDepth,
+        MCTSSimulationPolicy policy) const {
+    // Clone state once and mutate it throughout simulation for efficiency
+    auto currentState = state.clone();
+    int depth = 0;
+
+    // Use thread-local random generator for thread safety
+    static thread_local std::mt19937 gen(std::random_device{}());
+
+    // Simulate until terminal or max depth
+    while (!currentState->isTerminal() && depth < maxDepth) {
+        auto actions = getLegalActions(*currentState, playerId, 0, 0);
+        if (actions.empty()) { break; }
+
+        size_t selectedIndex = 0;
+
+        // Select action based on policy
+        switch (policy) {
+            case MCTSSimulationPolicy::RANDOM: {
+                std::uniform_int_distribution<> dis(0, actions.size() - 1);
+                selectedIndex = dis(gen);
+                break;
+            }
+
+            case MCTSSimulationPolicy::FILTERED_RANDOM: {
+                auto filteredIndices = filterActions(actions, *currentState);
+                if (!filteredIndices.empty()) {
+                    std::uniform_int_distribution<> dis(0, filteredIndices.size() - 1);
+                    selectedIndex = filteredIndices[dis(gen)];
+                } else {
+                    // Fall back to random if no actions pass filter
+                    std::uniform_int_distribution<> dis(0, actions.size() - 1);
+                    selectedIndex = dis(gen);
+                }
+                break;
+            }
+
+            case MCTSSimulationPolicy::BEST_IMMEDIATE: {
+                double bestScore = -std::numeric_limits<double>::infinity();
+                for (size_t i = 0; i < actions.size(); ++i) {
+                    double score = getActionScore(
+                            *currentState,
+                            *actions[i],
+                            currentState->currentPlayerId());
+                    if (score > bestScore) {
+                        bestScore = score;
+                        selectedIndex = i;
+                    }
+                }
+                break;
+            }
+
+            case MCTSSimulationPolicy::WEIGHTED_BEST_IMMEDIATE: {
+                // Score all actions and weight by ranking
+                std::vector<std::pair<size_t, double>> scores;
+                scores.reserve(actions.size());
+
+                for (size_t i = 0; i < actions.size(); ++i) {
+                    double score = getActionScore(
+                            *currentState,
+                            *actions[i],
+                            currentState->currentPlayerId());
+                    scores.emplace_back(i, score);
+                }
+
+                // Sort by score (descending)
+                std::sort(scores.begin(), scores.end(), [](const auto& a, const auto& b) {
+                    return a.second > b.second;
+                });
+
+                // Create weights based on ranking (1/rank)
+                std::vector<double> weights;
+                weights.reserve(scores.size());
+                for (size_t i = 0; i < scores.size(); ++i) { weights.push_back(1.0 / (i + 1.0)); }
+
+                // Select based on weights
+                std::discrete_distribution<> dis(weights.begin(), weights.end());
+                selectedIndex = scores[dis(gen)].first;
+                break;
+            }
+
+            case MCTSSimulationPolicy::WEIGHTED_HEURISTIC: {
+                // Get heuristic weights (fast O(1) per action)
+                const auto weights = getActionWeights(actions, *currentState);
+
+                // Filter out zero-weight actions
+                std::vector<size_t> validIndices;
+                std::vector<double> validWeights;
+                validIndices.reserve(actions.size());
+                validWeights.reserve(actions.size());
+
+                for (size_t i = 0; i < weights.size() && i < actions.size(); ++i) {
+                    if (weights[i] > 0.0) {
+                        validIndices.push_back(i);
+                        validWeights.push_back(weights[i]);
+                    }
+                }
+
+                // If all actions filtered out, this is a bug in the weighting logic
+                if (validWeights.empty()) {
+                    throw MCTSInternalError(
+                            "MCTS simulation (playout): All actions have zero weight in "
+                            "WEIGHTED_HEURISTIC policy (action count: " +
+                            std::to_string(actions.size()) +
+                            ") - this indicates incorrect weighting");
+                }
+
+                // Select based on heuristic weights
+                std::discrete_distribution<> dis(validWeights.begin(), validWeights.end());
+                selectedIndex = validIndices[dis(gen)];
+                break;
+            }
+        }
+
+        // Apply selected action using mutable version for efficiency
+        applyActionMutable(currentState, *actions[selectedIndex]);
+        if (!currentState) {
+            break;  // Failed to apply action
+        }
+
+        depth++;
+    }
+
+    // Return evaluation from original player's perspective
+    return evaluateState(*currentState, playerId);
+}
+
+}  // namespace mcts
+}  // namespace shardok

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

@@ -0,0 +1,161 @@
+//
+// Abstract game engine interface for MCTS
+//
+
+#ifndef EAGLE0_MCTS_GAME_ENGINE_HPP
+#define EAGLE0_MCTS_GAME_ENGINE_HPP
+
+#include <chrono>
+#include <memory>
+#include <vector>
+
+#include "MCTSAction.hpp"
+#include "MCTSGameState.hpp"
+#include "MCTSTypes.hpp"
+
+namespace shardok {
+namespace mcts {
+
+// Information about chance outcomes (supports both binary and multi-outcome)
+struct ChanceOutcomeInfo {
+    std::vector<double> probabilities;  // Probability of each outcome (must sum to 1.0)
+    std::vector<double> rolls;          // Roll values for each outcome
+
+    // Factory for binary success/failure outcomes (e.g., START_FIRE)
+    [[nodiscard]] static ChanceOutcomeInfo binary(double successProbability) {
+        // -100: triggers open-ended low sequence, succeeds against any threshold
+        // 150: triggers open-ended high sequence, fails against any threshold
+        return {{successProbability, 1.0 - successProbability}, {-100.0, 150.0}};
+    }
+
+    // Factory for multi-outcome with fixed seeds (e.g., END_TURN)
+    // Uses uniformly distributed roll values to sample different random outcomes
+    [[nodiscard]] static ChanceOutcomeInfo multiOutcome(int numOutcomes) {
+        std::vector<double> probs(numOutcomes, 1.0 / numOutcomes);
+        std::vector<double> rollValues;
+        rollValues.reserve(numOutcomes);
+        // Spread rolls across the percentile range: 10, 30, 50, 70, 90 for 5 outcomes
+        for (int i = 0; i < numOutcomes; ++i) {
+            rollValues.push_back(10.0 + (80.0 * i) / (numOutcomes - 1));
+        }
+        return {probs, rollValues};
+    }
+
+    [[nodiscard]] const std::vector<double>& getRepresentativeRolls() const { return rolls; }
+
+    [[nodiscard]] const std::vector<double>& getProbabilities() const { return probabilities; }
+};
+
+// Backward compatibility alias
+using BinaryOutcomeInfo = ChanceOutcomeInfo;
+
+// Abstract interface for game engines
+class MCTSGameEngine {
+public:
+    virtual ~MCTSGameEngine() = default;
+
+    // Apply an action to a state and return the resulting state
+    // If deterministicRoll is provided (0.0-100.0), use that for any random outcomes
+    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> applyAction(
+            const MCTSGameState& state,
+            const MCTSAction& action,
+            double deterministicRoll = -1.0) const = 0;
+
+    // Apply an action to a mutable state in-place (for efficient simulation)
+    // Default: clone, apply, and move the result back
+    // Override this for better performance
+    virtual void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
+            const {
+        state = applyAction(*state, action);
+    }
+
+    // Get all legal actions for the current state with player flip tracking
+    // Default implementation ignores flip tracking and calls base version
+    [[nodiscard]] virtual std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
+            const MCTSGameState& state,
+            MCTSPlayerId /*rootPlayerId*/,
+            int /*currentPlayerFlips*/,
+            int /*maxPlayerFlips*/) const = 0;
+
+    // Check if a state is terminal
+    [[nodiscard]] virtual bool isTerminal(const MCTSGameState& state) const = 0;
+
+    // Evaluate a state from the perspective of a player
+    [[nodiscard]] virtual double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
+            const = 0;
+
+    // Filter actions based on game-specific heuristics
+    // Returns indices of actions to keep
+    // Default: no filtering (return all indices)
+    [[nodiscard]] virtual std::vector<size_t> filterActions(
+            const std::vector<std::unique_ptr<MCTSAction>>& actions,
+            const MCTSGameState& /*state*/) const {
+        std::vector<size_t> indices;
+        indices.reserve(actions.size());
+        for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
+        return indices;
+    }
+
+    // Get heuristic weights for actions (used by WEIGHTED_HEURISTIC simulation policy)
+    // Returns weights corresponding to each action (same size as actions vector)
+    // Weight of 0.0 = never select, higher = more likely to select
+    // Default: uniform weights (all actions equally likely)
+    [[nodiscard]] virtual std::vector<double> getActionWeights(
+            const std::vector<std::unique_ptr<MCTSAction>>& actions,
+            const MCTSGameState& /*state*/) const {
+        // Default: uniform weights
+        return std::vector<double>(actions.size(), 1.0);
+    }
+
+    // Simulate a random playout from the given state
+    // Default implementation uses policy to select actions
+    [[nodiscard]] virtual double simulateRandomPlayout(
+            const MCTSGameState& state,
+            MCTSPlayerId playerId,
+            int maxDepth,
+            MCTSSimulationPolicy policy) const;
+
+    // Get the immediate score of applying an action
+    // Default: apply the action and evaluate the resulting state
+    [[nodiscard]] virtual double getActionScore(
+            const MCTSGameState& state,
+            const MCTSAction& action,
+            MCTSPlayerId playerId) const {
+        auto newState = applyAction(state, action);
+        if (!newState) { return 0.0; }
+        return evaluateState(*newState, playerId);
+    }
+
+    // Check if we should stop searching (e.g., time limit, found winning move)
+    [[nodiscard]] virtual bool shouldStopSearch(
+            const MCTSGameState& /*state*/,
+            int /*iterations*/,
+            std::chrono::steady_clock::time_point /*startTime*/) const {
+        // Default: no early stopping
+        return false;
+    }
+
+    // Map a filtered action index back to the original unfiltered index
+    // This is needed when getLegalActions() applies filtering - the returned actions
+    // may be a subset of all available actions, and this maps back to the original index.
+    // Default implementation: no filtering, so filtered index = original index
+    [[nodiscard]] virtual size_t mapFilteredIndexToOriginal(
+            size_t filteredIndex,
+            const MCTSGameState& state) const {
+        // Default: no filtering, index stays the same
+        (void)state;  // Suppress unused parameter warning
+        return filteredIndex;
+    }
+
+    // Get binary outcome information for an action that requires a chance node
+    // Only called for actions where action.requiresChanceNode() returns true
+    // Returns success probability for binary success/failure actions
+    [[nodiscard]] virtual BinaryOutcomeInfo getBinaryOutcomeInfo(
+            const MCTSGameState& state,
+            const MCTSAction& action) const = 0;
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_MCTS_GAME_ENGINE_HPP

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

@@ -0,0 +1,50 @@
+//
+// Abstract game state interface for MCTS
+//
+
+#ifndef EAGLE0_MCTS_GAME_STATE_HPP
+#define EAGLE0_MCTS_GAME_STATE_HPP
+
+#include <cstdint>
+#include <memory>
+#include <string>
+
+#include "MCTSTypes.hpp"
+
+namespace shardok {
+namespace mcts {
+
+// Abstract interface for game states
+class MCTSGameState {
+public:
+    virtual ~MCTSGameState() = default;
+
+    // Compute hash for transposition table
+    [[nodiscard]] virtual uint64_t hash() const = 0;
+
+    // Evaluate the state from the perspective of the given player
+    [[nodiscard]] virtual double score(MCTSPlayerId playerId) const = 0;
+
+    // Get the player whose turn it is
+    [[nodiscard]] virtual MCTSPlayerId currentPlayerId() const = 0;
+
+    // Check if the game has ended
+    [[nodiscard]] virtual bool isTerminal() const = 0;
+
+    // Create a deep copy of the state
+    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> clone() const = 0;
+
+    // Check if two states are equivalent
+    [[nodiscard]] virtual bool equals(const MCTSGameState& other) const = 0;
+
+    // Get winner if terminal, or -1 if not terminal or draw
+    [[nodiscard]] virtual MCTSPlayerId getWinner() const = 0;
+
+    // Optional: Get a string representation for debugging
+    [[nodiscard]] virtual std::string toString() const { return "MCTSGameState"; }
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_MCTS_GAME_STATE_HPP

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

@@ -0,0 +1,277 @@
+//
+// Abstract MCTS Node structure for game-agnostic implementation
+//
+
+#ifndef EAGLE0_ABSTRACT_MCTSNODE_HPP
+#define EAGLE0_ABSTRACT_MCTSNODE_HPP
+
+#include <cmath>
+#include <limits>
+#include <memory>
+#include <vector>
+
+#include "MCTSAction.hpp"
+#include "MCTSGameState.hpp"
+#include "MCTSTypes.hpp"
+
+namespace shardok {
+namespace mcts {
+
+// Node type for MCTS tree
+enum class NodeType {
+    DECISION,  // Player chooses an action (standard MCTS node)
+    CHANCE     // Nature determines outcome (for probabilistic actions)
+};
+
+// Abstract MCTS Node structure
+struct MCTSNode {
+    // Node type
+    NodeType nodeType = NodeType::DECISION;
+    // Action information
+    std::unique_ptr<MCTSAction> action;  // The action that led to this node (null for root)
+    size_t actionIndex = SIZE_MAX;       // Index in the original actions array (SIZE_MAX for root)
+
+    // Score information
+    double immediateScore = 0.0;
+    double lookaheadScore = 0.0;
+
+    // Game state after this action
+    std::unique_ptr<MCTSGameState> gameState;
+
+    // MCTS statistics
+    int visitCount = 0;
+    double totalReward = 0.0;
+    double averageReward = 0.0;
+    mutable double ucb1Value = 0.0;
+    double actionWeight = 1.0;  // Prior probability/weight for this action (from heuristics)
+
+    // Tree structure
+    std::vector<std::unique_ptr<MCTSNode>> children;
+    size_t nextUntriedActionIndex = 0;  // Next action to expand
+    size_t totalActions = 0;            // Total number of available actions
+    MCTSNode* parent = nullptr;
+
+    // Chance node specific fields (only used when nodeType == CHANCE)
+    std::vector<double> outcomeProbabilities;  // Probability of each outcome
+    std::vector<double> outcomeRolls;          // Representative roll for each outcome
+
+    // Game context
+    MCTSPlayerId playerId;
+    int depth = 0;
+    bool isTerminal = false;
+    int playerFlips = 0;  // Number of times the active player has changed from root player
+    bool isMaximizingPlayer = true;  // True if this node is maximizing for root player
+
+    // Transposition detection
+    uint64_t stateHash = 0;
+    bool isRedundant = false;  // True if this node represents a duplicate state
+
+    // Constructor for root node
+    MCTSNode(std::unique_ptr<MCTSGameState> state, MCTSPlayerId pid, int d)
+        : gameState(std::move(state)),
+          playerId(pid),
+          depth(d),
+          playerFlips(0),
+          isMaximizingPlayer(true) {
+        if (gameState) {
+            stateHash = gameState->hash();
+            isTerminal = gameState->isTerminal();
+        }
+    }
+
+    // Constructor for child node
+    MCTSNode(
+            std::unique_ptr<MCTSAction> act,
+            std::unique_ptr<MCTSGameState> state,
+            MCTSPlayerId pid,
+            int d,
+            size_t actIdx = SIZE_MAX,
+            int flips = 0,
+            bool isMaximizing = true,
+            double weight = 1.0)
+        : action(std::move(act)),
+          actionIndex(actIdx),
+          gameState(std::move(state)),
+          actionWeight(weight),
+          playerId(pid),
+          depth(d),
+          playerFlips(flips),
+          isMaximizingPlayer(isMaximizing) {
+        if (gameState) {
+            stateHash = gameState->hash();
+            isTerminal = gameState->isTerminal();
+        }
+    }
+
+    // Iterative destructor to avoid stack overflow with deep trees
+    ~MCTSNode() {
+        std::vector<std::unique_ptr<MCTSNode>> nodesToDestroy;
+        nodesToDestroy.swap(children);
+
+        while (!nodesToDestroy.empty()) {
+            std::vector<std::unique_ptr<MCTSNode>> currentBatch;
+            currentBatch.swap(nodesToDestroy);
+
+            for (const auto& node : currentBatch) {
+                if (node && !node->children.empty()) {
+                    for (auto& child : node->children) {
+                        nodesToDestroy.push_back(std::move(child));
+                    }
+                    node->children.clear();
+                }
+            }
+        }
+    }
+
+    // Calculate UCB1 value for this node from parent's perspective
+    // Uses prior-weighted formula similar to AlphaGo:
+    //   UCB = Q + c * P * sqrt(N_parent) / (1 + N_child)
+    // Where P is the action weight (prior probability from heuristics)
+    [[nodiscard]] double CalculateUCB1(
+            const double explorationConstant,
+            const int parentVisitCount,
+            const bool parentIsMaximizing) const {
+        // Exploitation: use lookahead score (minimax value)
+        // For minimizing nodes, negate the score to prefer low child values
+        const double exploitationValue = parentIsMaximizing ? lookaheadScore : -lookaheadScore;
+
+        // Exploration: prior-weighted formula (AlphaGo-style)
+        // Actions with weight 0.0 (like FLEE_COMMAND) get no exploration bonus
+        // Unvisited nodes get: c * weight * sqrt(N_parent)
+        // This prevents bad actions from dominating exploration due to infinite UCB
+        const double explorationValue = explorationConstant * actionWeight *
+                                        std::sqrt(parentVisitCount) / (1.0 + visitCount);
+
+        return exploitationValue + explorationValue;
+    }
+
+    // Check if this node can be expanded
+    [[nodiscard]] bool CanExpand() const { return nextUntriedActionIndex < totalActions; }
+
+    // Check if this is a chance node
+    [[nodiscard]] bool IsChanceNode() const { return nodeType == NodeType::CHANCE; }
+
+    // Check if this is a decision node
+    [[nodiscard]] bool IsDecisionNode() const { return nodeType == NodeType::DECISION; }
+
+    // Get best child from chance node (probability-weighted selection)
+    // For chance nodes, we want to explore outcomes proportionally to their probability
+    [[nodiscard]] MCTSNode* GetBestChanceChild() const {
+        if (children.empty() || !IsChanceNode()) return nullptr;
+
+        // Find the outcome that is most under-explored relative to its probability
+        // Expected visits for outcome i: total_visits * probability[i]
+        // Actual visits: child[i]->visitCount
+        // Deficit: expected - actual
+        size_t bestIndex = 0;
+        double bestDeficit = -std::numeric_limits<double>::max();
+
+        for (size_t i = 0; i < children.size(); i++) {
+            if (!children[i] || children[i]->isRedundant) continue;
+
+            const double expectedVisits = visitCount * outcomeProbabilities[i];
+            const double actualVisits = static_cast<double>(children[i]->visitCount);
+            const double deficit = expectedVisits - actualVisits;
+
+            if (deficit > bestDeficit) {
+                bestDeficit = deficit;
+                bestIndex = i;
+            }
+        }
+
+        return children[bestIndex].get();
+    }
+
+    // Get best child based on UCB1
+    [[nodiscard]] MCTSNode* GetBestChild(const double explorationConstant) const {
+        if (children.empty()) return nullptr;
+
+        MCTSNode* bestChild = nullptr;
+        double bestValue = -std::numeric_limits<double>::max();
+
+        for (auto& child : children) {
+            // Skip redundant nodes
+            if (child->isRedundant) continue;
+
+            // Calculate UCB1 value using the helper function
+            const double value =
+                    child->CalculateUCB1(explorationConstant, visitCount, isMaximizingPlayer);
+
+            // Debug logging for UCB selection
+            static bool enableUCBDebug = false;
+            if (enableUCBDebug && child->visitCount > 0) {
+                const double exploitationValue =
+                        isMaximizingPlayer ? child->lookaheadScore : -child->lookaheadScore;
+                const double explorationValue =
+                        explorationConstant * std::sqrt(std::log(visitCount) / child->visitCount);
+                printf("    UCB: %s lookahead=%.2f expl=%.2f (+%.2f) = %.2f [%s]\n",
+                       isMaximizingPlayer ? "MAX" : "MIN",
+                       child->lookaheadScore,
+                       exploitationValue,
+                       explorationValue,
+                       value,
+                       child->action ? child->action->getDescription().c_str() : "root");
+            }
+
+            if (value > bestValue) {
+                bestValue = value;
+                bestChild = child.get();
+            }
+        }
+
+        return bestChild;
+    }
+
+    // Get best child based on visit count (for final selection)
+    [[nodiscard]] MCTSNode* GetBestFinalChild() const {
+        if (children.empty()) return nullptr;
+
+        MCTSNode* bestChild = nullptr;
+        int bestVisits = 0;
+        double bestScore = isMaximizingPlayer ? -std::numeric_limits<double>::max()
+                                              : std::numeric_limits<double>::max();
+
+        for (const auto& child : children) {
+            // Skip redundant nodes
+            if (child->isRedundant) continue;
+
+            // Prefer most-visited node (robust child selection)
+            if (child->visitCount > bestVisits) {
+                bestVisits = child->visitCount;
+                bestScore = child->lookaheadScore;
+                bestChild = child.get();
+            } else if (child->visitCount == bestVisits) {
+                // Tie-break on lookahead score (minimax value, not poisoned average)
+                // Maximizing: prefer higher score (better for root player)
+                // Minimizing: prefer lower score (worse for root player)
+                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
+                                                              : (child->lookaheadScore < bestScore);
+                if (shouldReplace) {
+                    bestScore = child->lookaheadScore;
+                    bestChild = child.get();
+                }
+            }
+        }
+
+        // If no child was visited, fall back to lookahead score
+        if (!bestChild && !children.empty()) {
+            for (const auto& child : children) {
+                if (child->isRedundant) continue;
+
+                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
+                                                              : (child->lookaheadScore < bestScore);
+                if (shouldReplace) {
+                    bestScore = child->lookaheadScore;
+                    bestChild = child.get();
+                }
+            }
+        }
+
+        return bestChild;
+    }
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_ABSTRACT_MCTSNODE_HPP

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

@@ -0,0 +1,60 @@
+//
+// Core types for abstract MCTS implementation
+//
+
+#ifndef EAGLE0_MCTS_TYPES_HPP
+#define EAGLE0_MCTS_TYPES_HPP
+
+#include <stdexcept>
+#include <string>
+
+namespace shardok {
+namespace mcts {
+
+// Exception thrown when MCTS encounters an internal error that indicates a bug
+class MCTSInternalError : public std::logic_error {
+public:
+    explicit MCTSInternalError(const std::string& message) : std::logic_error(message) {}
+};
+
+// Abstract player identifier type
+using MCTSPlayerId = int;
+
+// Simulation policy for MCTS rollouts
+enum class MCTSSimulationPolicy {
+    RANDOM,                   // Pure random selection
+    FILTERED_RANDOM,          // Random from filtered actions
+    BEST_IMMEDIATE,           // Choose best immediate score
+    WEIGHTED_BEST_IMMEDIATE,  // Random weighted by score ranking
+    WEIGHTED_HEURISTIC        // Random weighted by fast heuristics (no score evaluation)
+};
+
+// Backpropagation policy for MCTS tree updates
+enum class MCTSBackpropagationPolicy {
+    AVERAGING,  // Traditional MCTS averaging (for stochastic/single-player games)
+    MINIMAX     // Minimax backup (for deterministic adversarial games)
+};
+
+// Configuration for MCTS algorithm
+struct MCTSConfig {
+    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
+    int maxSimulationDepth = 1000;       // Maximum depth for rollout
+    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
+    bool useMultithreading = true;       // Enable parallel MCTS
+    int numThreads = 16;                 // Number of threads for parallel MCTS
+    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
+    MCTSBackpropagationPolicy backpropagationPolicy = MCTSBackpropagationPolicy::AVERAGING;
+    int maxPlayerFlips = 0;          // Maximum number of player changes for tree expansion
+                                     // (0 = expand through current player's turn only,
+                                     //  1 = expand through opponent's first response, etc.)
+    int maxSimulationFlips = 0;      // Maximum player flips for leaf evaluation
+                                     // When evaluating a leaf at playerFlips < maxSimulationFlips,
+                                     // simulate forward to this phase for fair comparison
+                                     // (default 0 = evaluate leaves as-is, backward compatible)
+    std::string debugDumpPath = "";  // If non-empty, dump MCTS tree to this file path
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_MCTS_TYPES_HPP

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

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

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

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

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

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

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

@@ -9,7 +9,6 @@
 #include <ranges>
 #include <unordered_map>
 
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 
 namespace shardok {
@@ -76,30 +75,28 @@ auto MinDistanceIncludingBraving(
 auto EffectiveDistance(
         const Unit* unit,
         const HexMap* map,
-        const MapId& mapId,
-        const APDCache& apdCache,
         const AttackLocations& attackLocations,
-        const SettingsGetter& settings,
-        const int braveWaterCost) -> DIST_T {
+        const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> DIST_T {
     return EffectiveDistance(
             unit,
             map,
-            mapId,
-            apdCache,
             attackLocations.LocationsWithEnemyInRange(unit),
-            settings,
+            apdCache,
+            battalionTypeGetter,
             braveWaterCost);
 }
 
 auto EffectiveDistance(
         const Unit* unit,
         const HexMap* map,
-        const MapId& mapId,
-        const APDCache& apdCache,
         const CoordsSet& locations,
-        const SettingsGetter& settings,
-        const int braveWaterCost) -> DIST_T {
-    const auto& battType = settings.GetBattalionType(unit->battalion().type());
+        const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> DIST_T {
+    const auto mapId = ActionPointDistancesCache::GetMapId(map);
+    const auto& battType = battalionTypeGetter(unit->battalion().type());
     const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
     const ActionPointDistances* bravingApd = nullptr;
     if (battType->allowsBraveWater) {
@@ -132,12 +129,12 @@ auto GenerateTargetPriorities(
         const vector<const Unit*>& remainingUnits,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const MapId& mapId,
-        const SettingsGetter& settings,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         const bool isLateGame) -> vector<TargetPriorityList> {
     auto cc = map->column_count();
 
-    const auto braveWaterCost = settings.Backing().brave_water_action_point_cost();
+    const auto mapId = ActionPointDistancesCache::GetMapId(map);
 
     vector<TargetPriorityList> allTargetsUnitsAndDistances{};
     allTargetsUnitsAndDistances.reserve(remainingUnits.size());
@@ -161,7 +158,7 @@ auto GenerateTargetPriorities(
         vector<TargetAndDistance> targetsWithDistance;
 
         // Get APDs directly from cache (now with built-in thread-local optimization)
-        const auto& battType = settings.GetBattalionType(unit->battalion().type());
+        const auto& battType = battalionTypeGetter(unit->battalion().type());
         const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
         const ActionPointDistances* bravingApd = nullptr;
         if (battType->allowsBraveWater) {

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

@@ -5,12 +5,12 @@
 #ifndef EAGLE0_AIATTACKGROUPS_HPP
 #define EAGLE0_AIATTACKGROUPS_HPP
 
+#include <functional>
 #include <vector>
 
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/player_info.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/unit.hpp"
@@ -22,6 +22,8 @@ using Unit = net::eagle0::shardok::storage::fb::Unit;
 using net::eagle0::shardok::storage::fb::PlayerInfo;
 using std::vector;
 
+using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
+
 struct TargetAndAttackLocations {
     Coords target;
     CoordsSet attackLocations;
@@ -41,20 +43,18 @@ struct TargetPriorityList {
 auto EffectiveDistance(
         const Unit* unit,
         const HexMap* map,
-        const MapId& mapId,
-        const APDCache& apdCache,
         const AttackLocations& attackLocations,
-        const SettingsGetter& settings,
-        int braveWaterCost) -> DIST_T;
+        const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> DIST_T;
 
 auto EffectiveDistance(
         const Unit* unit,
         const HexMap* map,
-        const MapId& mapId,
-        const APDCache& apdCache,
         const CoordsSet& locations,
-        const SettingsGetter& settings,
-        int braveWaterCost) -> DIST_T;
+        const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> DIST_T;
 
 auto EffectiveDistance(
         const Unit* unit,
@@ -71,8 +71,8 @@ auto GenerateTargetPriorities(
         const vector<const Unit*>& remainingUnits,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const MapId& mapId,
-        const SettingsGetter& settings,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         bool isLateGame = false) -> vector<TargetPriorityList>;
 
 }  // namespace shardok

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

@@ -4,6 +4,7 @@
 
 #include "AIAttackerStrategySelector.hpp"
 
+#include "AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIFleeDecisionCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -20,11 +21,13 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
         const PlayerId attackerPid,
         const GameStateW& gameState,
         const CoordsSet& criticalTileCoords,
+        int maxRounds,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-        const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
+        const CommandListSPtr& /*availableCommands*/) -> AIStrategy {
     uint32_t attackerUnitCount = 0;
     int defenderOccupiedCriticalTileCount = 0;
     bool canFlee = false;
@@ -63,12 +66,14 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
     if (canFlee && AIFleeDecisionCalculator::ShouldConsiderFleeing(
                            attackerPid,
                            gameState,
-                           settings,
+                           maxRounds,
                            FLEE_CONSIDERATION_THRESHOLD)) {
         chosenStrategy = FleeStrategy;
     } else if (const CoordsSet startCrossingLocations =
-                       waterCrossingCommandChooser
-                               .StartCrossingFrom(settings, gameState, criticalTileCoords);
+                       waterCrossingCommandChooser.StartCrossingFrom(
+                               battalionTypeGetter,
+                               gameState,
+                               criticalTileCoords);
                !startCrossingLocations.empty()) {
         chosenStrategy = CrossRiversStrategy(startCrossingLocations);
     } else if (attackerUnitCount < criticalTileCoords.size()) {
@@ -83,8 +88,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                 attackerUnits,
                 apdCache,
                 alCache,
-                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
-                settings));
+                battalionTypeGetter,
+                braveWaterCost));
     }
     // If any critical tile is occupied by the defender, attack the castles.
     // Otherwise, try to hold the castles.
@@ -100,8 +105,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                 attackerUnits,
                 apdCache,
                 alCache,
-                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
-                settings));
+                battalionTypeGetter,
+                braveWaterCost));
     } else {
         chosenStrategy = HoldCastlesStrategy;
     }

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

@@ -6,9 +6,12 @@
 #define EAGLE0_AIATTACKERSTRATEGYSELECTOR_HPP
 
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 
 namespace shardok {
@@ -19,11 +22,13 @@ public:
             PlayerId attackerPid,
             const GameStateW& gameState,
             const CoordsSet& criticalTileCoords,
+            int maxRounds,
             const APDCache& apdCache,
             const ALCache& alCache,
-            const SettingsGetter& settings,
+            const BattalionTypeGetter& battalionTypeGetter,
+            ActionPoints braveWaterCost,
             const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-            const vector<CommandProto>& availableCommands) -> AIStrategy;
+            const CommandListSPtr& availableCommands) -> AIStrategy;
 };
 
 }  // namespace shardok

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

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

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

@@ -0,0 +1,110 @@
+//
+// Command evaluator for AI lookahead search.
+// Separated from AIScoreCalculator to isolate pure state scoring from lookahead logic.
+//
+
+#ifndef EAGLE0_AICOMMANDEVALUATOR_HPP
+#define EAGLE0_AICOMMANDEVALUATOR_HPP
+
+#include <chrono>
+#include <future>
+
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
+
+namespace shardok {
+
+// Forward declarations
+class AIScoreCalculator;
+class ShardokEngine;
+
+using ScoreValue = double;
+using CommandType = net::eagle0::shardok::common::CommandType;
+using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
+
+/// Evaluates commands with lookahead using minimax-style search.
+/// Uses AIScoreCalculator for pure state evaluation, adds recursive lookahead logic.
+class AICommandEvaluator {
+public:
+    /// Construct evaluator with a scorer for state evaluation and dependencies for command
+    /// filtering
+    AICommandEvaluator(
+            const AIScoreCalculator& scorer,
+            const APDCache& apdCache,
+            BattalionTypeGetter battalionTypeGetter);  // Pass by value
+
+    /// Evaluates the score for a particular command index with lookahead.
+    [[nodiscard]] auto EvaluateCommand(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine& guessedEngine,
+            const AIStrategy& attackerStrategy,
+            ScoreValue currentUtility,
+            const CoordsSet& allCastleCoords,
+            size_t commandIndex,
+            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
+
+    /// Find the best command among all available commands at the given depth.
+    struct IndexAndScore {
+        size_t index;
+        CommandType type;
+        ScoreValue lookaheadScore;
+        ScoreValue immediateScore;
+    };
+
+    [[nodiscard]] auto FindBestCommand(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine& guessedEngine,
+            const AIStrategy& attackerStrategy,
+            ScoreValue currentUtility,
+            const CoordsSet& allCastleCoords,
+            std::chrono::steady_clock::time_point deadline) const -> std::future<IndexAndScore>;
+
+private:
+    const AIScoreCalculator& scorer_;
+    const APDCache& apdCache_;
+    BattalionTypeGetter battalionTypeGetter_;  // Store by value
+
+    struct ImmediateAndLookaheadScore {
+        ScoreValue immediateScore;
+        std::future<ScoreValue> lookaheadScore;
+    };
+
+    /// Recursive lookahead calculator
+    [[nodiscard]] auto PerformLookahead(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const std::shared_ptr<ShardokEngine>& innerEngine,
+            ScoreValue currentUtility,
+            const AIStrategy& attackerStrategy,
+            const CoordsSet& allCastleCoords,
+            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
+
+    /// Evaluate single command execution with randomness handling
+    [[nodiscard]] auto EvaluateWithRandomness(
+            PlayerId pid,
+            bool isDefender,
+            uint32_t commandIndex,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const std::shared_ptr<class RandomGenerator>& randomGenerator,
+            const ShardokEngine& guessedEngine,
+            const AIStrategy& attackerStrategy,
+            const CoordsSet& allCastleCoords,
+            std::chrono::steady_clock::time_point deadline) const -> ImmediateAndLookaheadScore;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AICOMMANDEVALUATOR_HPP

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

@@ -7,6 +7,7 @@
 #include <algorithm>
 
 #include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexCubeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
@@ -36,8 +37,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
         PlayerId pid,
         bool isDefender,
         const GameStateW& gameState,
-        const SettingsGetter& settings,
-        const APDCache& apdCache) {
+        const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter) {
     std::vector<size_t> filteredIndices;
     filteredIndices.reserve(commands->size());
 
@@ -66,8 +67,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                     pid,
                     isDefender,
                     gameState,
-                    settings,
                     apdCache,
+                    battalionTypeGetter,
                     enemyLocations,
                     castleLocations,
                     minDistToEnemies)) {
@@ -80,16 +81,22 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                                      pid,
                                      isDefender,
                                      gameState,
-                                     settings,
                                      apdCache,
+                                     battalionTypeGetter,
                                      enemyLocations,
                                      minDistToEnemies)) {
             shouldFilter = true;
         }
 
         // Check strategic blunders
-        if (!shouldFilter &&
-            IsStrategicBlunder(*cmd, pid, isDefender, gameState, settings, minDistToEnemies)) {
+        if (!shouldFilter && IsStrategicBlunder(
+                                     *cmd,
+                                     pid,
+                                     isDefender,
+                                     gameState,
+                                     apdCache,
+                                     battalionTypeGetter,
+                                     minDistToEnemies)) {
             shouldFilter = true;
         }
 
@@ -104,8 +111,8 @@ bool AICommandFilter::IsWastefulAction(
         PlayerId pid,
         bool isDefender,
         const GameStateW& gameState,
-        const SettingsGetter& settings,
         const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
         const CoordsSet& enemyLocations,
         const CoordsSet& castleLocations,
         double minDistToEnemies) {
@@ -137,15 +144,16 @@ bool AICommandFilter::IsWastefulAction(
 
             if (!isDefender) {
                 // Attackers: Only allow fire if the target location is on or adjacent to an enemy
-                const auto cmdProto = cmd.GetCommandProto();
-                if (!cmdProto.has_target()) {
-                    return true;  // Can't analyze without target info
+                const int targetRow = cmd.GetTargetRow();
+                const int targetCol = cmd.GetTargetColumn();
+                if (targetRow < 0 || targetCol < 0) {
+                    throw ShardokInternalErrorException(
+                            "START_FIRE_COMMAND missing required target information");
                 }
 
-                const auto& targetCoords = cmdProto.target();
-                const Coords fireLocation{
-                        static_cast<int8_t>(targetCoords.row()),
-                        static_cast<int8_t>(targetCoords.column())};
+                const Coords fireLocation(
+                        static_cast<int8_t>(targetRow),
+                        static_cast<int8_t>(targetCol));
 
                 // Check if any enemy is on the fire location or adjacent to it
                 bool enemyNearFireLocation = false;
@@ -180,13 +188,12 @@ bool AICommandFilter::IsWastefulAction(
 
             if (!isDefender) {
                 // Attackers: Only allow fortify if within 3 hexes of enemies or castles
-                const auto cmdProto = cmd.GetCommandProto();
-                if (!cmdProto.has_actor()) {
-                    return true;  // Can't analyze without actor info
+                const int unitId = cmd.GetActorUnitId();
+                if (unitId < 0) {
+                    throw ShardokInternalErrorException(
+                            "FORTIFY_COMMAND missing required actor information");
                 }
 
-                const auto unitId = cmdProto.actor().value();
-
                 // Get the acting unit directly by ID
                 const Unit* actingUnit = gameState->units()->Get(unitId);
                 // verify the unit is still active
@@ -243,16 +250,18 @@ bool AICommandFilter::IsWastefulAction(
             // These actions can fail, so we need high confidence of benefit (8+ action points
             // saved)
 
-            const auto cmdProto = cmd.GetCommandProto();
-            if (!cmdProto.has_actor() || !cmdProto.has_target()) {
-                return true;  // Can't analyze without full command info
+            const int unitId = cmd.GetActorUnitId();
+            const int targetRow = cmd.GetTargetRow();
+            const int targetCol = cmd.GetTargetColumn();
+            if (unitId < 0 || targetRow < 0 || targetCol < 0) {
+                throw ShardokInternalErrorException(
+                        "BUILD_BRIDGE/FREEZE_WATER_COMMAND missing required actor or target "
+                        "information");
             }
 
-            const auto unitId = cmdProto.actor().value();
-            const auto& targetCoords = cmdProto.target();
-            const Coords waterLocation{
-                    static_cast<int8_t>(targetCoords.row()),
-                    static_cast<int8_t>(targetCoords.column())};
+            const Coords waterLocation(
+                    static_cast<int8_t>(targetRow),
+                    static_cast<int8_t>(targetCol));
 
             // Get the acting unit directly by ID
             const Unit* actingUnit = gameState->units()->Get(unitId);
@@ -269,7 +278,7 @@ bool AICommandFilter::IsWastefulAction(
             }
 
             // Get action point distances for this unit's battalion type
-            const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
+            const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
             const auto* apd = apdCache->GetRaw(
                     gameState->hex_map(),
                     ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -347,15 +356,16 @@ bool AICommandFilter::IsWastefulAction(
         case CommandType::REPAIR_COMMAND: {
             // Repair filtering - filter repairs with high integrity targets
             // Note: RepairCommandFactory already filters enemy-occupied targets
-            const auto cmdProto = cmd.GetCommandProto();
-            if (!cmdProto.has_target()) {
-                return true;  // Can't analyze without target info
+            const int targetRow = cmd.GetTargetRow();
+            const int targetCol = cmd.GetTargetColumn();
+            if (targetRow < 0 || targetCol < 0) {
+                throw ShardokInternalErrorException(
+                        "REPAIR_COMMAND missing required target information");
             }
 
-            const auto& targetCoords = cmdProto.target();
-            const Coords repairLocation{
-                    static_cast<int8_t>(targetCoords.row()),
-                    static_cast<int8_t>(targetCoords.column())};
+            const Coords repairLocation(
+                    static_cast<int8_t>(targetRow),
+                    static_cast<int8_t>(targetCol));
 
             // Check terrain modifiers at target location
             const auto* terrain = GetTerrain(gameState->hex_map(), repairLocation);
@@ -378,15 +388,16 @@ bool AICommandFilter::IsWastefulAction(
 
         case CommandType::EXTINGUISH_FIRE_COMMAND: {
             // Extinguish fire filtering - don't extinguish fires on enemy-occupied tiles
-            const auto cmdProto = cmd.GetCommandProto();
-            if (!cmdProto.has_target()) {
-                return true;  // Can't analyze without target info
+            const int targetRow = cmd.GetTargetRow();
+            const int targetCol = cmd.GetTargetColumn();
+            if (targetRow < 0 || targetCol < 0) {
+                throw ShardokInternalErrorException(
+                        "EXTINGUISH_FIRE_COMMAND missing required target information");
             }
 
-            const auto& targetCoords = cmdProto.target();
-            const Coords fireLocation{
-                    static_cast<int8_t>(targetCoords.row()),
-                    static_cast<int8_t>(targetCoords.column())};
+            const Coords fireLocation(
+                    static_cast<int8_t>(targetRow),
+                    static_cast<int8_t>(targetCol));
 
             // Check if any enemy occupies the fire location - let them burn!
             std::vector<PlayerId> allyPids;  // Empty for now - assume 2-player game
@@ -407,8 +418,8 @@ bool AICommandFilter::IsWastefulMovement(
         PlayerId pid,
         bool isDefender,
         const GameStateW& gameState,
-        const SettingsGetter& settings,
         const APDCache& apdCache,
+        const BattalionTypeGetter& battalionTypeGetter,
         const CoordsSet& enemyLocations,
         double minDistToEnemies) {
     if (cmd.GetCommandType() != CommandType::MOVE_COMMAND) { return false; }
@@ -418,17 +429,17 @@ bool AICommandFilter::IsWastefulMovement(
         return false;  // Don't filter defender movement or when close to enemies
     }
 
-    // Get the command proto to access unit and target information
-    const auto cmdProto = cmd.GetCommandProto();
+    // Get unit and target information directly from command
+    const int unitId = cmd.GetActorUnitId();
+    const int targetRow = cmd.GetTargetRow();
+    const int targetCol = cmd.GetTargetColumn();
 
     // Check if we have the required information
-    if (!cmdProto.has_actor() || !cmdProto.has_target()) {
-        return false;  // Can't analyze without unit and target info
+    if (unitId < 0 || targetRow < 0 || targetCol < 0) {
+        throw ShardokInternalErrorException(
+                "MOVE_COMMAND missing required actor or target information");
     }
 
-    const auto unitId = cmdProto.actor().value();
-    const auto& targetCoords = cmdProto.target();
-
     // Get the acting unit directly by ID
     const Unit* actingUnit = gameState->units()->Get(unitId);
     // Verify the unit is still active
@@ -444,12 +455,10 @@ bool AICommandFilter::IsWastefulMovement(
     }
 
     const auto& currentCoords = actingUnit->location();
-    const Coords targetCoordsFlat{
-            static_cast<int8_t>(targetCoords.row()),
-            static_cast<int8_t>(targetCoords.column())};
+    const Coords targetCoordsFlat(static_cast<int8_t>(targetRow), static_cast<int8_t>(targetCol));
 
     // Get action point distances for this unit's battalion type
-    const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
+    const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
     const auto* apd = apdCache->GetRaw(
             gameState->hex_map(),
             ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -490,7 +499,8 @@ bool AICommandFilter::IsStrategicBlunder(
         PlayerId /*pid*/,
         bool /*isDefender*/,
         const GameStateW& /*gameState*/,
-        const SettingsGetter& /*settings*/,
+        const APDCache& /*apdCache*/,
+        const BattalionTypeGetter& /*battalionTypeGetter*/,
         double /*minDistToEnemies*/) {
     // Simplified strategic blunder detection for now
     // TODO: Implement proper castle abandonment detection

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

@@ -8,12 +8,12 @@
 #include <memory>
 #include <vector>
 
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
@@ -32,8 +32,8 @@ public:
      * @param pid Player ID making the move
      * @param isDefender True if this player is the defender
      * @param gameState Current game state
-     * @param settings Game settings for parameter lookup
      * @param apdCache Action point distance cache for distance calculations
+     * @param battalionTypeLookup Function to look up battalion types by ID
      * @return Filtered list of commands worth evaluating
      */
     static std::vector<size_t> FilterCommands(
@@ -41,8 +41,8 @@ public:
             PlayerId pid,
             bool isDefender,
             const GameStateW& gameState,
-            const SettingsGetter& settings,
-            const APDCache& apdCache);
+            const APDCache& apdCache,
+            const BattalionTypeGetter& battalionTypeLookup);
 
 private:
     // Helper to build enemy locations once for efficiency
@@ -54,8 +54,8 @@ private:
             PlayerId pid,
             bool isDefender,
             const GameStateW& gameState,
-            const SettingsGetter& settings,
             const APDCache& apdCache,
+            const BattalionTypeGetter& battalionTypeLookup,
             const CoordsSet& enemyLocations,
             const CoordsSet& castleLocations,
             double minDistToEnemies);
@@ -66,8 +66,8 @@ private:
             PlayerId pid,
             bool isDefender,
             const GameStateW& gameState,
-            const SettingsGetter& settings,
             const APDCache& apdCache,
+            const BattalionTypeGetter& battalionTypeLookup,
             const CoordsSet& enemyLocations,
             double minDistToEnemies);
 
@@ -77,7 +77,8 @@ private:
             PlayerId pid,
             bool isDefender,
             const GameStateW& gameState,
-            const SettingsGetter& settings,
+            const APDCache& apdCache,
+            const BattalionTypeGetter& battalionTypeLookup,
             double minDistToEnemies);
 
     // Helper functions for distance and position analysis

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

@@ -0,0 +1,23 @@
+//
+// AICommonTypes.hpp
+// Common type definitions used across AI utility functions
+//
+
+#ifndef EAGLE0_AICOMMONTYPES_HPP
+#define EAGLE0_AICOMMONTYPES_HPP
+
+#include <functional>
+
+#include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+
+namespace shardok {
+
+// Function type for looking up battalion types by ID
+// Used across AI utilities to get battalion type information without
+// needing to pass the entire scorer object
+using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AICOMMONTYPES_HPP

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

@@ -0,0 +1,25 @@
+//
+// AI System Types and Configuration
+//
+
+#ifndef EAGLE0_AI_CONFIG_HPP
+#define EAGLE0_AI_CONFIG_HPP
+
+namespace shardok {
+
+// Enum for AI algorithm selection
+enum class AIAlgorithmType {
+    ITERATIVE_DEEPENING,  // Default: Minimax with sophisticated randomness
+    MCTS                  // Monte Carlo Tree Search with multithreading
+};
+
+// Enum for scoring calculator selection
+enum class ScoringCalculatorType {
+    STANDARD,       // Default: Unbounded raw scores
+    NORMALIZED,     // Normalized scores in [0, 1] range for ML training
+    MCTS_OPTIMIZED  // Bounded linear scores tuned for MCTS
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AI_CONFIG_HPP

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

@@ -7,8 +7,10 @@
 #include <algorithm>
 #include <ranges>
 
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 
 namespace shardok {
@@ -19,8 +21,9 @@ constexpr double MINIMUM_RATIO_FOR_DEFENDER_TO_HOLD = 0.60;
 auto AIDefenderStrategySelector::BestDefenderStrategy(
         const GameStateW& gameState,
         const CoordsSet& criticalTileCoords,
+        int maxRounds,
         const APDCache& apdCache,
-        const SettingsGetter& settings) -> AIStrategy {
+        const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy {
     uint32_t attackerNonUndeadUnitCount = 0;
     uint32_t attackerNonUndeadUnitNotRequiringWaterCrossingCount = 0;
     int attackerTroops = 0;
@@ -36,7 +39,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                     player->player_id(),
                     criticalTileCoords,
                     apdCache,
-                    settings);
+                    battalionTypeGetter);
             attackerUnitIdsRequiringWaterCrossing.insert(
                     attackerUnitIdsRequiringWaterCrossing.end(),
                     unitIdsRequiringWaterCrossing.begin(),
@@ -71,7 +74,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
         }
     }
 
-    const int roundsRemaining = 32 - gameState->current_round();
+    const int roundsRemaining = maxRounds - gameState->current_round();
     AIStrategy chosenStrategy;
 
     // Defender will flee if

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

@@ -6,19 +6,23 @@
 #define EAGLE0_AIDEFENDERSTRATEGYSELECTOR_HPP
 
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
 
 namespace shardok {
+
 class AIDefenderStrategySelector {
 public:
     static auto BestDefenderStrategy(
             const GameStateW& gameState,
             const CoordsSet& criticalTileCoords,
+            int maxRounds,
             const APDCache& apdCache,
-            const SettingsGetter& settings) -> AIStrategy;
+            const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy;
 };
 }  // namespace shardok
 

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

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

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

@@ -6,10 +6,10 @@
 #define EAGLE0_AIDISTANCEDEBUF_HPP
 
 #include "AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 
 namespace shardok {
 
@@ -23,8 +23,8 @@ auto DefenderDistanceBuf(
         const vector<const Unit *> &attackerUnits,
         const APDCache &apdCache,
         const ALCache &alCache,
-        const SettingsGetter &settings,
-        int braveWaterActionPointCost,
+        const BattalionTypeGetter &battalionTypeGetter,
+        ActionPoints braveWaterCost,
         bool lateGame,
         bool includeUndead) -> double;
 

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

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

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

@@ -9,14 +9,11 @@
 #ifndef AIFleeDecisionCalculator_hpp
 #define AIFleeDecisionCalculator_hpp
 
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
 class AIFleeDecisionCalculator {
 public:
     // Configuration for flee decision thresholds
@@ -35,31 +32,33 @@ public:
     // 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,
+            const CommandListSPtr& availableCommands,
+            const CommandList::const_iterator& fleeCommand,
+            int maxRounds,
+            int minimumFleeOddsThreshold,
+            int desperateFleeThreshold,
             bool enableDebugLogging = false) -> FleeDecision;
 
     // Estimate probability of combat success for the attacker
     [[nodiscard]] static auto EstimateCombatSuccess(
             PlayerId attackerPlayerId,
             const GameStateW& guessedState,
-            const SettingsGetter& settings) -> double;
+            int maxRounds) -> double;
 
     // Determine if the attacker should consider fleeing based on combat odds
     // Returns true if fleeing should be considered as an option
     [[nodiscard]] static auto ShouldConsiderFleeing(
             PlayerId attackerPlayerId,
             const GameStateW& guessedState,
-            const SettingsGetter& settings,
+            int maxRounds,
             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;
+            const CommandList::const_iterator& fleeCommand,
+            const CommandListSPtr& availableCommands) -> size_t;
 };
 
 }  // namespace shardok

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

@@ -0,0 +1,251 @@
+//
+// Fast heuristic weighting implementation with context-aware logic
+//
+
+#include "AIHeuristicWeighting.hpp"
+
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
+
+namespace shardok {
+
+using CommandType = net::eagle0::shardok::common::CommandType;
+using Coords = net::eagle0::shardok::storage::fb::Coords;
+using ProtoCoords = net::eagle0::shardok::common::Coords;
+
+double AIHeuristicWeighting::GetCommandWeight(
+        const CommandType commandType,
+        const UnitId actorUnitId,
+        const PlayerId actorPlayerId,
+        const Coords& targetCoords,
+        const GameStateW& state,
+        const CoordsSet& castleCoords,
+        const APDCache* apdCache,
+        bool isDefender,
+        std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType) {
+    // Fast O(1) heuristic weights based on command type and game context
+    // Higher weight = more likely to select in simulation
+    // 0.0 = never select (filtered out)
+
+    const auto* hexMap = state->hex_map();
+    const auto* units = state->units();
+    const bool hasTarget = (targetCoords.row() >= 0 && targetCoords.column() >= 0);
+
+    switch (commandType) {
+        // === HIGH VALUE OFFENSIVE (10.0) ===
+        // Ranged attacks - very valuable, typically available when in range
+        case CommandType::ARCHERY_COMMAND: return 20.0;
+        case CommandType::LIGHTNING_BOLT_COMMAND: return 10.0;
+        case CommandType::FEAR_COMMAND: return 10.0;
+
+        // Area/tactical spells - high impact
+        case CommandType::METEOR_START_COMMAND: {
+            // METEOR_START doesn't have a target - it's based on actor location
+            if (hasTarget) {
+                throw ShardokInternalErrorException(
+                        "METEOR_START_COMMAND should not have target coordinates");
+            }
+
+            // Get actor's location
+            const auto* actorUnit = units->Get(actorUnitId);
+            if (!actorUnit) {
+                throw ShardokInternalErrorException(
+                        "METEOR_START_COMMAND actor unit not found in game state");
+            }
+
+            const Coords& actorLocation = actorUnit->location();
+            int enemyCount = 0;
+
+            // Count enemies within meteor range (3 hexes) of actor location
+            constexpr int METEOR_RANGE = 3;
+            const auto tilesInRange = TilesWithinDistance(hexMap, actorLocation, METEOR_RANGE);
+            for (const auto& tileCoords : tilesInRange) {
+                if (const auto* unit = Occupant(units, tileCoords)) {
+                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
+                }
+            }
+
+            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
+        }
+
+        case CommandType::METEOR_TARGET_COMMAND: {
+            // High weight per enemy unit at or adjacent to target
+            if (!hasTarget) {
+                throw ShardokInternalErrorException(
+                        "METEOR_TARGET_COMMAND requires target coordinates for heuristic "
+                        "weighting");
+            }
+
+            int enemyCount = 0;
+
+            // Count enemies at target
+            if (const auto* targetUnit = Occupant(units, targetCoords)) {
+                if (targetUnit->player_id() != actorPlayerId) { enemyCount++; }
+            }
+
+            // Count enemies adjacent to target
+            for (const auto& neighbor : HexMapUtils::GetAdjacentTiles(hexMap, targetCoords)) {
+                if (const auto* unit = Occupant(units, neighbor.coords)) {
+                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
+                }
+            }
+
+            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
+        }
+
+        case CommandType::RAISE_DEAD_COMMAND: return 10.0;
+        case CommandType::HOLY_WAVE_COMMAND: return 8.0;
+
+        // Fire on enemy (context-dependent)
+        case CommandType::START_FIRE_COMMAND: {
+            // High if enemy at target, low otherwise
+            if (!hasTarget) {
+                throw ShardokInternalErrorException(
+                        "START_FIRE_COMMAND requires target coordinates for heuristic weighting");
+            }
+
+            if (const auto* targetUnit = Occupant(units, targetCoords)) {
+                if (targetUnit->player_id() != actorPlayerId) {
+                    return 10.0;  // Enemy at target - high value
+                }
+            }
+            return 1.0;  // No enemy - low value but still valid
+        }
+
+        // === MEDIUM-HIGH OFFENSIVE (5.0-7.0) ===
+        // Direct damage melee
+        case CommandType::MELEE_COMMAND: return 7.0;
+        case CommandType::CHARGE_COMMAND: return 7.0;  // Damage + movement
+        case CommandType::CHALLENGE_DUEL_COMMAND: return 5.0;
+
+        // Control and tactical magic
+        case CommandType::CONTROL_COMMAND: return 6.0;
+        case CommandType::METEOR_CAST_COMMAND: return 6.0;  // Finish meteor
+
+        case CommandType::REDUCE_COMMAND: {
+            // High if enemy at target, zero otherwise
+            if (!hasTarget) return 0.0;
+
+            if (const auto* targetUnit = Occupant(units, targetCoords)) {
+                if (targetUnit->player_id() != actorPlayerId) {
+                    return 10.0;  // Enemy at target - very high value
+                }
+            }
+            return 0.0;  // No enemy - don't use
+        }
+
+        // === MOVEMENT - Context-dependent ===
+        case CommandType::MOVE_COMMAND: {
+            if (isDefender) {
+                return 0.0;  // Defenders don't move
+            }
+
+            // Attackers: weight based on distance improvement towards castle
+            if (!hasTarget) {
+                throw ShardokInternalErrorException(
+                        "MOVE_COMMAND requires target coordinates for heuristic weighting");
+            }
+
+            // Get actor unit to determine battalion type and start position
+            const auto* actorUnit = units->Get(actorUnitId);
+            if (!actorUnit) return 4.0;  // Default if can't find actor
+
+            // Get battalion type for distance calculation
+            const auto battalionTypeId = actorUnit->battalion().type();
+            const auto battalionTypePtr = getBattalionType(battalionTypeId);
+            if (!battalionTypePtr) return 4.0;  // Default if can't get battalion type
+
+            // Get ActionPointDistances for this battalion type
+            const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);
+            const auto* apd = (*apdCache)->GetRaw(hexMap, mapId, battalionTypePtr, false, -1);
+            if (!apd) return 4.0;  // Default if can't get distances
+
+            // Calculate minimum distance from start to any castle
+            const Coords startCoords = actorUnit->location();
+            auto minStartDistance = ActionPointDistances::IMPOSSIBLE;
+            for (const auto& castleCoord : castleCoords) {
+                const auto dist = apd->Distance(startCoords, castleCoord);
+                if (dist < minStartDistance) { minStartDistance = dist; }
+            }
+
+            // Calculate minimum distance from end to any castle
+            const Coords& endCoords = targetCoords;
+            auto minEndDistance = ActionPointDistances::IMPOSSIBLE;
+            for (const auto& castleCoord : castleCoords) {
+                const auto dist = apd->Distance(endCoords, castleCoord);
+                if (dist < minEndDistance) { minEndDistance = dist; }
+            }
+
+            // Return weight based on distance improvement
+            // Higher weight if we're moving closer to castle
+            if (minStartDistance == ActionPointDistances::IMPOSSIBLE ||
+                minEndDistance == ActionPointDistances::IMPOSSIBLE) {
+                return 4.0;  // Default if distances are impossible
+            }
+
+            const auto improvement = static_cast<double>(minStartDistance - minEndDistance);
+            return std::max(0.0, improvement);
+        }
+
+        case CommandType::BRAVE_WATER_COMMAND: return 3.0;  // Tactical movement
+        case CommandType::SCOUT_COMMAND:
+            return 2.0;  // Information gathering
+
+        // Terrain manipulation
+        case CommandType::FREEZE_WATER_COMMAND: return 3.0;
+        case CommandType::BUILD_BRIDGE_COMMAND: return 3.0;
+
+        // === LOW VALUE DEFENSIVE/UTILITY (1.0-2.0) ===
+        case CommandType::EXTINGUISH_FIRE_COMMAND: {
+            // High if friendly at target, low otherwise
+            if (!hasTarget) {
+                throw ShardokInternalErrorException(
+                        "EXTINGUISH_FIRE_COMMAND requires target coordinates for heuristic "
+                        "weighting");
+            }
+
+            if (const auto* targetUnit = Occupant(units, targetCoords)) {
+                if (targetUnit->player_id() == actorPlayerId) {
+                    return 8.0;  // Friendly at target - high value
+                }
+            }
+            return 1.0;  // No friendly - low value but still valid
+        }
+
+        case CommandType::UNIT_REST_COMMAND: return 1.5;
+        case CommandType::FORTIFY_COMMAND: return 2.0;
+
+        // Zero weight - don't use in simulation
+        case CommandType::REPAIR_COMMAND: return 0.0;
+        case CommandType::HIDE_COMMAND: return 0.0;
+        case CommandType::RELEASE_UNIT_COMMAND: return 0.0;
+
+        case CommandType::REINFORCE_COMMAND: return 10.0;
+        case CommandType::MANAGE_PRISONER: return 1.0;
+
+        // === ZERO WEIGHT - NEVER SELECT (0.0) ===
+        // Explicitly bad actions
+        case CommandType::FLEE_COMMAND: return 0.0;  // Never flee in simulation
+        case CommandType::RETREAT_COMMAND: return 0.0;
+        case CommandType::BECOME_OUTLAW_COMMAND: return 0.0;  // Never become outlaw
+        case CommandType::DISMISS_UNIT_COMMAND:
+            return 0.0;  // Never dismiss in combat
+
+        // Actions that are fine as a fallback
+        case CommandType::END_TURN_COMMAND: return 1.0;
+        case CommandType::UNIT_STOP_COMMAND: return 1.0;
+        case CommandType::METEOR_CANCEL_COMMAND: return 1.0;
+
+        // Setup commands (shouldn't appear in combat, but filter anyway)
+        case CommandType::PLACE_UNIT_COMMAND: return 10.0;
+        case CommandType::PLACE_HIDDEN_UNIT_COMMAND: return 1.0;
+        case CommandType::END_PLAYER_SETUP_COMMAND: return 1.0;
+
+        // Unknown/unhandled
+        case CommandType::UNKNOWN_COMMAND:
+        default: return 0.0;  // Don't select unknown commands
+    }
+}
+
+}  // namespace shardok

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

@@ -0,0 +1,40 @@
+//
+// Fast heuristic weighting for MCTS simulations
+// Provides O(1) weights based on command type and context
+//
+
+#ifndef EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
+#define EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
+
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
+#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
+#pragma clang diagnostic pop
+
+#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+
+namespace shardok {
+
+// Fast heuristic-based command weighting for MCTS simulation policy
+// Avoids expensive score calculation while maintaining intelligent bias
+class AIHeuristicWeighting {
+public:
+    // Get weight for a command using fast heuristics with game context
+    // Returns weight >= 0.0, where 0.0 means "never select" and higher is more likely
+    static double GetCommandWeight(
+            net::eagle0::shardok::common::CommandType commandType,
+            UnitId actorUnitId,
+            PlayerId actorPlayerId,
+            const Coords& targetCoords,
+            const GameStateW& state,
+            const CoordsSet& castleCoords,
+            const APDCache* apdCache,
+            bool isDefender,
+            std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType);
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AI_HEURISTIC_WEIGHTING_HPP

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

@@ -1,64 +0,0 @@
-//
-// Created by dancrosby on 3/4/20.
-//
-
-#ifndef EAGLE0_AISCORECALCULATOR_HPP
-#define EAGLE0_AISCORECALCULATOR_HPP
-
-#include <chrono>
-#include <future>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
-#include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
-
-namespace shardok {
-
-using net::eagle0::shardok::api::GameStateView;
-using GameState = fb::GameState;
-using shardok::PlayerId;
-using std::future;
-using std::vector;
-
-using ScoreValue = double;
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-
-class AIScoreCalculator {
-public:
-    // Evaluate the score of a guessed game state based on the current AI strategy. DOES NOT perform
-    // or evaluate any commands.
-    [[nodiscard]] static auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords,
-            const SettingsGetter &settingsGetter,
-            const APDCache &apdCache,
-            const ALCache &alCache) -> ScoreValue;
-
-    // Evaluates the score for a particular command index for the given player, using lookahead.
-    [[nodiscard]] static auto CommandScore(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const ShardokEngine &guessedEngine,
-            const AIStrategy &attackerStrategy,
-            ScoreValue currentUtility,
-            const SettingsGetter &settingsGetter,
-            const CoordsSet &allCastleCoords,
-            const APDCache &apdCache,
-            const ALCache &alCache,
-            size_t commandIndex,
-            std::chrono::steady_clock::time_point deadline) -> std::future<ScoreValue>;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AISCORECALCULATOR_HPP

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

@@ -3,6 +3,7 @@
 //
 
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+
 namespace shardok {
 AIStrategy FleeStrategy = AIStrategy{AIStrategy::STRATEGY_FLEE};
 AIStrategy HoldCastlesStrategy = AIStrategy{AIStrategy::STRATEGY_HOLD_CASTLES};

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

@@ -24,10 +24,40 @@ int AIEvaluationCounter::GetCurrentCount() { return activeCount.load(); }
 auto CalculateTimeBudget(
         const PlayerId playerId,
         const GameSettingsSPtr &settings,
-        const GameStateW &state) -> AITimeBudget {
+        const GameStateW &state,
+        const size_t numCommands) -> AITimeBudget {
     const auto settingsGetter = settings->GetGetter();
     const auto castleCoords = AllCastleCoords(state->hex_map());
 
+    // Check if we're in setup phase
+    const bool isSetupPhase = state->status()->state() ==
+                              net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP;
+
+    // Get maximum budget cap from settings (in seconds)
+    const double maxBudgetSeconds =
+            settingsGetter.Backing().lookahead_time_budget_maximum_seconds();
+    const double maxBudgetMs = maxBudgetSeconds * 1000.0;
+
+    // During setup, use the setup-specific time budget
+    if (isSetupPhase) {
+        // Dynamic budget: msPerCommand × numCommands
+        const double msPerCommand =
+                settingsGetter.Backing().lookahead_time_budget_per_command_setup_ms();
+        const double budgetMs = msPerCommand * static_cast<double>(numCommands);
+
+        // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
+        const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
+        const auto remainingBudget =
+                std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
+
+        const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();
+
+        return AITimeBudget{
+                .remainingBudget = remainingBudget,
+                .minDepthRequired = minDepth,
+                .isCloseToEnemy = false};  // Not relevant during setup
+    }
+
     // Determine proximity (≤4 hex distance) - applies to both attackers and defenders
     bool isClose = false;
     const auto *units = state->units();
@@ -72,12 +102,25 @@ auto CalculateTimeBudget(
         }
     }
 
-    // Get time budget from settings
-    const auto budget = std::chrono::duration<double>(
-            isClose ? settingsGetter.Backing().lookahead_time_budget_close_in_seconds()
-                    : settingsGetter.Backing().lookahead_time_budget_far_in_seconds());
+    // Get time budget from settings - dynamic based on number of commands
+    // Dynamic budget: msPerCommand × numCommands
+    const double msPerCommand =
+            isClose ? settingsGetter.Backing().lookahead_time_budget_per_command_close_ms()
+                    : settingsGetter.Backing().lookahead_time_budget_per_command_far_ms();
+    const double budgetMs = msPerCommand * static_cast<double>(numCommands);
 
-    const auto remainingBudget = std::chrono::duration_cast<std::chrono::milliseconds>(budget);
+    // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
+    const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
+    const auto remainingBudget = std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
+
+    // TEMPORARY DEBUG OUTPUT
+    printf("[DEBUG CalculateTimeBudget] numCommands=%zu, msPerCommand=%.2f, budgetMs=%.2f, "
+           "clampedBudgetMs=%.2f, isClose=%d\n",
+           numCommands,
+           msPerCommand,
+           budgetMs,
+           clampedBudgetMs,
+           isClose);
 
     // Get minimum depth requirement
     const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();

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

@@ -36,10 +36,13 @@ struct AITimeBudget {
 };
 
 // Calculate time budget based on proximity to enemies and castles
+// Time budget is calculated dynamically based on number of available commands:
+//   budget = msPerCommand × numCommands (clamped to 200-5000ms)
 auto CalculateTimeBudget(
         PlayerId playerId,
         const GameSettingsSPtr &settings,
-        const GameStateW &state) -> AITimeBudget;
+        const GameStateW &state,
+        size_t numCommands) -> AITimeBudget;
 
 }  // namespace shardok
 

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

@@ -17,9 +17,10 @@ using std::end;
 using std::shared_ptr;
 
 constexpr double kProfessionValue = 200;
+constexpr double kVigorScoreMultiplier = 5.0;
 constexpr double kCastleMultiplierBonus = 1.0;
 constexpr double kOnFireMultiplier = 0.25;
-constexpr double kAdjacentFireMultiplier = 0.99;
+constexpr double kAdjacentFireMultiplier = 0.80;
 constexpr double kOnIceMultiplier = 0.25;
 constexpr double kMeteorStartInRangeValue = 50;
 constexpr double kMeteorDirectTargetingEnemy = 2;
@@ -63,7 +64,8 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
                      4.0;
     }
 
-    const double vigorValue = unit->has_attached_hero() ? unit->attached_hero().vigor() : 0.0;
+    const double vigorValue =
+            unit->has_attached_hero() ? unit->attached_hero().vigor() * kVigorScoreMultiplier : 0.0;
 
     double battalionTypeMultiplier = 1.0;
     switch (unit->battalion().type()) {
@@ -335,7 +337,8 @@ auto UnitValue(
         const AttackLocations &locationsThisSideCanAttackFrom,
         const CoordsSet &locationsInDangerFromEnemy,
         const ActionPointDistances *distances,
-        const SettingsGetter &settings) -> ScoreValue {
+        int meteorRange,
+        double meteorCastVigorCost) -> ScoreValue {
     const auto &location = unit->location();
     if (location.row() < 0) return 0;  // unplaced unit
 
@@ -354,9 +357,7 @@ auto UnitValue(
                 kCastleMultiplierBonus * (terrain->modifier().castle().integrity() + 25) / 100.0;
     }
     double onFireMultiplier = 1.0;
-    if (terrain->modifier().fire().present() && (isAttacker || attackerWantsCastles)) {
-        onFireMultiplier *= kOnFireMultiplier;
-    }
+    if (terrain->modifier().fire().present()) { onFireMultiplier *= kOnFireMultiplier; }
     {
         for (const auto adjacentCoords = HexMapUtils::GetAdjacentCoords(map, location);
              const auto &c : adjacentCoords) {
@@ -380,8 +381,8 @@ auto UnitValue(
             roundsRemaining,
             attackerUnits,
             defenderUnits,
-            settings.Backing().meteor_range(),
-            settings.Backing().meteor_cast_vigor_cost());
+            meteorRange,
+            meteorCastVigorCost);
 
     // scouting values
     // attack range

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

@@ -46,7 +46,8 @@ auto UnitValue(
         const AttackLocations &locationsThisSideCanAttackFrom,
         const CoordsSet &locationsInDangerFromEnemy,
         const ActionPointDistances *distances,
-        const SettingsGetter &settings) -> ScoreValue;
+        int meteorRange,
+        double meteorCastVigorCost) -> ScoreValue;
 
 }  // namespace shardok
 

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

@@ -15,7 +15,7 @@ auto UnitIdsRequiringWaterCrossing(
         const PlayerId pid,
         const CoordsSet &destinations,
         const APDCache &apdCache,
-        const SettingsGetter &settings) -> vector<UnitId> {
+        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
     // Put out all the fires, except on bridges
     fb::HexMapW mapCopy = fb::CopyHexMap(gameState->hex_map());
     for (uint32_t index = 0; index < mapCopy->terrain()->size(); index++) {
@@ -36,7 +36,7 @@ auto UnitIdsRequiringWaterCrossing(
     for (const auto *unit : *gameState->units()) {
         if (unit->player_id() != pid) continue;
 
-        const auto &battType = settings.GetBattalionType(unit->battalion().type());
+        const auto &battType = battalionTypeGetter(unit->battalion().type());
 
         if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) {
             for (const Coords &destination : destinations) {
@@ -76,8 +76,7 @@ auto UnitIdsRequiringWaterCrossing(
 auto UnitIdsToCreateWaterCrossing(
         const GameStateW &gameState,
         const PlayerId pid,
-        const APDCache & /*apdCache*/,
-        const SettingsGetter &settings) -> vector<UnitId> {
+        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
     vector<UnitId> unitIds{};
 
     for (const auto *unit : *gameState->units()) {
@@ -88,7 +87,7 @@ auto UnitIdsToCreateWaterCrossing(
         if (!unit->has_attached_hero()) continue;
 
         const auto profession = unit->attached_hero().profession_info().profession();
-        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
 
         if (profession == net::eagle0::shardok::storage::fb::Profession_ENGINEER ||
             (profession == net::eagle0::shardok::storage::fb::Profession_MAGE &&
@@ -199,14 +198,14 @@ auto IntendedCrossingStarts(
         const GameStateW &gameState,
         const vector<UnitId> &unitIdsCreatingCrossing,
         const CoordsSet &tilesToStartCrossingFrom,
-        const MapId &mapId,
         const APDCache &apdCache,
-        const SettingsGetter &settings) -> CoordsSet {
+        const BattalionTypeGetter &battalionTypeGetter) -> CoordsSet {
     CoordsSet intendedCrossingStarts(gameState->hex_map());
+    const MapId mapId = apdCache->GetMapId(gameState->hex_map());
     for (const UnitId uid : unitIdsCreatingCrossing) {
         const Unit *unit = gameState->units()->Get(uid);
         const Coords &location = unit->location();
-        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
         const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
 
         if (location.row() >= 0) {
@@ -219,4 +218,111 @@ auto IntendedCrossingStarts(
     return intendedCrossingStarts;
 }
 
+using Unit = net::eagle0::shardok::storage::fb::Unit;
+
+constexpr double kNoRequiredCrossingScore = std::numeric_limits<double>::max();
+constexpr double kNoCrossingCreatorsScore = std::numeric_limits<double>::min();
+
+auto WaterCrossingScore(
+        const PlayerId playerId,
+        const BattalionTypeGetter &battalionTypeGetter,
+        const GameStateW &gameState,
+        const CoordsSet &castleCoords,
+        const CoordsSet &startCrossingFrom,
+        const APDCache &apdCache) -> double {
+    uint32_t castleClaimCount = 0;
+    for (const auto *unit : *gameState->units()) {
+        if (unit->player_id() != playerId) continue;
+        const auto status = unit->status();
+        if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
+            status != net::eagle0::shardok::storage::fb::UnitStatus_RESERVE_UNIT)
+            continue;
+        if (!unit->has_attached_hero()) continue;
+
+        ++castleClaimCount;
+    }
+
+    CoordsSet destinations = castleCoords;
+    if (castleClaimCount < castleCoords.size()) {
+        destinations = CoordsSet(gameState->hex_map());
+        for (const auto *enemyUnit : *gameState->units()) {
+            if (enemyUnit->player_id() == playerId) continue;
+            const auto status = enemyUnit->status();
+            if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;
+            AssertValid(enemyUnit->location(), gameState->hex_map());
+            destinations.Add(enemyUnit->location());
+        }
+    }
+
+    const auto unitIdsRequiringCrossing = UnitIdsRequiringWaterCrossing(
+            gameState,
+            playerId,
+            castleCoords,
+            apdCache,
+            battalionTypeGetter);
+    if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;
+
+    const auto unitIdsCreatingCrossing =
+            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
+    if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;
+
+    double totalScore = 0;
+
+    const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
+
+    // First put a big penalty on the distance for units that can create a crossing
+    for (const UnitId uid : unitIdsCreatingCrossing) {
+        const Unit *unit = gameState->units()->Get(uid);
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        Coords location = unit->location();
+
+        int thisDistance;
+        if (location.row() < 0) thisDistance = 1000;
+        else {
+            const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
+
+            thisDistance = MinimumDistance(apd, location, startCrossingFrom);
+        }
+
+        totalScore -= thisDistance * 100.0;
+    }
+
+    // Now a smaller penalty for distance for units that need to cross, except if they block -- then
+    // a large penalty
+    for (const UnitId uid : unitIdsRequiringCrossing) {
+        // If this unit ID can also create a crossing, we already handled it
+        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
+
+        const Unit *unit = gameState->units()->Get(uid);
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        Coords location = unit->location();
+        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
+
+        int thisDistance;
+        if (location.row() < 0) thisDistance = 1000;
+        else { thisDistance = MinimumDistance(apd, location, startCrossingFrom); }
+
+        bool targetBlocks = false;
+        // If we're not capable of creating a crossing, don't get in the way of somebody that is.
+        for (const UnitId crossingUid : unitIdsCreatingCrossing) {
+            const auto *crossingCapableUnit = gameState->units()->Get(crossingUid);
+
+            // Don't check for units that aren't yet placed
+            if (crossingCapableUnit->location().row() < 0) continue;
+            AssertValid(crossingCapableUnit->location(), gameState->hex_map());
+
+            if (thisDistance <
+                MinimumDistance(apd, crossingCapableUnit->location(), startCrossingFrom)) {
+                targetBlocks = true;
+                break;
+            }
+        }
+        if (targetBlocks) continue;
+
+        totalScore -= thisDistance;
+    }
+
+    return totalScore;
+}
+
 }  // namespace shardok

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

@@ -5,6 +5,7 @@
 #ifndef EAGLE0_AIWATERCROSSINGCALCULATOR_HPP
 #define EAGLE0_AIWATERCROSSINGCALCULATOR_HPP
 
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
@@ -34,14 +35,13 @@ auto UnitIdsRequiringWaterCrossing(
         PlayerId pid,
         const CoordsSet& destinations,
         const APDCache& apdCache,
-        const SettingsGetter& settings) -> vector<UnitId>;
+        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
 
 // Units belonging to the player that are capable of creating water crossings
 auto UnitIdsToCreateWaterCrossing(
         const GameStateW& gameState,
         PlayerId pid,
-        const APDCache& apdCache,
-        const SettingsGetter& settings) -> vector<UnitId>;
+        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
 
 // Whether a unit of the given type can reach destination from origin, given the current state
 // of the map
@@ -71,9 +71,17 @@ auto IntendedCrossingStarts(
         const GameStateW& gameState,
         const vector<UnitId>& unitIdsCreatingCrossing,
         const CoordsSet& tilesToStartCrossingFrom,
-        const MapId& mapId,
         const APDCache& apdCache,
-        const SettingsGetter& settings) -> CoordsSet;
+        const BattalionTypeGetter& battalionTypeGetter) -> CoordsSet;
+
+// Calculate score based on water crossing strategy
+auto WaterCrossingScore(
+        PlayerId playerId,
+        const BattalionTypeGetter& battalionTypeGetter,
+        const GameStateW& gameState,
+        const CoordsSet& castleCoords,
+        const CoordsSet& startCrossingFrom,
+        const APDCache& apdCache) -> double;
 
 }  // namespace shardok
 

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

@@ -18,7 +18,7 @@ constexpr ScoreValue kNoRequiredCrossingScore = std::numeric_limits<ScoreValue>:
 constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>::min();
 
 [[nodiscard]] auto AIWaterCrossingCommandChooser::WaterCrossingScore(
-        const SettingsGetter &settingsGetter,
+        const BattalionTypeGetter &battalionTypeGetter,
         const GameStateW &gameState,
         const CoordsSet &castleCoords,
         const CoordsSet &startCrossingFrom) const -> ScoreValue {
@@ -51,15 +51,13 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
             playerId,
             castleCoords,
             apdCache,
-            settingsGetter);
+            battalionTypeGetter);
     if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;
 
     const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
     if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;
 
-    fprintf(stderr, "%lu units require a water crossing\n", unitIdsRequiringCrossing.size());
-
     ScoreValue totalScore = 0;
 
     const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
@@ -67,7 +65,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
     // First put a big penalty on the distance for units that can create a crossing
     for (const UnitId uid : unitIdsCreatingCrossing) {
         const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
         Coords location = unit->location();
 
         int thisDistance;
@@ -88,7 +86,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
         if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
 
         const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
         Coords location = unit->location();
         const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
 
@@ -120,7 +118,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
 }
 
 auto AIWaterCrossingCommandChooser::StartCrossingFrom(
-        const SettingsGetter &settingsGetter,
+        const BattalionTypeGetter &battalionTypeGetter,
         const GameStateW &gameState,
         const CoordsSet &castleCoords) const -> CoordsSet {
     CoordsSet startCrossingFrom(gameState->hex_map());
@@ -154,16 +152,16 @@ auto AIWaterCrossingCommandChooser::StartCrossingFrom(
             playerId,
             castleCoords,
             apdCache,
-            settingsGetter);
+            battalionTypeGetter);
     if (unitIdsRequiringCrossing.empty()) return startCrossingFrom;
 
     const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
     if (unitIdsCreatingCrossing.empty()) return startCrossingFrom;
 
     for (const UnitId uid : unitIdsRequiringCrossing) {
         const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
+        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
         Coords origin = unit->location();
 
         // FIXME: this is just grabbing the first starting position, ideally we'd try them all

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

@@ -6,19 +6,16 @@
 #define EAGLE0_AIWATERCROSSINGCOMMANDCHOOSER_HPP
 
 #include <utility>
-#include <vector>
 
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/fb_helpers/FlatbufferWrapper.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
 using GameState = net::eagle0::shardok::storage::fb::GameState;
 using Unit = net::eagle0::shardok::storage::fb::Unit;
 using ScoreValue = double;
@@ -33,13 +30,13 @@ public:
         : playerId(pid),
           apdCache(std::move(apdCache)) {}
 
-    auto StartCrossingFrom(
-            const SettingsGetter &settingsGetter,
+    [[nodiscard]] auto StartCrossingFrom(
+            const BattalionTypeGetter &battalionTypeGetter,
             const GameStateW &gameState,
             const CoordsSet &castleCoords) const -> CoordsSet;
 
     [[nodiscard]] auto WaterCrossingScore(
-            const SettingsGetter &settingsGetter,
+            const BattalionTypeGetter &battalionTypeGetter,
             const GameStateW &gameState,
             const CoordsSet &castleCoords,
             const CoordsSet &startCrossingFrom) const -> ScoreValue;

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

@@ -210,4 +210,556 @@ 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.
+This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
+
+## AIScoreCalculator Function Reference
+
+### Public Interface Functions
+
+#### `GuessedStateScore`
+**Purpose**: Evaluates the score of a game state from the perspective of the current AI strategy without performing any commands.
+
+**Parameters**:
+- `isDefender`: Whether the AI is playing as defender
+- `state`: Current game state to evaluate
+- `aiStrategy`: Strategy being used (attack castles, hold castles, scatter, etc.)
+- `allCastleCoords`: Set of all castle coordinates on the map
+- `settingsGetter`: Game configuration and rules
+- `apdCache`: Cached action point distances for movement calculations
+- `alCache`: Cached attack locations for combat calculations
+
+**Returns**: Score value representing how favorable the state is for the evaluating player (positive = good, negative = bad)
+
+#### `CommandScore`
+**Purpose**: Evaluates the score for a specific command using lookahead search to consider future consequences.
+
+**Parameters**:
+- `pid`: Player ID executing the command
+- `isDefender`: Whether the player is a defender
+- `remainingLookahead`: Depth of recursive search remaining
+- `maxRepeatCount`: Number of random simulations for non-deterministic commands
+- `guessedEngine`: Current game engine state
+- `attackerStrategy`: Strategy being used by attackers
+- `currentUtility`: Current game state score before command execution
+- `settingsGetter`: Game configuration
+- `allCastleCoords`: Castle locations
+- `apdCache` & `alCache`: Cached distance/attack calculations
+- `commandIndex`: Index of command to evaluate
+- `deadline`: Time limit for computation
+
+**Returns**: Future containing the final score after lookahead evaluation
+
+### Internal Core Functions
+
+#### `BuildDecisionTree` (NEW)
+**Purpose**: Builds a complete decision tree containing all evaluated command paths up to the specified depth.
+
+**Process**:
+1. Filters commands using `AICommandFilter` to reduce search space
+2. For each command, calls `ExecuteCommandForTree` to build complete subtrees
+3. Returns full tree with all possible moves and their consequences
+4. Identifies best command within the complete tree structure
+
+**Returns**: `std::future<CommandDecisionTree>` containing the complete decision tree
+
+#### `BestCommandIndex` (Legacy - Wrapper)
+**Purpose**: Backward compatibility wrapper that uses `BuildDecisionTree` but returns traditional `IndexAndScore`.
+
+**Process**:
+1. Calls `BuildDecisionTree` to get complete tree
+2. Extracts best command information for compatibility
+3. Returns only the optimal command details in legacy format
+
+#### `ExecuteCommandForTree` (NEW)
+**Purpose**: Executes a command and creates a tree node with the resulting game state and scores.
+
+**Process**:
+1. Creates engine copy and executes the command with given random seed
+2. Creates `CommandTreeNode` with command results and game state
+3. Calculates immediate score using `GuessedStateScore`
+4. Calls `RecursiveTreeBuilder` to populate child nodes if depth allows
+5. Calculates lookahead score from children (or uses immediate score)
+
+**Returns**: `std::unique_ptr<CommandTreeNode>` containing the command execution results and subtree
+
+#### `RecursiveTreeBuilder` (NEW)
+**Purpose**: Recursively populates child nodes of a tree node by building subtrees for subsequent moves.
+
+**Process**:
+1. Gets available commands for the next player
+2. Filters commands to reduce search space
+3. For each command, calls `ExecuteCommandForTree` to create child nodes
+4. Handles different command types (deterministic, odds-based, random)
+5. Populates the parent node's children vector with complete subtrees
+
+#### `CalcOne` (Legacy)
+**Purpose**: Executes a single command simulation with specified randomness and returns both immediate and lookahead scores.
+
+**Process**:
+1. Creates engine copy and executes the command with given random seed
+2. Calculates immediate score using `GuessedStateScore`
+3. Initiates recursive lookahead calculation if depth remains
+4. Handles timeouts gracefully by returning default scores
+
+#### `EvaluateCommand`
+**Purpose**: Lower-level command evaluation that handles different command types appropriately.
+
+**Command Type Handling**:
+- **Deterministic**: Single evaluation with average randomness (0.5)
+- **Odds-based**: Two evaluations (success/failure) weighted by success probability
+- **Non-deterministic**: Multiple evaluations with distributed random values, averaged
+
+#### `BasicLookaheadCalculator`
+**Purpose**: Recursive lookahead search that finds the best future command sequence and propagates scores backward.
+
+**Features**:
+- Uses transposition table to cache previously computed positions
+- Handles depth limits and terminal states
+- Returns futures for asynchronous computation
+- Stores results in transposition table for reuse
+
+### Strategy-Specific Scoring Functions
+
+#### `AttackerScoreForState`
+**Purpose**: Calculates state score from attacker perspective based on strategy type.
+
+**Strategy Support**:
+- `STRATEGY_ATTACK_CASTLES`: Prioritizes capturing castle positions
+- `STRATEGY_ATTACK_UNITS`: Focuses on eliminating defender units
+- `STRATEGY_HOLD_CASTLES`: Maintains control of captured castles
+- `STRATEGY_CROSS_RIVERS`: Special water crossing objectives
+- `STRATEGY_FLEE`: Escape-focused scoring
+
+#### `DefenderScoreForState`
+**Purpose**: Calculates state score from defender perspective.
+
+**Strategy Support**:
+- `STRATEGY_HOLD_CASTLES`: Defend critical castle positions
+- `STRATEGY_SCATTER`: Spread units to avoid elimination
+- `STRATEGY_FLEE`: Escape-focused scoring
+
+#### `AttackerUnitsScore`
+**Purpose**: Core unit valuation function that calculates total value of all units on the board with contextual modifiers.
+
+**Features**:
+- Uses `UnitValue` for individual unit calculations
+- Applies distance multipliers based on proximity to objectives
+- Handles special cases like undead, VIP units, and scattered defenders
+- Incorporates castle bonuses and environmental penalties
+
+### Specialized Strategy Functions
+
+#### `DefenderScatterStrategyScoreForState`
+**Purpose**: Implements scatter strategy scoring that rewards defensive units for staying far from enemies and friendlies.
+
+#### `DefenderHoldCastlesStrategyScoreForState`
+**Purpose**: Implements castle defense strategy with victory condition scoring.
+
+#### `FleeStrategyScoreForState`
+**Purpose**: Implements flee strategy that heavily penalizes remaining on the battlefield.
+
+### Utility Functions
+
+#### `AttackerMultiplierForTargetDistance`
+**Purpose**: Calculates distance-based scoring multipliers for attackers based on proximity to priority targets.
+
+**Features**:
+- Uses recursive priority list evaluation
+- Accounts for occupied vs. unoccupied targets
+- Incorporates brave water crossing capabilities
+- Uses cached action point distances for efficiency
+
+#### `CommandSorter`
+**Purpose**: Comparison function for ranking commands by lookahead score (primary) and immediate score (tiebreaker).
+
+#### `IsDeterministic`
+**Purpose**: Determines if a command type has predictable outcomes or requires random simulation.
+
+### Performance and Caching
+
+#### `EffectiveDistanceCache`
+**Purpose**: Memoization cache for expensive distance calculations between units and targets.
+
+#### `AttackerScorePerformanceLogger`
+**Purpose**: Performance monitoring system that tracks call frequency and timing for `AttackerScoreForState`.
+
+The function architecture supports parallel evaluation, caching, and recursive lookahead while maintaining separation between strategy-specific logic and core evaluation mechanics.
+
+## Decision Tree Data Structures (NEW)
+
+### CommandTreeNode
+**Purpose**: Represents a single command execution and its consequences in the decision tree.
+
+**Key Fields**:
+- `commandIndex`: Index of the command in the original command list
+- `commandType`: Type of command (MOVE, MELEE, END_TURN, etc.)
+- `immediateScore`: Score of the game state immediately after this command
+- `lookaheadScore`: Best achievable score considering future moves
+- `resultingGameState`: Game state after command execution
+- `children`: Vector of child nodes representing subsequent possible moves
+- `playerId`, `depth`, `isDefender`: Metadata about the command context
+
+**Features**:
+- Stores complete game state for each decision point
+- Maintains parent-child relationships for tree traversal
+- Supports both immediate and lookahead scoring
+- Contains metadata for debugging and analysis
+
+### CommandDecisionTree
+**Purpose**: Complete decision tree containing all evaluated command paths from a given position.
+
+**Key Fields**:
+- `rootNodes`: All possible first moves from the starting position
+- `bestCommand`: Pointer to the optimal root command
+- `maxDepth`: Maximum lookahead depth of the tree
+- `totalNodes`: Total number of nodes in the tree (for statistics)
+
+**Features**:
+- Provides complete visibility into AI decision-making process
+- Enables analysis of alternative moves and their consequences
+- Supports tree statistics and debugging information
+- Maintains backward compatibility through `GetBestCommandIndex()`
+
+**Memory Management**:
+- Uses `std::unique_ptr` for automatic memory cleanup
+- `GameStateW` objects are stored directly (not shared pointers for simplicity)
+- Tree structure ensures proper cleanup when nodes go out of scope
+
+### Tree vs. Legacy Approach Comparison
+
+| Aspect | Legacy (Single Best) | Tree-Based (Complete) |
+|--------|---------------------|----------------------|
+| **Output** | Best command only | Complete decision tree |
+| **Memory** | Minimal | Higher (stores all paths) |
+| **Analysis** | Limited visibility | Full decision transparency |
+| **Debugging** | Single command info | Complete move sequences |
+| **Performance** | Slightly faster | Comparable (same calculations) |
+| **Compatibility** | Direct usage | Wrapper maintains compatibility |
+
+### Usage Patterns
+
+**For AI Decision Making**:
+```cpp
+auto treeFuture = BuildDecisionTree(pid, isDefender, depth, maxRepeat,
+                                   engine, strategy, utility, settings,
+                                   castles, apdCache, alCache, deadline);
+CommandDecisionTree tree = treeFuture.get();
+size_t bestCommand = tree.bestCommand->commandIndex;
+```
+
+**For Analysis and Debugging**:
+```cpp
+CommandDecisionTree tree = treeFuture.get();
+// Examine all possible moves
+for (const auto& rootNode : tree.rootNodes) {
+    std::cout << "Command " << rootNode->commandIndex
+              << " Score: " << rootNode->lookaheadScore << std::endl;
+    // Traverse children to see consequences
+    for (const auto& child : rootNode->children) {
+        // ... analyze child moves
+    }
+}
+```
+
+**Legacy Compatibility**:
+```cpp
+// Existing code continues to work unchanged
+auto indexScoreFuture = BestCommandIndex(pid, isDefender, ...);
+IndexAndScore result = indexScoreFuture.get();
+size_t bestCommand = result.index;
+```
+
+The tree-based approach provides complete decision transparency while maintaining full backward compatibility with existing AI code.
+
+## MCTS Alternative: Randomness Handling Recommendations
+
+The new MCTS-based AI system is available in `MCTSAI.hpp/.cpp` and provides an alternative to the iterative deepening approach. However, the current MCTS implementation uses simplified randomness handling compared to the sophisticated approach in the original system.
+
+### Current MCTS Limitations
+
+1. **Expansion Phase**: Uses average rolls (0.5) for all commands during tree expansion
+2. **Simulation Phase**: Uses random command selection with average rolls
+3. **Missing**: No explicit chance nodes for commands with `HasOdds()`
+4. **Missing**: No multi-sample evaluation for stochastic commands
+
+### Recommended Improvements: Chance Node Integration
+
+#### 1. **Explicit Chance Nodes** (Highest Priority)
+
+For commands with `HasOdds()`, create explicit chance nodes in the MCTS tree:
+
+```cpp
+// During MCTSExpansion
+if (descriptor->HasOdds()) {
+    // Create TWO child nodes: success and failure
+    auto successNode = CreateMCTSNode(commandIndex, SUCCESS_VARIANT);
+    auto failureNode = CreateMCTSNode(commandIndex, FAILURE_VARIANT);
+
+    // Execute with deterministic rolls (matching original system)
+    ExecuteWithRoll(successNode, 1.0 - successChance/2.0);  // High roll
+    ExecuteWithRoll(failureNode, (1.0 - successChance)/2.0); // Low roll
+
+    // Set probability weights for selection
+    successNode->probabilityWeight = successChance;
+    failureNode->probabilityWeight = 1.0 - successChance;
+}
+```
+
+#### 2. **Weighted Selection for Chance Nodes**
+
+Modify `MCTSSelection` to handle chance nodes:
+
+```cpp
+if (node->isChanceNode) {
+    // Select based on probability distribution, not UCB1
+    return SelectByProbability(node->children);
+} else {
+    // Normal UCB1 selection for decision nodes
+    return node->GetBestChild(explorationConstant);
+}
+```
+
+#### 3. **Probability-Weighted Backpropagation**
+
+Update backpropagation to account for chance node probabilities:
+
+```cpp
+void MCTSBackpropagation(MCTSNode* node, double reward) {
+    while (node) {
+        node->visitCount++;
+
+        // Weight reward by probability for chance nodes
+        double weightedReward = reward;
+        if (node->parent && node->parent->isChanceNode) {
+            weightedReward *= node->probabilityWeight;
+        }
+
+        node->totalReward += weightedReward;
+        node->averageReward = node->totalReward / node->visitCount;
+        node = node->parent;
+    }
+}
+```
+
+#### 4. **Multi-Sample Commands**
+
+For commands without explicit odds but with randomness, use stratified sampling:
+
+```cpp
+// During expansion, create multiple child nodes with different rolls
+for (int sample = 0; sample < numSamples; ++sample) {
+    double roll = static_cast<double>(sample) / (numSamples - 1);
+    auto sampleNode = CreateMCTSNodeWithRoll(commandIndex, roll);
+    sampleNode->probabilityWeight = 1.0 / numSamples;
+}
+```
+
+### Benefits of Chance Node Integration
+
+1. **Accurate Evaluation**: Preserves the sophisticated randomness handling from the original system
+2. **Better Convergence**: MCTS can properly explore both success/failure outcomes
+3. **Realistic Simulations**: Tree accurately represents game's probability distributions
+4. **Comparable Results**: Makes MCTS results directly comparable to iterative deepening
+
+### Implementation Priority
+
+1. **Phase 1**: Add explicit chance nodes for `HasOdds()` commands
+2. **Phase 2**: Implement probability-weighted selection and backpropagation
+3. **Phase 3**: Add multi-sample support for general stochastic commands
+4. **Phase 4**: Optimize performance with lazy expansion of chance nodes
+
+### Alternative: Determinization Approach
+
+If explicit chance nodes prove too complex, consider **determinization**:
+
+- Run multiple MCTS trees with different fixed random seeds
+- Aggregate results across all determinizations
+- Simpler to implement but potentially less accurate than explicit chance nodes
+
+### Switching Between AI Systems
+
+Both AI systems (`IterativeDeepeningAI` and `MCTSAI`) implement compatible interfaces. The algorithm is selected at **runtime** via the ShardokAIClient constructor:
+
+```cpp
+// Using Iterative Deepening (default)
+ShardokAIClient client(playerId, isDefender, hexMap, settings);
+// Or explicitly:
+ShardokAIClient client(playerId, isDefender, hexMap, settings,
+                      AIAlgorithmType::ITERATIVE_DEEPENING);
+
+// Using MCTS
+ShardokAIClient client(playerId, isDefender, hexMap, settings,
+                      AIAlgorithmType::MCTS);
+
+// Note: MCTS configuration can be customized via MCTSConfig:
+// - maxIterations: 10000 (max MCTS iterations per move)
+// - maxSimulationDepth: 10 (depth for rollout phase)
+// - maxTreeDepth: 20 (max tree depth to prevent stack overflow)
+// - explorationConstant: 1.414 (UCB1 exploration vs exploitation)
+// - useMultithreading: true (APD cache is thread-safe with TLS + mutex protection)
+// - numThreads: 4
+```
+
+The selection is made per AI client instance, allowing different algorithms for different players or game situations within the same server process.
+
+#### Direct AI Usage (Lower Level)
+
+Both AI systems can also be used directly:
+
+```cpp
+// Using Iterative Deepening directly
+auto iterativeAI = IterativeDeepeningAI(playerId, isDefender, strategy,
+                                       castleCoords, apdCache, alCache);
+auto result = iterativeAI.IterativeSearch(settings, state, commands, budget);
+
+// Using MCTS directly
+auto mctsAI = MCTSAI(playerId, isDefender, strategy,
+                    castleCoords, apdCache, alCache);
+auto result = mctsAI.Search(settings, state, commands, budget);
+```
+
+#### Algorithm Comparison
+
+| Feature | Iterative Deepening | MCTS |
+|---------|-------------------|------|
+| **Randomness Handling** | Sophisticated (chance nodes, multi-sample) | Simplified (average rolls) |
+| **Performance** | Single-threaded | Multithreaded |
+| **Search Type** | Fixed depth with iterative deepening | Adaptive with time budget |
+| **Memory Usage** | Lower | Higher (maintains tree) |
+| **Max Tree Depth** | Limited by lookahead setting | Limited by `maxTreeDepth` config (default: 20) |
+| **Tree Destruction** | Not applicable | Iterative (avoids stack overflow) |
+| **Best For** | Precise evaluation, production | Performance testing, fast decisions |
+
+The MCTS implementation provides a solid foundation. Known limitations:
+1. **Randomness Handling**: Simplified compared to iterative deepening (no explicit chance nodes)
+2. **Simulation Quality**: Uses random rollouts instead of sophisticated evaluation
+
+Note: The APD cache is fully thread-safe using thread-local storage and mutex-protected shared cache.
+
+Adding chance node handling and ensuring thread safety would make it a superior replacement for the iterative deepening approach while maintaining the sophisticated randomness evaluation that makes the current system effective.
+
+## MCTS Configuration Options
+
+The MCTS AI system provides extensive configuration through the `MCTSConfig` structure:
+
+### Core MCTS Parameters
+
+```cpp
+struct MCTSConfig {
+    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
+    int maxSimulationDepth = 1000;       // Maximum depth for rollout
+    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
+    bool useMultithreading = true;       // Enable parallel MCTS
+    int numThreads = 16;                 // Number of threads for parallel MCTS (when enabled)
+    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
+    bool enableTranspositionDetection = true;  // Enable pruning of duplicate states
+    double immediateScoreTieBreakThreshold = 5.0;  // When avg rewards differ by less than this, prefer higher immediate score
+    double visitCountTolerance = 0.05;  // Treat visit counts as equal if within this % of best count
+    bool enableImmediateScoreInUCB1 = true;  // Apply immediate score tie-breaking in UCB1 selection too
+};
+```
+
+### Exploration vs Exploitation
+
+- **`explorationConstant`**: Controls the exploration vs exploitation balance in UCB1 selection
+  - Higher values (>1.414): More exploration of unvisited nodes
+  - Lower values (<1.414): More exploitation of known good moves
+  - Default: 1.414 (√2, theoretical optimum for UCB1)
+
+### Tree Structure Limits
+
+- **`maxTreeDepth`**: Prevents stack overflow in deep game trees
+  - Default: 2000 (very high limit for most tactical scenarios)
+  - Terminal detection stops expansion when this depth is reached
+
+- **`maxSimulationDepth`**: Controls rollout length during simulation phase
+  - Default: 1000 (sufficient for most tactical scenarios)
+  - Longer simulations provide more accurate estimates but use more time
+
+### Multithreading Configuration
+
+- **`useMultithreading`**: Enable/disable parallel MCTS execution
+  - Default: true (takes advantage of modern multi-core CPUs)
+  - Requires thread-safe game engine and scoring components
+
+- **`numThreads`**: Number of worker threads for parallel tree building
+  - Default: 16 (adjust based on available CPU cores)
+  - More threads can improve search speed but with diminishing returns
+
+### Simulation Policies
+
+The `MCTSSimulationPolicy` enum controls how commands are selected during the rollout phase:
+
+- **`RANDOM`**: Pure random selection from all available commands
+  - Fastest but least informed simulations
+  - Good baseline for testing MCTS convergence
+
+- **`FILTERED_RANDOM`**: Random selection from AICommandFilter-approved commands
+  - Eliminates obviously bad moves (moving away from objectives, etc.)
+  - Better simulation quality with minimal overhead
+
+- **`BEST_IMMEDIATE`**: Always choose command with highest immediate score
+  - Most informed simulations
+  - Slower but higher quality rollouts
+  - Default setting for production use
+
+- **`WEIGHTED_BEST_IMMEDIATE`**: Random selection weighted by immediate score ranking
+  - Balances exploration with informed choice
+  - Alternative to pure greedy selection
+
+### Transposition Detection
+
+- **`enableTranspositionDetection`**: Enable pruning of duplicate game states
+  - Default: true (improves search efficiency)
+  - Uses hash-based state identification
+  - Prevents wasted computation on equivalent positions reached via different move sequences
+
+### Immediate Score Tie-Breaking
+
+These settings address MCTS's tendency to choose indirect paths when direct paths lead to the same outcome:
+
+- **`immediateScoreTieBreakThreshold`**: Score difference threshold for tie-breaking
+  - Default: 5.0 (when backpropagated rewards differ by less than this, prefer immediate score)
+  - Helps AI choose direct moves over equivalent indirect sequences
+  - Improves user experience by reducing unnecessary intermediate moves
+
+- **`visitCountTolerance`**: Visit count equality threshold for tie-breaking
+  - Default: 0.05 (5% tolerance - visit counts within this percentage are considered equal)
+  - Prevents minor visit count differences from overriding immediate score preferences
+
+- **`enableImmediateScoreInUCB1`**: Apply immediate score tie-breaking during exploration
+  - Default: true (consistent tie-breaking in both exploration and final selection)
+  - When UCB1 values are very close, prefer nodes with higher immediate scores
+  - Improves convergence on direct paths to objectives
+
+### Usage Example
+
+```cpp
+// Custom MCTS configuration for performance testing
+MCTSConfig config;
+config.explorationConstant = 2.0;  // More exploration
+config.simulationPolicy = MCTSSimulationPolicy::FILTERED_RANDOM;  // Faster rollouts
+config.numThreads = 8;  // Reduce threads for testing environment
+config.immediateScoreTieBreakThreshold = 10.0;  // More aggressive tie-breaking
+
+MCTSAI ai(playerId, isDefender, strategy, castleCoords, apdCache, alCache, config);
+```
+
+### Configuration Recommendations
+
+**For Production Use:**
+- Use default settings for balanced performance and quality
+- Consider reducing `numThreads` on systems with limited CPU cores
+- `BEST_IMMEDIATE` simulation policy provides highest quality decisions
+
+**For Performance Testing:**
+- `FILTERED_RANDOM` or `RANDOM` simulation policies for faster rollouts
+- Lower `explorationConstant` (1.0) for more exploitation
+- Disable transposition detection for baseline comparison
+
+**For Analysis/Debugging:**
+- Single-threaded execution (`useMultithreading = false`) for deterministic results
+- Higher `immediateScoreTieBreakThreshold` to emphasize direct paths
+- `BEST_IMMEDIATE` simulation for most predictable behavior
+
+The configuration system allows fine-tuning MCTS behavior for different scenarios while maintaining compatibility with the existing AI infrastructure.

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

@@ -1,5 +1,16 @@
 load("//tools:copts.bzl", "COPTS")
 
+cc_library(
+    name = "ai_common_types",
+    hdrs = ["AICommonTypes.hpp"],
+    copts = COPTS,
+    visibility = ["//visibility:public"],
+    deps = [
+        "//src/main/cpp/net/eagle0/shardok/library:battalion_type",
+        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
+    ],
+)
+
 cc_library(
     name = "ai_attacker_strategy_selector",
     srcs = ["AIAttackerStrategySelector.cpp"],
@@ -28,14 +39,15 @@ cc_library(
     hdrs = ["AIAttackGroups.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
     deps = [
         ":ai_attack_locations",
+        ":ai_common_types",
         ":ai_score_utilities",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
         "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
         "//src/main/flatbuffer/net/eagle0/shardok/storage:hex_map_cc_fbs",
         "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
@@ -47,6 +59,10 @@ cc_library(
     srcs = ["AIAttackLocations.cpp"],
     hdrs = ["AIAttackLocations.hpp"],
     copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
+    ],
     deps = [
         ":ai_score_utilities",
         "//src/main/cpp/net/eagle0/shardok/library/map:terrain",
@@ -85,11 +101,14 @@ cc_library(
     hdrs = ["AIDistanceDebuf.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
     deps = [
         ":ai_attack_locations",
+        ":ai_common_types",
         ":ai_score_utilities",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
@@ -118,8 +137,10 @@ cc_library(
     hdrs = ["AIScoreUtilities.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
     deps = [
         "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
@@ -142,9 +163,48 @@ cc_library(
         ":ai_score_utilities",
         ":ai_unit_score_calculator",
         "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
         "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
+    ],
+)
+
+cc_library(
+    name = "ai_heuristic_weighting",
+    srcs = ["AIHeuristicWeighting.cpp"],
+    hdrs = ["AIHeuristicWeighting.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+    ],
+    deps = [
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
+        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
+        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
+    ],
+)
+
+cc_library(
+    name = "ai_command_evaluator",
+    srcs = ["AICommandEvaluator.cpp"],
+    hdrs = ["AICommandEvaluator.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+    ],
+    deps = [
+        ":ai_command_filter",
+        ":ai_strategy",
+        ":transposition_table",
+        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
+        "//src/main/cpp/net/eagle0/shardok/library/util:hex_cube_utils",
+        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
     ],
 )
 
@@ -154,16 +214,18 @@ cc_library(
     hdrs = ["AICommandFilter.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
     ],
     deps = [
+        ":ai_common_types",
         "//src/main/cpp/net/eagle0/shardok/library:engine",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
         "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
         "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
         "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
         "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
     ],
 )
@@ -182,38 +244,19 @@ cc_library(
     ],
 )
 
-cc_library(
-    name = "ai_score_calculator",
-    srcs = ["AIScoreCalculator.cpp"],
-    hdrs = ["AIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_attacker_strategy_selector",
-        ":ai_command_filter",
-        ":ai_unit_score_calculator",
-        ":ai_victory_condition_score_calculator",
-        ":transposition_table",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library/view_filters:game_state_guesser",
-    ],
-)
-
 cc_library(
     name = "ai_strategy",
     srcs = ["AIStrategy.cpp"],
     hdrs = ["AIStrategy.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
     deps = [
         ":ai_attack_groups",
+        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
     ],
 )
 
@@ -223,6 +266,7 @@ cc_library(
     hdrs = ["AIUnitScoreCalculator.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
@@ -233,27 +277,6 @@ cc_library(
     ],
 )
 
-cc_library(
-    name = "ai_victory_condition_score_calculator",
-    srcs = ["AIVictoryConditionScoreCalculator.cpp"],
-    hdrs = ["AIVictoryConditionScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_attack_groups",
-        ":ai_attack_locations",
-        ":ai_distance_debuf",
-        ":ai_score_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
-    ],
-)
-
 cc_library(
     name = "ai_water_crossing_calculator",
     srcs = ["AIWaterCrossingCalculator.cpp"],
@@ -261,10 +284,13 @@ cc_library(
     copts = COPTS,
     visibility = [
         "//src/main/cpp/net/eagle0/shardok:__pkg__",
+        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
         "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
     ],
     deps = [
+        ":ai_common_types",
         ":ai_minimum_distance_and_target",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
         "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
@@ -286,7 +312,6 @@ cc_library(
         "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
     ],
 )
 
@@ -296,6 +321,7 @@ 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__",
     ],
@@ -314,19 +340,30 @@ cc_library(
     hdrs = ["IterativeDeepeningAI.hpp"],
     copts = COPTS,
     visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
         "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
         "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
     ],
     deps = [
         ":ai_attacker_strategy_selector",
+        ":ai_command_evaluator",
         ":ai_defender_strategy_selector",
-        ":ai_score_calculator",
         ":ai_time_budget",
         ":ai_water_crossing_command_chooser",
         "//src/main/cpp/net/eagle0/common:time_utils",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
         "//src/main/cpp/net/eagle0/shardok/library:engine",
         "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
+    ],
+)
+
+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__",
     ],
 )
 
@@ -338,15 +375,21 @@ cc_library(
     visibility = ["//visibility:public"],
     deps = [
         ":ai_attacker_strategy_selector",
+        ":ai_config",
         ":ai_defender_strategy_selector",
         ":ai_flee_decision_calculator",
-        ":ai_iterative_deepening",
-        ":ai_score_calculator",
+        ":ai_iterative_deepening",  # Direct dependency for runtime selection
         ":ai_time_budget",
         ":ai_water_crossing_command_chooser",
         "//src/main/cpp/net/eagle0/common:time_utils",
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:shardok_mcts_ai",  # MCTS with abstraction layer
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:mcts_optimized_ai_score_calculator",  # Bounded linear scorer for MCTS
+        "//src/main/cpp/net/eagle0/shardok/ai/score:normalized_ai_score_calculator",  # Normalized [0,1] scorer for ML training
+        "//src/main/cpp/net/eagle0/shardok/ai/score:standard_ai_score_calculator",  # Standard unbounded scorer (default)
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
         "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/cpp/net/eagle0/shardok/library/util:game_state_dumper",
         "@com_google_protobuf//:protobuf",
     ],
 )

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

@@ -10,8 +10,9 @@
 #include <utility>
 
 #include "AIAttackerStrategySelector.hpp"
-#include "AIScoreCalculator.hpp"
+#include "AICommandEvaluator.hpp"
 #include "TranspositionTable.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 
 namespace shardok {
@@ -23,19 +24,21 @@ IterativeDeepeningAI::IterativeDeepeningAI(
         const bool isDefender,
         AIStrategy strategy,
         const CoordsSet& castleCoords,
+        const AIScoreCalculator& scorer,
         const APDCache& apdCache,
-        const ALCache& alCache)
+        BattalionTypeGetter battalionTypeGetter)
     : playerId(playerId),
       isDefender(isDefender),
       strategy(std::move(strategy)),
       castleCoords(castleCoords),
+      scorer(scorer),
       apdCache(apdCache),
-      alCache(alCache) {}
+      battalionTypeGetter(std::move(battalionTypeGetter)) {}  // Move the function object
 
 auto IterativeDeepeningAI::IterativeSearch(
         const GameSettingsSPtr& settings,
         const GameStateW& state,
-        const std::vector<CommandProto>& commands,
+        const CommandListSPtr& commands,
         const AITimeBudget& initialBudget) const -> SearchResult {
     // Make a mutable copy of the time budget to track remaining time
     AITimeBudget timeBudget = initialBudget;
@@ -48,7 +51,7 @@ auto IterativeDeepeningAI::IterativeSearch(
 
     // DEBUG: Clear TT to see if that's causing the suspicious depth reaching
     // g_transpositionTable.clear();  // Uncomment to test without cross-search caching
-    if (commands.empty()) {
+    if (commands->empty()) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
         printf("ID AI: Commands are empty, returning early\n");
 #endif
@@ -67,20 +70,14 @@ auto IterativeDeepeningAI::IterativeSearch(
     const auto& settingsGetter = settings->GetGetter();
     const auto guessedEngine = ShardokEngine(settings, state);
     const auto maxRepeatCount = settingsGetter.Backing().ai_utility_repeat_count();
-    const ScoreValue currentUtility = AIScoreCalculator::GuessedStateScore(
-            isDefender,
-            state,
-            strategy,
-            castleCoords,
-            settingsGetter,
-            apdCache,
-            alCache);
+    const ScoreValue currentUtility =
+            scorer.GuessedStateScore(isDefender, state, strategy, castleCoords);
 
     // Initialize data structures for tracking scores at each depth
     scoresByDepth.clear();
-    scoresByDepth.resize(commands.size());
+    scoresByDepth.resize(commands->size());
     highestDepthCompleted.clear();
-    highestDepthCompleted.resize(commands.size(), 0);
+    highestDepthCompleted.resize(commands->size(), 0);
 
     size_t currentDepth = 1;
     size_t previousBestCommand = 0;  // Track best command from previous depth
@@ -111,7 +108,7 @@ auto IterativeDeepeningAI::IterativeSearch(
 
             auto future = SearchCommandAtDepthWithEngine(
                     guessedEngine,
-                    settingsGetter,
+                    scorer,
                     maxRepeatCount,
                     commands,
                     cmdIndex,
@@ -135,7 +132,8 @@ auto IterativeDeepeningAI::IterativeSearch(
             evaluatedCount++;
 
             // Check if this command is not END_TURN_COMMAND
-            if (commands[cmdIndex].type() != net::eagle0::shardok::common::END_TURN_COMMAND) {
+            if ((*commands)[cmdIndex]->GetCommandType() !=
+                net::eagle0::shardok::common::END_TURN_COMMAND) {
                 allEndTurnCommands = false;
             }
         }
@@ -146,7 +144,7 @@ auto IterativeDeepeningAI::IterativeSearch(
             size_t currentBestCommand = 0;
             ScoreValue currentBestScore = -std::numeric_limits<ScoreValue>::infinity();
 
-            for (size_t i = 0; i < commands.size(); ++i) {
+            for (size_t i = 0; i < commands->size(); ++i) {
                 if (highestDepthCompleted[i] >= currentDepth) {
                     if (scoresByDepth[i][currentDepth] > currentBestScore) {
                         currentBestScore = scoresByDepth[i][currentDepth];
@@ -159,16 +157,20 @@ auto IterativeDeepeningAI::IterativeSearch(
             if (currentDepth > 1 && currentBestCommand != previousBestCommand) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
                 printf("ID AI: Best command changed at depth %lu:\n", currentDepth);
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                printf("  Depth %lu best: command %zu (score %.2f) - type: %s\n",
                        currentDepth - 1,
                        previousBestCommand,
                        scoresByDepth[previousBestCommand][currentDepth - 1],
-                       commands[previousBestCommand].DebugString().c_str());
-                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
+                       net::eagle0::shardok::common::CommandType_Name(
+                               (*commands)[previousBestCommand]->GetCommandType())
+                               .c_str());
+                printf("  Depth %lu best: command %zu (score %.2f) - type: %s\n",
                        currentDepth,
                        currentBestCommand,
                        currentBestScore,
-                       commands[currentBestCommand].DebugString().c_str());
+                       net::eagle0::shardok::common::CommandType_Name(
+                               (*commands)[currentBestCommand]->GetCommandType())
+                               .c_str());
 #endif
             }
 
@@ -247,7 +249,7 @@ auto IterativeDeepeningAI::IterativeSearch(
     result.searchCompleted = result.minimumDepthCompleted;
     result.timeUsed = std::chrono::duration_cast<std::chrono::milliseconds>(
             std::chrono::steady_clock::now() - startTime);
-    result.availableCommandCount = commands.size();
+    result.availableCommandCount = commands->size();
     result.commandCountEvaluated = evaluatedCountAtHighestDepth;
     result.completionReason = completionReason;
 
@@ -270,9 +272,9 @@ bool IterativeDeepeningAI::IsTimeExpired(const AITimeBudget& budget) {
 
 auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
         const ShardokEngine& guessedEngine,
-        const GameSettings::Getter& settingsGetter,
+        const AIScoreCalculator& scorer,
         const int maxRepeatCount,
-        const std::vector<CommandProto>& commands,
+        const CommandListSPtr& commands,
         const size_t commandIndex,
         const int desiredDepth,
         const ScoreValue currentUtility,
@@ -282,65 +284,57 @@ auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
     result.depthAchieved = desiredDepth;
     result.searchCompleted = true;
     result.minimumDepthCompleted = true;
-    result.availableCommandCount = commands.size();
+    result.availableCommandCount = commands->size();
     result.commandCountEvaluated = 1;  // We're evaluating just this command
 
-    if (commandIndex >= commands.size()) {
+    if (commandIndex >= commands->size()) {
         result.bestScore = 0.0;
         std::promise<SearchResult> p;
         p.set_value(result);
         return p.get_future();
     }
 
-    try {
-        // Track concurrent evaluations and adjust time accounting
-        AIEvaluationCounter counter;
-        const auto startTime = std::chrono::steady_clock::now();
+    // Track concurrent evaluations and adjust time accounting
+    AIEvaluationCounter counter;
+    const auto startTime = std::chrono::steady_clock::now();
 
-        // Calculate deadline from remaining time budget
-        const auto deadline = startTime + timeBudget.remainingBudget;
+    // Calculate deadline from remaining time budget
+    const auto deadline = startTime + timeBudget.remainingBudget;
 
-        // Get the future from CommandScore - don't wait yet
-        // Note: CommandScore expects remainingLookahead, not desiredDepth
-        // desiredDepth 1 = evaluate immediate (remainingLookahead 0)
-        // desiredDepth 2 = look 1 move ahead (remainingLookahead 1)
-        // desiredDepth N = look N-1 moves ahead (remainingLookahead N-1)
-        auto commandScoreFuture = AIScoreCalculator::CommandScore(
-                playerId,
-                isDefender,
-                desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
-                maxRepeatCount,
-                guessedEngine,
-                strategy,
-                currentUtility,
-                settingsGetter,
-                castleCoords,
-                apdCache,
-                alCache,
-                commandIndex,
-                deadline);
+    // Create command evaluator for lookahead search
+    AICommandEvaluator evaluator(scorer, apdCache, battalionTypeGetter);
 
-        // Calculate time and adjust budget before waiting
-        // This is needed because we need to update timeBudget synchronously
-        const auto commandScore = commandScoreFuture.get();
+    // Get the future from EvaluateCommand - don't wait yet
+    // Note: EvaluateCommand expects remainingLookahead, not desiredDepth
+    // desiredDepth 1 = evaluate immediate (remainingLookahead 0)
+    // desiredDepth 2 = look 1 move ahead (remainingLookahead 1)
+    // desiredDepth N = look N-1 moves ahead (remainingLookahead N-1)
+    auto commandScoreFuture = evaluator.EvaluateCommand(
+            playerId,
+            isDefender,
+            desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
+            maxRepeatCount,
+            guessedEngine,
+            strategy,
+            currentUtility,
+            castleCoords,
+            commandIndex,
+            deadline);
 
-        const auto elapsed = std::chrono::steady_clock::now() - startTime;
-        const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
-        const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
-        const auto adjustedElapsedMs =
-                std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);
+    // Calculate time and adjust budget before waiting
+    // This is needed because we need to update timeBudget synchronously
+    const auto commandScore = commandScoreFuture.get();
 
-        // Deduct adjusted time from remaining budget
-        timeBudget.remainingBudget -= adjustedElapsedMs;
+    const auto elapsed = std::chrono::steady_clock::now() - startTime;
+    const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
+    const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
+    const auto adjustedElapsedMs =
+            std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);
 
-        result.bestScore = commandScore;
-    } catch (const std::exception& e) {
-        // If evaluation fails, return a neutral score rather than crashing
-#if DEBUG_ITERATIVE_DEEPENING_TIMINGS
-        printf("SearchCommandAtDepthWithEngine: evaluation failed with exception: %s\n", e.what());
-#endif
-        result.bestScore = 0.0;
-    }
+    // Deduct adjusted time from remaining budget
+    timeBudget.remainingBudget -= adjustedElapsedMs;
+
+    result.bestScore = commandScore;
 
     std::promise<SearchResult> p;
     p.set_value(result);

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

@@ -12,17 +12,18 @@
 #include "AIStrategy.hpp"
 #include "AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
 
 namespace shardok {
 
 // Forward declarations
 class ShardokEngine;
 using ScoreValue = double;
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
+using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
 
 /// Reason why AI evaluation completed at the achieved depth.
 enum class EvaluationCompletionReason {
@@ -61,13 +62,14 @@ public:
             bool isDefender,
             AIStrategy strategy,
             const CoordsSet& castleCoords,
+            const AIScoreCalculator& scorer,
             const APDCache& apdCache,
-            const ALCache& alCache);
+            BattalionTypeGetter battalionTypeGetter);  // Pass by value
 
     [[nodiscard]] SearchResult IterativeSearch(
             const GameSettingsSPtr& settings,
             const GameStateW& state,
-            const std::vector<CommandProto>& commands,
+            const CommandListSPtr& commands,
             const AITimeBudget& initialBudget) const;
 
 private:
@@ -75,8 +77,9 @@ private:
     bool isDefender;
     AIStrategy strategy;
     CoordsSet castleCoords;
+    const AIScoreCalculator& scorer;
     const APDCache& apdCache;
-    const ALCache& alCache;
+    BattalionTypeGetter battalionTypeGetter;  // Store by value, not reference!
 
     // Reusable vectors to reduce memory allocations
     mutable std::vector<std::vector<ScoreValue>> scoresByDepth;
@@ -87,9 +90,9 @@ private:
 
     [[nodiscard]] std::future<SearchResult> SearchCommandAtDepthWithEngine(
             const ShardokEngine& guessedEngine,
-            const GameSettings::Getter& settingsGetter,
+            const AIScoreCalculator& scorer,
             int maxRepeatCount,
-            const std::vector<CommandProto>& commands,
+            const CommandListSPtr& commands,
             size_t commandIndex,
             int desiredDepth,
             ScoreValue currentUtility,

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

@@ -10,15 +10,27 @@
 
 #define DEBUG_FLEE_DECISIONS
 
-#include <google/protobuf/util/message_differencer.h>
+// Enable to dump game state and debug tree to /tmp for debugging
+// #define ENABLE_MCTS_DEBUG_DUMP
+
+#ifdef ENABLE_MCTS_DEBUG_DUMP
+#include <chrono>
+#include <fstream>
+#include <iomanip>
+#include <sstream>
+#endif
 
 #include "AIAttackerStrategySelector.hpp"
+#include "AIConfig.hpp"
 #include "AIDefenderStrategySelector.hpp"
 #include "AIFleeDecisionCalculator.hpp"
 #include "AIScoreUtilities.hpp"
 #include "AITimeBudget.hpp"
 #include "IterativeDeepeningAI.hpp"
-#include "src/main/cpp/net/eagle0/common/TimeUtils.hpp"
+#include "mcts/ShardokMCTSAI.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/MCTSOptimizedAIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/NormalizedAIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/StandardAIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/view_filters/GameStateGuesser.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/action_result_view.pb.h"
@@ -42,11 +54,17 @@ ShardokAIClient::ShardokAIClient(
         const PlayerId playerId,
         const bool isDefender,
         const HexMap *hexMap,
-        const SettingsGetter &settings)
+        const SettingsGetter &settings,
+        const AIAlgorithmType aiAlgorithmType,
+        const ScoringCalculatorType scoringCalculatorType,
+        const mcts::MCTSConfig &mctsConfig)
     : playerId(playerId),
       isDefender(isDefender),
+      aiAlgorithmType(aiAlgorithmType),
+      scoringCalculatorType(scoringCalculatorType),
       alCache(std::make_unique<AttackLocationsCache>(hexMap, settings)),
-      waterCrossingCommandChooser(playerId, apdCache) {
+      waterCrossingCommandChooser(playerId, apdCache),
+      mctsConfig(mctsConfig) {
     // Pre-generate the most common cache entries for better performance
     const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);
 
@@ -70,38 +88,110 @@ ShardokAIClient::ShardokAIClient(
     apdCache->ConsolidateThreadLocalCache_Racy();
 }
 
-void CheckCommand(const CommandProto &realDescriptor, const CommandProto &guessedDescriptor) {
-    string diff;
-    auto differencer = google::protobuf::util::MessageDifferencer();
-    differencer.IgnoreField(CommandProto::descriptor()->FindFieldByNumber(
-            CommandProto::kFollowUpCommandTypesFieldNumber));
-    differencer.ReportDifferencesToString(&diff);
-    if (!differencer.Compare(realDescriptor, guessedDescriptor)) {
-        printf("diff: %s\n\n", diff.c_str());
+void CheckCommand(const CommandSPtr &realCommand, const CommandSPtr &guessedCommand) {
+    // Verify that the AI's guessed state produces the same available commands as the real state.
+    // We only compare fields that uniquely identify a command - metadata fields like action_points,
+    // will_unhide, next_round_target_info are not part of command identity.
 
-        printf("Selected command descriptor\n%s\ndoes not match guessed\n%s\n\n",
-               realDescriptor.DebugString().c_str(),
-               guessedDescriptor.DebugString().c_str());
-        throw ShardokInternalErrorException("Illegal state for AI client");
+    if (realCommand->GetCommandType() != guessedCommand->GetCommandType()) {
+        throw ShardokInternalErrorException("Command type mismatch between real and guessed state");
+    }
+
+    if (realCommand->GetPlayerId() != guessedCommand->GetPlayerId()) {
+        throw ShardokInternalErrorException("Player ID mismatch between real and guessed state");
+    }
+
+    if (realCommand->GetActorUnitId() != guessedCommand->GetActorUnitId()) {
+        throw ShardokInternalErrorException("Actor unit mismatch between real and guessed state");
+    }
+
+    if (realCommand->GetTargetRow() != guessedCommand->GetTargetRow() ||
+        realCommand->GetTargetColumn() != guessedCommand->GetTargetColumn()) {
+        throw ShardokInternalErrorException(
+                "Target coordinates mismatch between real and guessed state");
+    }
+
+    // For commands with odds (like FLEE), verify the odds match
+    if (realCommand->HasOdds() != guessedCommand->HasOdds()) {
+        throw ShardokInternalErrorException(
+                "Odds presence mismatch between real and guessed state");
+    }
+
+    if (realCommand->HasOdds() && guessedCommand->HasOdds()) {
+        if (realCommand->GetOddsPercentile() != guessedCommand->GetOddsPercentile()) {
+            throw ShardokInternalErrorException(
+                    "Odds percentile mismatch between real and guessed state");
+        }
     }
 }
 
 auto ShardokAIClient::StandardChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateW &guessedState,
-        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
+        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
     const auto settingsGetter = settings->GetGetter();
     const auto guessedEngine = ShardokEngine(settings, guessedState);
+    const auto guessedCommands = guessedEngine.GetAvailableCommandsForAIPlayer(playerId);
+    const auto commandCount = guessedCommands->size();
 
-    // Calculate time budget based on game situation using new settings
-    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState);
+    // Calculate time budget based on game situation using new dynamic per-command settings
+    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState, commandCount);
 
-    const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
-    const auto commandCount = guessedCommands.size();
+    // Configure MCTS based on proximity to enemy
+    // When far from enemy: use AVERAGING with maxPlayerFlips=0 (single-player lookahead)
+    //   - AVERAGING naturally penalizes longer paths through variance
+    //   - No opponent nodes, so no one-bad-child problem
+    // When close to enemy: use MINIMAX with maxPlayerFlips=1 (adversarial lookahead)
+    //   - MINIMAX correctly models opponent choosing best response
+    //   - Explores through one opponent turn for tactical accuracy
+    auto adjustedMCTSConfig = mctsConfig;
 
-    assert(commandCount == realAvailableCommands.size());
+    // For fair evaluation: simulate leaves to opponent's turn start (maxSimulationFlips=1)
+    // This ensures all leaves are scored at the same game phase:
+    // - Leaves at playerFlips=0 (still my turn): simulate through END_TURN to playerFlips=1
+    // - Leaves at playerFlips=1 (opponent's turn): evaluate immediately
+    // Result: consistent comparison of "what happens after I end my turn"
+    // adjustedMCTSConfig.maxSimulatfixionFlips = 1;
+
+    // adjustedMCTSConfig.maxPlayerFlips = 0;
+    // if (timeBudget.isCloseToEnemy) {
+    //     adjustedMCTSConfig.maxPlayerFlips = 1;
+    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::MINIMAX;
+    //     if constexpr (kPerformanceLogging) {
+    //         printf("MCTS Config: Close to enemy - using maxPlayerFlips=1, MINIMAX backprop\n");
+    //     }
+    // } else {
+    //     adjustedMCTSConfig.maxPlayerFlips = 0;
+    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::AVERAGING;
+    //     if constexpr (kPerformanceLogging) {
+    //         printf("MCTS Config: Far from enemy - using maxPlayerFlips=0, AVERAGING backprop\n");
+    //     }
+    // }
+
+    assert(commandCount == realAvailableCommands->size());
+    // Verify that the AI's guessed state produces the same available commands as reality
     for (size_t i = 0; i < commandCount; i++) {
-        CheckCommand(realAvailableCommands[i], guessedCommands[i]);
+        CheckCommand((*realAvailableCommands)[i], (*guessedCommands)[i]);
+    }
+
+    // Extract values directly from settings for strategy selection
+    const auto maxRounds = settingsGetter.Backing().max_rounds();
+    const auto braveWaterCost = settingsGetter.Backing().brave_water_action_point_cost();
+    const auto battalionTypeGetter = [&settingsGetter](BattalionTypeId typeId) {
+        return settingsGetter.GetBattalionType(typeId);
+    };
+
+    // Create scorer for actual scoring during search - type selected at construction
+    std::unique_ptr<AIScoreCalculator> scorer;
+    switch (scoringCalculatorType) {
+        case ScoringCalculatorType::NORMALIZED:
+            scorer = MakeNormalizedAIScoreCalculator(settingsGetter, apdCache, alCache);
+            break;
+        case ScoringCalculatorType::MCTS_OPTIMIZED:
+            scorer = MakeMCTSOptimizedAIScoreCalculator(settingsGetter, apdCache, alCache);
+            break;
+        case ScoringCalculatorType::STANDARD:
+        default: scorer = MakeStandardAIScoreCalculator(settingsGetter, apdCache, alCache); break;
     }
 
     // Determine strategy once for consistent scoring throughout iterative deepening
@@ -109,23 +199,80 @@ auto ShardokAIClient::StandardChooseCommandIndex(
     const AIStrategy strategy = isDefender ? AIDefenderStrategySelector::BestDefenderStrategy(
                                                      guessedState,
                                                      castleCoords,
+                                                     maxRounds,
                                                      apdCache,
-                                                     settingsGetter)
+                                                     battalionTypeGetter)
                                            : AIAttackerStrategySelector::BestAttackerStrategy(
                                                      playerId,
                                                      guessedState,
                                                      castleCoords,
+                                                     maxRounds,
                                                      apdCache,
                                                      alCache,
-                                                     settingsGetter,
+                                                     battalionTypeGetter,
+                                                     braveWaterCost,
                                                      waterCrossingCommandChooser,
                                                      realAvailableCommands);
 
-    // 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);
+    // AI implementation chosen at runtime via constructor parameter
+    IterativeDeepeningAI::SearchResult search_result;
+
+    if (aiAlgorithmType == AIAlgorithmType::MCTS) {
+#ifdef ENABLE_MCTS_DEBUG_DUMP
+        // Set unique debug dump path for each action using timestamp
+        const auto now = std::chrono::system_clock::now();
+        const auto nowTime = std::chrono::system_clock::to_time_t(now);
+        const auto nowMs =
+                std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()) %
+                1000;
+
+        std::ostringstream pathStream;
+        pathStream << "/tmp/shardok_debug_"
+                   << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
+                   << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
+                   << static_cast<int>(playerId) << ".txt";
+        adjustedMCTSConfig.debugDumpPath = pathStream.str();
+
+        // Also dump the game state to a file for reproduction
+        std::ostringstream statePathStream;
+        statePathStream << "/tmp/shardok_state_"
+                        << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
+                        << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
+                        << static_cast<int>(playerId) << ".bin";
+        const std::string statePath = statePathStream.str();
+
+        // Write the flatbuffer game state to file using SaveTo method
+        if (guessedState.SaveTo(statePath)) {
+            printf("Game state dumped to: %s\n", statePath.c_str());
+        } else {
+            printf("Failed to dump game state to: %s\n", statePath.c_str());
+        }
+#endif  // ENABLE_MCTS_DEBUG_DUMP
+
+        // Using Monte Carlo Tree Search AI (with abstraction layer)
+        ShardokMCTSAI ai(
+                playerId,
+                isDefender,
+                strategy,
+                castleCoords,
+                *scorer,
+                apdCache,
+                alCache,
+                adjustedMCTSConfig);
+        search_result = ai.Search(settings, guessedState, timeBudget);
+    } else {
+        // Using Iterative Deepening AI (default)
+        IterativeDeepeningAI ai(
+                playerId,
+                isDefender,
+                strategy,
+                castleCoords,
+                *scorer,
+                apdCache,
+                battalionTypeGetter);
+        search_result =
+                ai.IterativeSearch(settings, guessedState, realAvailableCommands, timeBudget);
+    }
 
     CommandChoiceResults result{};
     result.chosenIndex = search_result.bestCommandIndex;
@@ -141,9 +288,12 @@ auto ShardokAIClient::StandardChooseCommandIndex(
                    result.commandCountEvaluated,
                    result.availableCommandCount);
         }
-        printf("ID AI: Search complete - achieved depth %d for best command %zu\n",
+        const auto chosenCommandType =
+                (*realAvailableCommands)[result.chosenIndex]->GetCommandType();
+        printf("ID AI: Search complete - achieved depth %d for best command %zu (%s)\n",
                result.depthAchieved,
-               result.chosenIndex);
+               result.chosenIndex,
+               net::eagle0::shardok::common::CommandType_Name(chosenCommandType).c_str());
 
         fflush(stdout);
     }
@@ -154,19 +304,20 @@ auto ShardokAIClient::StandardChooseCommandIndex(
 auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateW &guessedState,
-        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
+        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
     if (const auto dismissCommand = std::ranges::find_if(
-                realAvailableCommands,
-                [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
-                    return cmd.type() == net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
+                *realAvailableCommands,
+                [](const CommandSPtr &cmd) {
+                    return cmd->GetCommandType() ==
+                           net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
                 });
-        dismissCommand == realAvailableCommands.end()) {
+        dismissCommand == realAvailableCommands->end()) {
         return StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
     } else {
         CommandChoiceResults results{};
         results.chosenIndex =
-                static_cast<size_t>(std::distance(realAvailableCommands.begin(), dismissCommand));
-        results.availableCommandCount = realAvailableCommands.size();
+                static_cast<size_t>(std::distance(realAvailableCommands->begin(), dismissCommand));
+        results.availableCommandCount = realAvailableCommands->size();
         results.depthAchieved = 1;          // Simple heuristic choice
         results.commandCountEvaluated = 1;  // Only evaluated one command type
         results.completionReason =
@@ -178,24 +329,31 @@ auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
 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;
+        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+    const auto fleeCommand =
+            std::ranges::find_if(*realAvailableCommands, [](const CommandSPtr &cmd) {
+                return cmd->GetCommandType() == net::eagle0::shardok::common::FLEE_COMMAND;
             });
 
-    if (fleeCommand == realAvailableCommands.end()) {
+    if (fleeCommand == realAvailableCommands->end()) {
         return LateRoundAttackerChooseCommandIndex(settings, guessedState, realAvailableCommands);
     }
 
+    // Extract values directly from settings for flee decision evaluation
+    const auto settingsGetter = settings->GetGetter();
+    const auto maxRounds = settingsGetter.Backing().max_rounds();
+    const auto minimumFleeOddsThreshold = settingsGetter.Backing().ai_minimum_flee_odds_threshold();
+    const auto desperateFleeThreshold = settingsGetter.Backing().ai_desperate_flee_threshold();
+
     // Use the flee decision calculator
     const auto fleeDecision = AIFleeDecisionCalculator::EvaluateFleeVsFight(
             playerId,
-            settings->GetGetter(),
             guessedState,
             realAvailableCommands,
             fleeCommand,
+            maxRounds,
+            minimumFleeOddsThreshold,
+            desperateFleeThreshold,
 #ifdef DEBUG_FLEE_DECISIONS
             true  // Enable debug logging
 #else
@@ -206,7 +364,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
     if (fleeDecision.shouldFlee) {
         CommandChoiceResults results{};
         results.chosenIndex = fleeDecision.commandIndex;
-        results.availableCommandCount = realAvailableCommands.size();
+        results.availableCommandCount = realAvailableCommands->size();
         results.depthAchieved = 1;          // Heuristic choice
         results.commandCountEvaluated = 1;  // Only evaluated one command type
         results.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
@@ -220,7 +378,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
 auto ShardokAIClient::ChooseCommandIndex(
         const GameSettingsSPtr &settings,
         const GameStateView &gsv,
-        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
+        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
     static int typeChosenCount[net::eagle0::shardok::common::CommandType_MAX + 1];
     static int totalChoices = 0;
 
@@ -239,7 +397,7 @@ auto ShardokAIClient::ChooseCommandIndex(
         results = StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
     }
 
-    const auto chosenType = realAvailableCommands[results.chosenIndex].type();
+    const auto chosenType = (*realAvailableCommands)[results.chosenIndex]->GetCommandType();
     typeChosenCount[static_cast<int>(chosenType)]++;
     totalChoices++;
 
@@ -265,8 +423,8 @@ auto ShardokAIClient::ChooseCommandIndex(
 
 auto ShardokAIClient::ChooseCommandIndex(const ShardokEngine &engine) const
         -> CommandChoiceResults {
-    if (const auto &availableCommands = engine.GetAvailableCommandProtos(playerId, false);
-        availableCommands.empty()) {
+    if (const auto &availableCommands = engine.GetAvailableCommandsForAIPlayer(playerId);
+        availableCommands->empty()) {
         printf("no commands for player %d\n", playerId);
         throw ShardokInternalErrorException(
                 "Asked to choose a command, but there are none available");

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

@@ -12,10 +12,13 @@
 #include <vector>
 
 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIConfig.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
 
 namespace shardok {
@@ -38,42 +41,55 @@ class ShardokAIClient {
 private:
     const PlayerId playerId;
     const bool isDefender;
+    const AIAlgorithmType aiAlgorithmType;
+    const ScoringCalculatorType scoringCalculatorType;
 
     APDCache apdCache = std::make_shared<ActionPointDistancesCache>();
     ALCache alCache;
 
     const AIWaterCrossingCommandChooser waterCrossingCommandChooser;
 
+    // MCTS configuration (only used when aiAlgorithmType == MCTS)
+    mcts::MCTSConfig mctsConfig;
+
     [[nodiscard]] auto StandardChooseCommandIndex(
             const GameSettingsSPtr& settings,
             const GameStateW& guessedState,
-            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
+            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
     [[nodiscard]] auto LateRoundAttackerChooseCommandIndex(
             const GameSettingsSPtr& settings,
             const GameStateW& guessedState,
-            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
+            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
     [[nodiscard]] auto FinalRoundAttackerChooseCommandIndex(
             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,
-            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
+            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
 
 public:
     explicit ShardokAIClient(
             PlayerId playerId,
             bool isDefender,
             const HexMap* hexMap,
-            const SettingsGetter& settings);
+            const SettingsGetter& settings,
+            AIAlgorithmType aiAlgorithmType,
+            ScoringCalculatorType scoringCalculatorType,
+            const mcts::MCTSConfig& mctsConfig);
     ~ShardokAIClient() = default;
 
     [[nodiscard]] auto GetPlayerId() const -> PlayerId { return playerId; }
 
     [[nodiscard]] auto ChooseCommandIndex(const ShardokEngine& engine) const
             -> CommandChoiceResults;
+
+    // Overload that works on copies of state - allows caller to release lock during AI thinking
+    [[nodiscard]] auto ChooseCommandIndex(
+            const GameSettingsSPtr& settings,
+            const net::eagle0::shardok::api::GameStateView& gsv,
+            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+
+    // MCTS configuration methods (only relevant when using MCTS algorithm)
+    [[nodiscard]] auto GetMCTSConfig() const -> const mcts::MCTSConfig& { return mctsConfig; }
+    void SetMCTSConfig(const mcts::MCTSConfig& config) { mctsConfig = config; }
 };
 }  // namespace shardok
 

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

@@ -0,0 +1,24 @@
+load("//tools:copts.bzl", "COPTS")
+
+cc_library(
+    name = "shardok_mcts_ai",
+    srcs = ["ShardokMCTSAI.cpp"],
+    hdrs = ["ShardokMCTSAI.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+    ],
+    deps = [
+        "//src/main/cpp/net/eagle0/common/mcts/abstract:abstract_mcts_ai",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_iterative_deepening",  # For SearchResult compatibility
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_time_budget",
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:shardok_mcts_factory",
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
+    ],
+)

src/main/cpp/net/eagle0/shardok/ai/mcts/CHANCE_NODES_DESIGN.md

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

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

@@ -0,0 +1,111 @@
+//
+// Shardok-specific MCTS AI implementation using abstract interfaces
+//
+
+#include "ShardokMCTSAI.hpp"
+
+#include "adapters/ShardokGameEngine.hpp"
+#include "adapters/ShardokGameState.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
+
+namespace shardok {
+
+ShardokMCTSAI::ShardokMCTSAI(
+        PlayerId playerId,
+        bool isDefender,
+        AIStrategy strategy,
+        const CoordsSet& castleCoords,
+        const AIScoreCalculator& scoreCalculator,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        MCTSConfig config)
+    : abstractAI_(std::make_unique<mcts::AbstractMCTSAI>(
+              static_cast<mcts::MCTSPlayerId>(
+                      playerId),  // Use actual player ID for correct scoring
+              config)),
+      isDefender_(isDefender),
+      strategy_(strategy),
+      castleCoords_(castleCoords),
+      scoreCalculator_(scoreCalculator),
+      apdCache_(apdCache),
+      alCache_(alCache) {}
+
+auto ShardokMCTSAI::Search(
+        const GameSettingsSPtr& settings,
+        const GameStateW& state,
+        const AITimeBudget& budget) const -> SearchResult {
+    // Compute critical tiles once to avoid 8.5% runtime overhead in ShardokEngine construction
+    const auto criticalTiles = GetCriticalTileLocations(state->hex_map());
+
+    // Create Shardok engine for simulation
+    ShardokEngine engine(settings, state, criticalTiles, 0, false);
+
+    // Create game state adapter
+    auto gameState = mcts::ShardokMCTSFactory::createGameState(
+            state,
+            &scoreCalculator_,  // Pass the score calculator
+            settings,           // Pass shared_ptr directly
+            isDefender_,
+            strategy_,
+            castleCoords_,
+            apdCache_,
+            alCache_,
+            criticalTiles);
+
+    // Create game engine adapter (passing critical tiles to avoid recomputation)
+    auto gameEngine = mcts::ShardokMCTSFactory::createGameEngine(
+            engine,
+            &scoreCalculator_,  // Pass the score calculator
+            settings,
+            apdCache_,
+            alCache_,
+            isDefender_,
+            strategy_,
+            castleCoords_,
+            criticalTiles);
+
+    // Perform abstract search
+    const auto timeLimit = budget.remainingBudget;
+    const auto abstractResult = abstractAI_->Search(*gameEngine, *gameState, timeLimit);
+
+    // Report cache statistics for performance analysis
+    if (auto* shardokEngine = dynamic_cast<mcts::ShardokGameEngine*>(gameEngine.get())) {
+        shardokEngine->reportCacheStatistics();
+    }
+
+    // Get unfiltered command count for consistent reporting with IterativeDeepeningAI
+    // (MCTS uses filtered commands internally, but we report unfiltered count for metrics)
+    const auto unfilteredCommands = engine.GetAvailableCommandsForAIPlayer(
+            static_cast<PlayerId>(gameState->currentPlayerId()));
+    const size_t unfilteredCount = unfilteredCommands ? unfilteredCommands->size() : 0;
+
+    // Convert result back to Shardok format
+    SearchResult result;
+    // Map filtered index back to original unfiltered index
+    result.bestCommandIndex =
+            gameEngine->mapFilteredIndexToOriginal(abstractResult.bestActionIndex, *gameState);
+    result.bestScore = abstractResult.bestScore;
+    result.depthAchieved = static_cast<size_t>(abstractResult.searchDepth);
+    result.commandCountEvaluated = static_cast<size_t>(abstractResult.nodesEvaluated);
+    result.timeUsed = abstractResult.searchTime;
+    result.availableCommandCount = unfilteredCount;
+    result.minimumDepthCompleted =
+            (abstractResult.searchDepth >= static_cast<int>(budget.minDepthRequired));
+    result.searchCompleted = true;  // MCTS is anytime - always returns a valid result
+
+    // Determine completion reason based on what actually happened
+    if (abstractResult.foundWinningMove || unfilteredCount == 0) {
+        // Found a terminal winning state or no commands available
+        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
+    } else {
+        // Normal case - time budget exhausted while exploring
+        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
+    }
+
+    return result;
+}
+
+}  // namespace shardok

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

@@ -0,0 +1,71 @@
+//
+// Shardok-specific MCTS AI that wraps the abstract implementation
+//
+
+#ifndef EAGLE0_SHARDOK_MCTSAI_HPP
+#define EAGLE0_SHARDOK_MCTSAI_HPP
+
+#include <memory>
+#include <vector>
+
+#include "adapters/ShardokMCTSFactory.hpp"
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/AbstractMCTSAI.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"  // For SearchResult compatibility
+#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
+#pragma clang diagnostic pop
+
+namespace shardok {
+
+// Forward declarations
+class ShardokEngine;
+class AICommandFilter;
+class AIScoreCalculator;
+
+class ShardokMCTSAI {
+public:
+    using SearchResult = IterativeDeepeningAI::SearchResult;
+    using MCTSConfig = mcts::MCTSConfig;
+
+    ShardokMCTSAI(
+            PlayerId playerId,
+            bool isDefender,
+            AIStrategy strategy,
+            const CoordsSet& castleCoords,
+            const AIScoreCalculator& scoreCalculator,
+            const APDCache& apdCache,
+            const ALCache& alCache,
+            MCTSConfig config = MCTSConfig{});
+
+    // Main search interface - compatible with IterativeDeepeningAI
+    [[nodiscard]] auto Search(
+            const GameSettingsSPtr& settings,
+            const GameStateW& state,
+            const AITimeBudget& budget) const -> SearchResult;
+
+    // Configuration
+    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return abstractAI_->GetConfig(); }
+    void SetConfig(const MCTSConfig& newConfig) { abstractAI_->SetConfig(newConfig); }
+
+private:
+    std::unique_ptr<mcts::AbstractMCTSAI> abstractAI_;
+
+    // Shardok-specific context
+    bool isDefender_;
+    AIStrategy strategy_;
+    const CoordsSet& castleCoords_;
+    const AIScoreCalculator& scoreCalculator_;
+    const APDCache& apdCache_;
+    const ALCache& alCache_;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_SHARDOK_MCTSAI_HPP

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

@@ -0,0 +1,82 @@
+load("//tools:copts.bzl", "COPTS")
+
+cc_library(
+    name = "shardok_action",
+    srcs = ["ShardokAction.cpp"],
+    hdrs = ["ShardokAction.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+    ],
+    deps = [
+        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_action",
+        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
+        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
+    ],
+)
+
+cc_library(
+    name = "shardok_game_state",
+    srcs = ["ShardokGameState.cpp"],
+    hdrs = ["ShardokGameState.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+    ],
+    deps = [
+        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_state",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
+        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
+    ],
+)
+
+cc_library(
+    name = "shardok_game_engine",
+    srcs = ["ShardokGameEngine.cpp"],
+    hdrs = ["ShardokGameEngine.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+    ],
+    deps = [
+        ":shardok_action",
+        ":shardok_game_state",
+        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
+        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_engine",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_heuristic_weighting",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
+    ],
+)
+
+cc_library(
+    name = "shardok_mcts_factory",
+    srcs = ["ShardokMCTSFactory.cpp"],
+    hdrs = ["ShardokMCTSFactory.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
+        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
+    ],
+    deps = [
+        ":shardok_action",
+        ":shardok_game_engine",
+        ":shardok_game_state",
+        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
+        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
+    ],
+)

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

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

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

@@ -0,0 +1,61 @@
+//
+// Shardok-specific action adapter for MCTS
+//
+
+#ifndef EAGLE0_SHARDOK_ACTION_HPP
+#define EAGLE0_SHARDOK_ACTION_HPP
+
+#include <memory>
+#include <string>
+
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSAction.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
+#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
+#pragma clang diagnostic pop
+
+namespace shardok::mcts {
+
+class ShardokAction : public MCTSAction {
+public:
+    using CommandType = net::eagle0::shardok::common::CommandType;
+
+    // Constructor: store just the essential fields (no proto, no pointer)
+    ShardokAction(
+            size_t index,
+            CommandType type,
+            PlayerId player,
+            int actorId,
+            int targetRow,
+            int targetCol,
+            bool hasOdds);
+
+    // MCTSAction interface implementation
+    [[nodiscard]] size_t getIndex() const override { return commandIndex_; }
+    [[nodiscard]] std::string getDescription() const override;
+    [[nodiscard]] std::unique_ptr<MCTSAction> clone() const override;
+    [[nodiscard]] bool equals(const MCTSAction& other) const override;
+    [[nodiscard]] bool requiresChanceNode() const override;
+
+    // Shardok-specific accessors (O(1), no allocations)
+    [[nodiscard]] int getType() const { return static_cast<int>(type_); }
+    [[nodiscard]] PlayerId getPlayer() const { return player_; }
+    [[nodiscard]] int getActorId() const { return actorId_; }
+    [[nodiscard]] std::pair<int, int> getTarget() const { return {targetRow_, targetCol_}; }
+
+private:
+    // Store only essential fields (~25 bytes, all POD, cache-friendly)
+    size_t commandIndex_;
+    CommandType type_;
+    PlayerId player_;
+    int actorId_;    // -1 if no actor
+    int targetRow_;  // -1 if no target
+    int targetCol_;  // -1 if no target
+    bool hasOdds_;   // true if command has probabilistic outcome
+};
+
+}  // namespace shardok::mcts
+
+#endif  // EAGLE0_SHARDOK_ACTION_HPP

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

@@ -0,0 +1,628 @@
+//
+// Shardok-specific game engine adapter implementation
+//
+
+#include "ShardokGameEngine.hpp"
+
+#include <algorithm>
+#include <chrono>
+#include <numeric>
+
+#include "ShardokAction.hpp"
+#include "ShardokGameState.hpp"
+#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIHeuristicWeighting.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok::mcts {
+
+// Shared cache for legal actions (uses lock-free parallel hash map for thread safety)
+// Using 8 submaps to reduce contention with 16 MCTS threads
+gtl::parallel_flat_hash_map<
+        uint64_t,
+        ShardokGameEngine::LegalActionsCache,
+        std::hash<uint64_t>,
+        std::equal_to<uint64_t>,
+        std::allocator<std::pair<const uint64_t, ShardokGameEngine::LegalActionsCache>>,
+        8,
+        std::mutex>
+        ShardokGameEngine::legalActionsCache_;
+std::atomic<uint64_t> ShardokGameEngine::cacheHits_{0};
+std::atomic<uint64_t> ShardokGameEngine::cacheMisses_{0};
+std::atomic<uint64_t> ShardokGameEngine::timeInHashComputation_{0};
+std::atomic<uint64_t> ShardokGameEngine::timeInLegalActionsComputation_{0};
+
+ShardokGameEngine::ShardokGameEngine(
+        [[maybe_unused]] const ShardokEngine* engine,
+        const AIScoreCalculator* scoreCalculator,
+        const GameSettingsSPtr& gameSettings,
+        const APDCache* apdCache,
+        const ALCache* alCache,
+        bool isDefender,
+        const AIStrategy& strategy,
+        const CoordsSet& castleCoords,
+        const CoordsSet& criticalTileCoords)
+    : scoreCalculator_(scoreCalculator),
+      gameSettings_(gameSettings),
+      apdCache_(apdCache),
+      alCache_(alCache),
+      isDefender_(isDefender),
+      strategy_(strategy),
+      castleCoords_(castleCoords),
+      criticalTileCoords_(criticalTileCoords) {
+    // Thread-local cache is automatically initialized per thread
+    // Reserve space to reduce rehashing (based on profiling: ~30-50K unique states per search)
+    legalActionsCache_.reserve(100000);
+}
+
+std::unique_ptr<MCTSGameState> ShardokGameEngine::applyAction(
+        const MCTSGameState& state,
+        const MCTSAction& action,
+        double deterministicRoll) const {
+    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
+    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
+
+    if (!shardokState || !shardokAction) { return nullptr; }
+
+    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
+
+    // Use cached engine if available (avoids recomputing GetAvailableCommands for same state)
+    std::shared_ptr<ShardokEngine> engine;
+    if (auto cachedEngine = shardokState->getCachedEngine()) {
+        // Clone the cached engine to preserve command cache
+        engine = std::make_shared<ShardokEngine>(*cachedEngine);
+    } else {
+        // Create fresh engine and populate command cache
+        engine = std::make_shared<ShardokEngine>(
+                gameSettings_,
+                shardokState->getShardokState(),
+                criticalTileCoords_,
+                0,
+                false);
+        // Populate command cache (result intentionally unused, just populating cache)
+        [[maybe_unused]] const auto commands =
+                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+        // Cache the engine for future use with this state
+        shardokState->setCachedEngine(engine);
+        // Clone it for applying the action (don't mutate the cached engine)
+        engine = std::make_shared<ShardokEngine>(*engine);
+    }
+
+    // Create deterministic random generator if a specific roll is requested
+    // deterministicRoll of -1.0 (default) means use random generator
+    // Any other value (including negative) creates a deterministic generator
+    // For open-ended percentile commands, we compute a sequence of values that will
+    // produce the desired final result through the normal open-ended mechanics
+    std::shared_ptr<::RandomGenerator> randomGen = nullptr;
+    constexpr double kNoRollSentinel = -1.0;
+    if (deterministicRoll != kNoRollSentinel) {
+        std::vector<double> sequence;
+
+        if (deterministicRoll >= 5.0 && deterministicRoll <= 95.0) {
+            // Normal range: single value works directly
+            sequence = {deterministicRoll / 100.0};
+        } else if (deterministicRoll < 5.0) {
+            // Need open-ended LOW result (e.g., -100 for guaranteed success)
+            // OpenEndedPercentile: if initial < 5, returns initial - OpenEndedHighImpl(0, 4)
+            // We want: initial - accumulated = deterministicRoll
+            // Use initial = 2 (clearly < 5), so accumulated = 2 - deterministicRoll
+            constexpr double kInitialLow = 2.0;
+            sequence = {kInitialLow / 100.0};
+            // OpenEndedHighImpl accumulates rolls until one < 95
+            // Split accumulated into rolls: 96 (continues) + remaining (stops)
+            double remaining = kInitialLow - deterministicRoll;
+            while (remaining > 95.0) {
+                sequence.push_back(0.96);  // 96 > 95, continues accumulation
+                remaining -= 96.0;
+            }
+            sequence.push_back(remaining / 100.0);  // Final roll < 95, stops
+        } else {
+            // Need open-ended HIGH result (e.g., 150 for guaranteed failure)
+            // OpenEndedPercentile: if initial > 95, returns OpenEndedHighImpl(initial, 4)
+            // OpenEndedHighImpl accumulates rolls until one < 95
+            constexpr double kInitialHigh = 96.0;
+            sequence = {kInitialHigh / 100.0};
+            double remaining = deterministicRoll - kInitialHigh;
+            while (remaining > 95.0) {
+                sequence.push_back(0.96);
+                remaining -= 96.0;
+            }
+            sequence.push_back(remaining / 100.0);
+        }
+
+        randomGen = std::make_shared<::SequenceRandomGenerator>(sequence);
+    }
+
+    engine->PostCommand(currentPlayer, shardokAction->getIndex(), randomGen);
+
+    // Create and return the new state
+    auto newState = std::make_unique<ShardokGameState>(
+            engine->GetCurrentGameState(),
+            scoreCalculator_,
+            gameSettings_.get(),
+            isDefender_,
+            strategy_,
+            castleCoords_,
+            *apdCache_,
+            *alCache_,
+            criticalTileCoords_);
+
+    // Cache the engine on the new state so score() can use it for END_TURN normalization
+    // The engine's command list may be stale after the action was applied, but that's OK -
+    // we'll refresh it when we call GetAvailableCommandsForAIPlayer() in score()
+    newState->setCachedEngine(engine);
+
+    // Don't pre-compute hash - let it be computed lazily on first use
+    // Many states (especially in simulation) never need their hash computed
+    return newState;
+}
+
+void ShardokGameEngine::applyActionMutable(
+        std::unique_ptr<MCTSGameState>& state,
+        const MCTSAction& action) const {
+    auto* shardokState = dynamic_cast<ShardokGameState*>(state.get());
+    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
+
+    if (!shardokState || !shardokAction) {
+        // Fallback to default implementation
+        state = applyAction(*state, action);
+        return;
+    }
+
+    const auto currentPlayer = static_cast<PlayerId>(state->currentPlayerId());
+
+    // Use cached engine if available
+    std::shared_ptr<ShardokEngine> engine;
+    if (auto cachedEngine = shardokState->getCachedEngine()) {
+        engine = std::make_shared<ShardokEngine>(*cachedEngine);
+    } else {
+        engine = std::make_shared<ShardokEngine>(
+                gameSettings_,
+                shardokState->getShardokState(),
+                criticalTileCoords_,
+                0,
+                false);
+        // Populate command cache (result intentionally unused, just populating cache)
+        [[maybe_unused]] const auto commands =
+                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+        shardokState->setCachedEngine(engine);
+        engine = std::make_shared<ShardokEngine>(*engine);
+    }
+
+    engine->PostCommand(currentPlayer, shardokAction->getIndex(), nullptr);
+    shardokState->getMutableShardokState() = engine->GetCurrentGameState();
+    // Clear the cached engine and hash since the state has been mutated
+    shardokState->setCachedEngine(nullptr);
+    shardokState->invalidateHashCache();
+}
+
+std::vector<std::unique_ptr<MCTSAction>> ShardokGameEngine::getLegalActions(
+        const MCTSGameState& state,
+        MCTSPlayerId /*rootPlayerId*/,
+        int currentPlayerFlips,
+        int maxPlayerFlips) const {
+    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
+    if (!shardokState) { return {}; }
+
+    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
+
+    // Check if we've exceeded the maximum allowed player flips
+    // currentPlayerFlips is the number of times the player has changed since root
+    // maxPlayerFlips is the maximum number of changes we allow
+    // If maxPlayerFlips is 0, only explore root player's moves (stop when player first changes)
+    // If maxPlayerFlips is 1, explore through opponent's response (stop after opponent's moves)
+    if (currentPlayerFlips > maxPlayerFlips) {
+        return {};  // Stop exploration - we've exceeded the flip limit
+    }
+
+    // Time hash computation
+    const auto hashStart = std::chrono::high_resolution_clock::now();
+    const uint64_t stateHash = shardokState->hash();
+    const auto hashEnd = std::chrono::high_resolution_clock::now();
+    timeInHashComputation_.fetch_add(
+            std::chrono::duration_cast<std::chrono::microseconds>(hashEnd - hashStart).count(),
+            std::memory_order_relaxed);
+
+    // Check transposition table for cached legal actions
+    if (auto it = legalActionsCache_.find(stateHash); it != legalActionsCache_.end()) {
+        cacheHits_.fetch_add(1, std::memory_order_relaxed);
+
+        // Use cached engine
+        shardokState->setCachedEngine(it->second.engine);
+
+        // Get commands from the cached engine (Engine already caches these internally)
+        const CommandListSPtr commands =
+                it->second.engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+
+        if (!commands || commands->empty()) { return {}; }
+
+        // Convert to MCTSActions using stored filtered indices
+        std::vector<std::unique_ptr<MCTSAction>> actions;
+        actions.reserve(it->second.filteredIndices.size());
+
+        for (const size_t origIdx : it->second.filteredIndices) {
+            if (origIdx < commands->size()) {
+                const auto& cmd = commands->at(origIdx);
+
+                // Extract essential fields directly from command (no proto conversion!)
+                actions.push_back(std::make_unique<ShardokAction>(
+                        origIdx,
+                        cmd->GetCommandType(),
+                        cmd->GetPlayerId(),
+                        cmd->GetActorUnitId(),
+                        cmd->GetTargetRow(),
+                        cmd->GetTargetColumn(),
+                        cmd->HasOdds()));
+            }
+        }
+
+        // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
+        const std::vector<double> weights = getActionWeights(actions, state);
+
+        std::vector<size_t> sortedIndices(actions.size());
+        std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
+
+        std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
+            return weights[a] > weights[b];
+        });
+
+        std::vector<std::unique_ptr<MCTSAction>> sortedActions;
+        sortedActions.reserve(actions.size());
+        for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
+
+        return sortedActions;
+    }
+
+    cacheMisses_.fetch_add(1, std::memory_order_relaxed);
+
+    // Time legal actions computation
+    const auto actionsStart = std::chrono::high_resolution_clock::now();
+
+    // Use cached engine if available, otherwise create and cache it
+    std::shared_ptr<ShardokEngine> engine;
+    if (auto cachedEngine = shardokState->getCachedEngine()) {
+        engine = cachedEngine;
+    } else {
+        engine = std::make_shared<ShardokEngine>(
+                gameSettings_,
+                shardokState->getShardokState(),
+                criticalTileCoords_);
+        shardokState->setCachedEngine(engine);
+    }
+
+    const CommandListSPtr commands = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+
+    if (!commands || commands->empty()) { return {}; }
+
+    // Filter commands using AICommandFilter (matching original MCTSAI behavior)
+    // Use gameSettings for battalion type lookups
+    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
+            commands,
+            currentPlayer,
+            isDefender_,
+            shardokState->getShardokState(),
+            *apdCache_,
+            [this](BattalionTypeId typeId) {
+                return gameSettings_->GetGetter().GetBattalionType(typeId);
+            });
+
+    // Convert only filtered commands to MCTSActions
+    std::vector<std::unique_ptr<MCTSAction>> actions;
+    actions.reserve(filteredIndices.size());
+
+    for (const size_t idx : filteredIndices) {
+        if (idx < commands->size()) {
+            const auto& cmd = commands->at(idx);
+
+            // Extract essential fields directly from command (no proto conversion!)
+            actions.push_back(std::make_unique<ShardokAction>(
+                    idx,
+                    cmd->GetCommandType(),
+                    cmd->GetPlayerId(),
+                    cmd->GetActorUnitId(),
+                    cmd->GetTargetRow(),
+                    cmd->GetTargetColumn(),
+                    cmd->HasOdds()));
+        }
+    }
+
+    // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
+    // This is critical when maxPlayerFlips is low (e.g., 1), as only the first few actions
+    // get explored deeply. Original indices are preserved in ShardokAction::getIndex()
+    const std::vector<double> weights = getActionWeights(actions, state);
+
+    // Create index vector for sorting
+    std::vector<size_t> sortedIndices(actions.size());
+    std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
+
+    // Sort indices by weight (descending)
+    std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
+        return weights[a] > weights[b];
+    });
+
+    // Reorder actions according to sorted indices
+    std::vector<std::unique_ptr<MCTSAction>> sortedActions;
+    sortedActions.reserve(actions.size());
+    for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
+    actions = std::move(sortedActions);
+
+    const auto actionsEnd = std::chrono::high_resolution_clock::now();
+    timeInLegalActionsComputation_.fetch_add(
+            std::chrono::duration_cast<std::chrono::microseconds>(actionsEnd - actionsStart)
+                    .count(),
+            std::memory_order_relaxed);
+
+    // Store in transposition table for future lookups
+    // Note: We only store filtered indices and the engine (which caches commands internally)
+    // This avoids duplicating heavy protocol buffer objects
+    // Use lazy_emplace_l to ensure thread-safe insertion (locks the bucket during construction)
+    legalActionsCache_.lazy_emplace_l(
+            stateHash,
+            [&](typename decltype(legalActionsCache_)::value_type& v) {
+                // Update existing entry
+                v.second.filteredIndices = filteredIndices;
+                v.second.engine = engine;
+            },
+            [&](const typename decltype(legalActionsCache_)::constructor& ctor) {
+                // Create new entry
+                ctor(stateHash, LegalActionsCache{filteredIndices, engine});
+            });
+
+    return actions;
+}
+
+bool ShardokGameEngine::isTerminal(const MCTSGameState& state) const { return state.isTerminal(); }
+
+double ShardokGameEngine::evaluateState(const MCTSGameState& state, MCTSPlayerId playerId) const {
+    return state.score(playerId);
+}
+
+std::vector<size_t> ShardokGameEngine::filterActions(
+        const std::vector<std::unique_ptr<MCTSAction>>& actions,
+        const MCTSGameState& /*state*/) const {
+    // All filtering is already done in getLegalActions() using AICommandFilter
+    // This method is used by simulation policies and doesn't need additional filtering
+    std::vector<size_t> indices;
+    indices.reserve(actions.size());
+    for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
+    return indices;
+}
+
+std::vector<double> ShardokGameEngine::getActionWeights(
+        const std::vector<std::unique_ptr<MCTSAction>>& actions,
+        const MCTSGameState& state) const {
+    // Cast to ShardokGameState to access Shardok-specific methods
+    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
+    if (!shardokState) {
+        throw MCTSInternalError(
+                "ShardokGameEngine::getActionWeights called with non-Shardok state - this "
+                "indicates a type mismatch in the MCTS adapter layer");
+    }
+
+    // Get cached engine and command list for looking up command protos
+    auto cachedEngine = shardokState->getCachedEngine();
+    if (!cachedEngine) {
+        throw MCTSInternalError(
+                "ShardokGameEngine::getActionWeights called with state that has no cached engine");
+    }
+
+    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
+    const CommandListSPtr commands = cachedEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
+
+    // Determine if current player is defender (not root player!)
+    // During simulation we need to use the correct perspective for action weighting
+    bool currentPlayerIsDefender = false;
+    const auto& gameState = shardokState->getShardokState();
+    for (const auto* pi : *gameState->player_infos()) {
+        if (pi->player_id() == currentPlayer) {
+            currentPlayerIsDefender = pi->is_defender();
+            break;
+        }
+    }
+
+    // Use AIHeuristicWeighting for fast O(1) context-aware command weighting
+    std::vector<double> weights;
+    weights.reserve(actions.size());
+
+    for (const auto& action : actions) {
+        const auto* shardokAction = dynamic_cast<const ShardokAction*>(action.get());
+        if (!shardokAction) {
+            throw MCTSInternalError(
+                    "ShardokGameEngine::getActionWeights encountered non-Shardok action - this "
+                    "indicates a type mismatch in the MCTS adapter layer");
+        }
+
+        // Look up command proto from cached engine using action's index
+        const size_t cmdIndex = shardokAction->getIndex();
+        if (cmdIndex >= commands->size()) {
+            throw MCTSInternalError(
+                    "ShardokGameEngine::getActionWeights: action index out of bounds");
+        }
+
+        const auto& cmd = commands->at(cmdIndex);
+
+        weights.push_back(AIHeuristicWeighting::GetCommandWeight(
+                cmd->GetCommandType(),
+                cmd->GetActorUnitId(),
+                cmd->GetPlayerId(),
+                Coords{cmd->GetTargetRow(), cmd->GetTargetColumn()},
+                gameState,
+                castleCoords_,
+                apdCache_,
+                currentPlayerIsDefender,  // Use current player's role, not root player's!
+                [this](BattalionTypeId typeId) {
+                    return gameSettings_->GetGetter().GetBattalionType(typeId);
+                }));
+    }
+
+    return weights;
+}
+
+double ShardokGameEngine::getActionScore(
+        const MCTSGameState& state,
+        const MCTSAction& action,
+        MCTSPlayerId playerId) const {
+    auto newState = applyAction(state, action);
+    if (!newState) { return 0.0; }
+
+    return newState->score(playerId);
+}
+
+bool ShardokGameEngine::shouldStopSearch(
+        const MCTSGameState& /*state*/,
+        int /*iterations*/,
+        std::chrono::steady_clock::time_point /*startTime*/) const {
+    // Could add early termination logic here
+    return false;
+}
+
+size_t ShardokGameEngine::mapFilteredIndexToOriginal(
+        size_t filteredIndex,
+        const MCTSGameState& state) const {
+    // Get the filtered actions (uses cached engine)
+    auto actions = getLegalActions(state, state.currentPlayerId(), 0, 0);
+
+    // Check bounds
+    if (filteredIndex >= actions.size()) { return filteredIndex; }
+
+    // Extract the original index from the ShardokAction
+    const auto* shardokAction = dynamic_cast<const ShardokAction*>(actions[filteredIndex].get());
+    if (!shardokAction) { return filteredIndex; }
+
+    // ShardokAction stores the original unfiltered index
+    return shardokAction->getIndex();
+}
+
+void ShardokGameEngine::reportCacheStatistics() const {
+    const uint64_t hits = cacheHits_.load(std::memory_order_relaxed);
+    const uint64_t misses = cacheMisses_.load(std::memory_order_relaxed);
+    const uint64_t hashTime = timeInHashComputation_.load(std::memory_order_relaxed);
+    const uint64_t actionsTime = timeInLegalActionsComputation_.load(std::memory_order_relaxed);
+    const uint64_t totalLookups = hits + misses;
+
+    if (totalLookups > 0) {
+        const double hitRate = static_cast<double>(hits) / static_cast<double>(totalLookups);
+        const double avgHashTimeUs =
+                static_cast<double>(hashTime) / static_cast<double>(totalLookups);
+        const double avgActionsTimeUs =
+                misses > 0 ? static_cast<double>(actionsTime) / static_cast<double>(misses) : 0.0;
+
+        printf("Legal Actions Cache Stats:\n");
+        printf("  Lookups: %llu hits, %llu misses, %.1f%% hit rate, %zu entries\n",
+               static_cast<unsigned long long>(hits),
+               static_cast<unsigned long long>(misses),
+               hitRate * 100.0,
+               legalActionsCache_.size());
+        printf("  Timing: %.2f us avg hash, %.2f us avg actions (on miss)\n",
+               avgHashTimeUs,
+               avgActionsTimeUs);
+        printf("  Total time: %.2f ms in hash, %.2f ms in actions\n",
+               hashTime / 1000.0,
+               actionsTime / 1000.0);
+
+        // Calculate if transposition table is worth it
+        const double timeWithCache = hashTime + actionsTime;
+        const double timeWithoutCache =
+                avgActionsTimeUs * static_cast<double>(totalLookups);  // All lookups recompute
+        const double savings = (timeWithoutCache - timeWithCache) / timeWithoutCache * 100.0;
+        printf("  Cache savings: %.1f%% vs. no cache (%.2f ms saved)\n",
+               savings,
+               (timeWithoutCache - timeWithCache) / 1000.0);
+    }
+}
+
+void ShardokGameEngine::resetCacheStatistics() {
+    cacheHits_.store(0, std::memory_order_relaxed);
+    cacheMisses_.store(0, std::memory_order_relaxed);
+    timeInHashComputation_.store(0, std::memory_order_relaxed);
+    timeInLegalActionsComputation_.store(0, std::memory_order_relaxed);
+}
+
+ChanceOutcomeInfo ShardokGameEngine::getBinaryOutcomeInfo(
+        const MCTSGameState& state,
+        const MCTSAction& action) const {
+    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
+    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
+
+    if (!shardokState || !shardokAction) {
+        throw ShardokInternalErrorException("Invalid state or action type in getBinaryOutcomeInfo");
+    }
+
+    // Check for multi-outcome commands (roll affects outcome quality, not just success/failure)
+    // These use multiOutcome() with fixed seeds to sample the range of possible results
+    using namespace net::eagle0::shardok::common;
+    const auto commandType = static_cast<CommandType>(shardokAction->getType());
+
+    switch (commandType) {
+        case END_TURN_COMMAND:
+            // END_TURN has random effects (fire spread, weather changes)
+            return ChanceOutcomeInfo::multiOutcome(5);
+
+        case MELEE_COMMAND:
+        case ARCHERY_COMMAND:
+        case CHARGE_COMMAND:
+        case REDUCE_COMMAND:
+            // Combat/siege commands: OpenEndedPercentile roll affects damage dealt
+            // Use 5 outcomes to sample the roll distribution
+            return ChanceOutcomeInfo::multiOutcome(5);
+
+        case CHALLENGE_DUEL_COMMAND:
+            // Duels have multiple combat rounds with rolls, so outcomes vary significantly
+            return ChanceOutcomeInfo::multiOutcome(5);
+
+        default:
+            // Continue to binary outcome handling below
+            break;
+    }
+
+    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
+
+    // Get or create the engine for this state
+    std::shared_ptr<ShardokEngine> engine;
+    if (auto cachedEngine = shardokState->getCachedEngine()) {
+        engine = cachedEngine;
+    } else {
+        engine = std::make_shared<ShardokEngine>(
+                gameSettings_,
+                shardokState->getShardokState(),
+                criticalTileCoords_,
+                0,
+                false);
+        // Populate command cache
+        [[maybe_unused]] const auto commands =
+                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+        shardokState->setCachedEngine(engine);
+    }
+
+    // Get command descriptors
+    const auto descriptors = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
+    const size_t actionIndex = shardokAction->getIndex();
+
+    if (actionIndex >= descriptors->size()) {
+        throw ShardokInternalErrorException("Action index out of range in getBinaryOutcomeInfo");
+    }
+
+    const auto& descriptor = descriptors->at(actionIndex);
+
+    // Get success probability for binary outcome actions
+    if (!descriptor->HasOdds()) {
+        throw ShardokInternalErrorException("Action does not have odds in getBinaryOutcomeInfo");
+    }
+
+    const auto successChancePercentile = descriptor->GetOddsPercentile();
+    const double successProbability = static_cast<double>(successChancePercentile) / 100.0;
+
+    return ChanceOutcomeInfo::binary(successProbability);
+}
+
+void ShardokGameEngine::clearLegalActionsCache() { legalActionsCache_.clear(); }
+
+// Extern-linkage function for testing
+void clearLegalActionsCache_ForTesting() { ShardokGameEngine::clearLegalActionsCache(); }
+
+}  // namespace shardok::mcts

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

@@ -0,0 +1,144 @@
+//
+// Shardok-specific game engine adapter for MCTS
+//
+
+#ifndef EAGLE0_SHARDOK_GAME_ENGINE_HPP
+#define EAGLE0_SHARDOK_GAME_ENGINE_HPP
+
+#include <atomic>
+#include <functional>
+#include <gtl/phmap.hpp>
+#include <memory>
+#include <vector>
+
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok {
+
+// Forward declarations
+class AICommandFilter;
+class AIScoreCalculator;
+class RandomGenerator;
+
+// Use existing type definitions from the Shardok codebase
+// GameSettingsSPtr and SettingsGetter are defined in GameSettings.hpp
+
+namespace mcts {
+
+class ShardokGameEngine : public MCTSGameEngine {
+public:
+    ShardokGameEngine(
+            const ShardokEngine* engine,
+            const AIScoreCalculator* scoreCalculator,
+            const GameSettingsSPtr& gameSettings,
+            const APDCache* apdCache,
+            const ALCache* alCache,
+            bool isDefender,
+            const AIStrategy& strategy,
+            const CoordsSet& castleCoords,
+            const CoordsSet& criticalTileCoords);
+
+    // MCTSGameEngine interface implementation
+    [[nodiscard]] std::unique_ptr<MCTSGameState> applyAction(
+            const MCTSGameState& state,
+            const MCTSAction& action,
+            double deterministicRoll = -1.0) const override;
+
+    void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
+            const override;
+
+    [[nodiscard]] std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
+            const MCTSGameState& state,
+            MCTSPlayerId rootPlayerId,
+            int currentPlayerFlips,
+            int maxPlayerFlips) const override;
+
+    [[nodiscard]] bool isTerminal(const MCTSGameState& state) const override;
+
+    [[nodiscard]] double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
+            const override;
+
+    [[nodiscard]] std::vector<size_t> filterActions(
+            const std::vector<std::unique_ptr<MCTSAction>>& actions,
+            const MCTSGameState& state) const override;
+
+    [[nodiscard]] std::vector<double> getActionWeights(
+            const std::vector<std::unique_ptr<MCTSAction>>& actions,
+            const MCTSGameState& state) const override;
+
+    [[nodiscard]] double getActionScore(
+            const MCTSGameState& state,
+            const MCTSAction& action,
+            MCTSPlayerId playerId) const override;
+
+    [[nodiscard]] bool shouldStopSearch(
+            const MCTSGameState& state,
+            int iterations,
+            std::chrono::steady_clock::time_point startTime) const override;
+
+    [[nodiscard]] size_t mapFilteredIndexToOriginal(
+            size_t filteredIndex,
+            const MCTSGameState& state) const override;
+
+    [[nodiscard]] BinaryOutcomeInfo getBinaryOutcomeInfo(
+            const MCTSGameState& state,
+            const MCTSAction& action) const override;
+
+    // Report transposition table statistics
+    void reportCacheStatistics() const;
+
+    // Reset cache statistics
+    void resetCacheStatistics();
+
+private:
+    // Transposition table entry for caching legal actions
+    // Note: We don't store command protos since the Engine already caches them
+    struct LegalActionsCache {
+        std::vector<size_t> filteredIndices;
+        std::shared_ptr<ShardokEngine> engine;  // Engine with populated command cache
+    };
+
+    const AIScoreCalculator* scoreCalculator_;
+    const GameSettingsSPtr gameSettings_;
+    const APDCache* apdCache_;
+    const ALCache* alCache_;
+    bool isDefender_;
+    AIStrategy strategy_;
+    const CoordsSet castleCoords_;  // Own the data to avoid dangling references
+    // Computed once to avoid 8.5% overhead per engine construction
+    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
+
+    // Transposition table for legal actions (shared across threads with lock-free hash map)
+    // parallel_flat_hash_map provides thread-safe concurrent access without explicit locking
+    // Using 8 submaps (N=8) to reduce contention with default 16 MCTS threads
+    static gtl::parallel_flat_hash_map<
+            uint64_t,
+            LegalActionsCache,
+            std::hash<uint64_t>,
+            std::equal_to<uint64_t>,
+            std::allocator<std::pair<const uint64_t, LegalActionsCache>>,
+            8,
+            std::mutex>
+            legalActionsCache_;
+    static std::atomic<uint64_t> cacheHits_;
+    static std::atomic<uint64_t> cacheMisses_;
+
+    // Performance timing (in microseconds)
+    static std::atomic<uint64_t> timeInHashComputation_;
+    static std::atomic<uint64_t> timeInLegalActionsComputation_;
+
+public:
+    // Clear the static legal actions cache (useful for tests)
+    static void clearLegalActionsCache();
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_SHARDOK_GAME_ENGINE_HPP

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

@@ -0,0 +1,125 @@
+//
+// Shardok-specific game state adapter implementation
+//
+
+#include "ShardokGameState.hpp"
+
+#include <sstream>
+#include <string>
+#include <utility>
+
+#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok::mcts {
+
+ShardokGameState::ShardokGameState(
+        GameStateW state,
+        const AIScoreCalculator* calculator,
+        const GameSettings* settings,
+        const bool isDefender,
+        AIStrategy strategy,
+        const CoordsSet& castleCoords,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const CoordsSet& criticalTileCoords)
+    : state_(std::move(state)),
+      scoreCalculator_(calculator),
+      settings_(settings),
+      isDefender_(isDefender),
+      strategy_(std::move(strategy)),
+      castleCoords_(castleCoords),
+      apdCache_(apdCache),
+      alCache_(alCache),
+      criticalTileCoords_(criticalTileCoords) {}
+
+uint64_t ShardokGameState::hash() const {
+    if (!hashCached_) {
+        cachedHash_ = state_.ComputeFNV1aHash();
+        hashCached_ = true;
+    }
+    return cachedHash_;
+}
+
+double ShardokGameState::score(MCTSPlayerId playerId) const {
+    // Honor the interface contract: score() should return evaluation from playerId's perspective.
+    // Map the requested playerId to defender/attacker role to determine scoring perspective.
+
+    // Look up which player ID is the defender from game state
+    bool foundDefender = false;
+    bool requestedPlayerIsDefender = false;
+
+    if (state_->player_infos()) {
+        for (const auto* pi : *state_->player_infos()) {
+            if (pi && pi->is_defender()) {
+                foundDefender = true;
+                requestedPlayerIsDefender = (static_cast<PlayerId>(playerId) == pi->player_id());
+                break;
+            }
+        }
+    }
+
+    // Fallback: if we can't determine from game state, use isDefender_ which represents
+    // the root player's role (and playerId is always the root player in practice)
+    const bool scoreFromDefenderPerspective =
+            foundDefender ? requestedPlayerIsDefender : isDefender_;
+
+    // Score the current state directly
+    return scoreCalculator_
+            ->GuessedStateScore(scoreFromDefenderPerspective, state_, strategy_, castleCoords_);
+}
+
+MCTSPlayerId ShardokGameState::currentPlayerId() const { return state_->current_player(); }
+
+bool ShardokGameState::isTerminal() const {
+    // Check if game status indicates the game is over
+    if (state_->status()) {
+        const auto gameStatus = state_->status()->state();
+        if (gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_VICTORY ||
+            gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_DRAW) {
+            return true;
+        }
+    }
+
+    // Check max rounds
+    if (state_->current_round() >= settings_->GetGetter().Backing().max_rounds()) { return true; }
+
+    return false;
+}
+
+std::unique_ptr<MCTSGameState> ShardokGameState::clone() const {
+    auto cloned = std::make_unique<ShardokGameState>(
+            state_,
+            scoreCalculator_,
+            settings_,
+            isDefender_,
+            strategy_,
+            castleCoords_,
+            apdCache_,
+            alCache_,
+            criticalTileCoords_);
+    // Don't copy the cached engine - each state needs its own
+    return cloned;
+}
+
+bool ShardokGameState::equals(const MCTSGameState& other) const {
+    const auto* shardokOther = dynamic_cast<const ShardokGameState*>(&other);
+    if (!shardokOther) { return false; }
+
+    return hash() == shardokOther->hash();
+}
+
+MCTSPlayerId ShardokGameState::getWinner() const {
+    // Note: FlatBuffer doesn't have a winner field
+    // In practice, this would need to determine winner from victory conditions
+    return -1;  // No winner
+}
+
+std::string ShardokGameState::toString() const {
+    std::stringstream ss;
+    ss << "ShardokGameState[Round:" << static_cast<int>(state_->current_round())
+       << " Player:" << currentPlayerId() << " Hash:" << hash() << "]";
+    return ss.str();
+}
+
+}  // namespace shardok::mcts

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

@@ -0,0 +1,83 @@
+//
+// Shardok-specific game state adapter for MCTS
+//
+
+#ifndef EAGLE0_SHARDOK_GAME_STATE_HPP
+#define EAGLE0_SHARDOK_GAME_STATE_HPP
+
+#include <memory>
+
+#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameState.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok {
+
+// Forward declarations
+class AIScoreCalculator;
+
+namespace mcts {
+
+class ShardokGameState : public MCTSGameState {
+public:
+    ShardokGameState(
+            GameStateW state,
+            const AIScoreCalculator* calculator,
+            const GameSettings* settings,
+            bool isDefender,
+            AIStrategy strategy,
+            const CoordsSet& castleCoords,
+            const APDCache& apdCache,
+            const ALCache& alCache,
+            const CoordsSet& criticalTileCoords);
+
+    // MCTSGameState interface implementation
+    [[nodiscard]] uint64_t hash() const override;
+    [[nodiscard]] double score(MCTSPlayerId playerId) const override;
+    [[nodiscard]] MCTSPlayerId currentPlayerId() const override;
+    [[nodiscard]] bool isTerminal() const override;
+    [[nodiscard]] std::unique_ptr<MCTSGameState> clone() const override;
+    [[nodiscard]] bool equals(const MCTSGameState& other) const override;
+    [[nodiscard]] MCTSPlayerId getWinner() const override;
+    [[nodiscard]] std::string toString() const override;
+
+    // Shardok-specific accessors
+    [[nodiscard]] const GameStateW& getShardokState() const { return state_; }
+    [[nodiscard]] GameStateW& getMutableShardokState() { return state_; }
+    [[nodiscard]] bool isDefender() const { return isDefender_; }
+    [[nodiscard]] const GameSettings* getSettings() const { return settings_; }
+    [[nodiscard]] const CoordsSet& getCriticalTileCoords() const { return criticalTileCoords_; }
+
+    // Engine caching for performance (avoids recomputing available commands)
+    void setCachedEngine(std::shared_ptr<ShardokEngine> engine) const { cachedEngine_ = engine; }
+    [[nodiscard]] std::shared_ptr<ShardokEngine> getCachedEngine() const { return cachedEngine_; }
+
+    // Invalidate hash cache when state is mutated
+    void invalidateHashCache() const {
+        hashCached_ = false;
+        cachedHash_ = 0;
+    }
+
+private:
+    GameStateW state_;
+    const AIScoreCalculator* scoreCalculator_;
+    const GameSettings* settings_;
+    bool isDefender_;
+    AIStrategy strategy_;
+    const CoordsSet castleCoords_;  // Own the data to avoid dangling references
+    const APDCache& apdCache_;
+    const ALCache& alCache_;
+    mutable uint64_t cachedHash_ = 0;
+    mutable bool hashCached_ = false;
+    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
+    mutable std::shared_ptr<ShardokEngine> cachedEngine_;  // Engine with cached available commands
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_SHARDOK_GAME_STATE_HPP

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

@@ -0,0 +1,82 @@
+//
+// Factory implementation for creating Shardok-specific MCTS components
+//
+
+#include "ShardokMCTSFactory.hpp"
+
+#include "ShardokAction.hpp"
+#include "ShardokGameEngine.hpp"
+#include "ShardokGameState.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok::mcts {
+
+std::unique_ptr<MCTSGameEngine> ShardokMCTSFactory::createGameEngine(
+        const ShardokEngine& engine,
+        const AIScoreCalculator* scoreCalculator,
+        const GameSettingsSPtr& gameSettings,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        bool isDefender,
+        const AIStrategy& strategy,
+        const CoordsSet& castleCoords,
+        const CoordsSet& criticalTileCoords) {
+    return std::make_unique<ShardokGameEngine>(
+            &engine,
+            scoreCalculator,
+            gameSettings,
+            &apdCache,
+            &alCache,
+            isDefender,
+            strategy,
+            castleCoords,
+            criticalTileCoords);
+}
+
+std::unique_ptr<MCTSGameState> ShardokMCTSFactory::createGameState(
+        const GameStateW& state,
+        const AIScoreCalculator* scoreCalculator,
+        const GameSettingsSPtr& settings,
+        bool isDefender,
+        const AIStrategy& strategy,
+        const CoordsSet& castleCoords,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const CoordsSet& criticalTileCoords) {
+    return std::make_unique<ShardokGameState>(
+            state,
+            scoreCalculator,
+            settings.get(),  // Get raw pointer from shared_ptr
+            isDefender,
+            strategy,
+            castleCoords,
+            apdCache,
+            alCache,
+            criticalTileCoords);
+}
+
+std::vector<std::unique_ptr<MCTSAction>> ShardokMCTSFactory::createActionsFromCommandList(
+        const CommandListSPtr& commands) {
+    std::vector<std::unique_ptr<MCTSAction>> actions;
+    if (!commands) { return actions; }
+
+    actions.reserve(commands->size());
+    for (size_t i = 0; i < commands->size(); ++i) {
+        const auto& cmd = (*commands)[i];
+
+        // Extract essential fields directly from command (no proto conversion!)
+        actions.push_back(std::make_unique<ShardokAction>(
+                i,
+                cmd->GetCommandType(),
+                cmd->GetPlayerId(),
+                cmd->GetActorUnitId(),
+                cmd->GetTargetRow(),
+                cmd->GetTargetColumn(),
+                cmd->HasOdds()));
+    }
+
+    return actions;
+}
+
+}  // namespace shardok::mcts

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

@@ -0,0 +1,70 @@
+//
+// Factory for creating Shardok-specific MCTS components
+//
+
+#ifndef EAGLE0_SHARDOK_MCTS_FACTORY_HPP
+#define EAGLE0_SHARDOK_MCTS_FACTORY_HPP
+
+#include <functional>
+#include <memory>
+#include <vector>
+
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+
+namespace shardok {
+
+// Forward declarations
+class ShardokEngine;
+class AICommandFilter;
+class AIScoreCalculator;
+class GameStateW;
+class GameSettings;
+
+namespace mcts {
+
+// Forward declarations
+class MCTSGameEngine;
+class MCTSGameState;
+class MCTSAction;
+
+class ShardokMCTSFactory {
+public:
+    // Create a Shardok game engine adapter
+    [[nodiscard]] static std::unique_ptr<MCTSGameEngine> createGameEngine(
+            const ShardokEngine& engine,
+            const AIScoreCalculator* scoreCalculator,
+            const GameSettingsSPtr& gameSettings,
+            const APDCache& apdCache,
+            const ALCache& alCache,
+            bool isDefender,
+            const AIStrategy& strategy,
+            const CoordsSet& castleCoords,
+            const CoordsSet& criticalTileCoords);
+
+    // Create a Shardok game state adapter
+    [[nodiscard]] static std::unique_ptr<MCTSGameState> createGameState(
+            const GameStateW& state,
+            const AIScoreCalculator* scoreCalculator,
+            const GameSettingsSPtr& settings,
+            bool isDefender,
+            const AIStrategy& strategy,
+            const CoordsSet& castleCoords,
+            const APDCache& apdCache,
+            const ALCache& alCache,
+            const CoordsSet& criticalTileCoords);
+
+    // Convert from command list to MCTS actions
+    [[nodiscard]] static std::vector<std::unique_ptr<MCTSAction>> createActionsFromCommandList(
+            const CommandListSPtr& commands);
+};
+
+}  // namespace mcts
+}  // namespace shardok
+
+#endif  // EAGLE0_SHARDOK_MCTS_FACTORY_HPP

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

@@ -0,0 +1,56 @@
+//
+// Created by dancrosby on 3/4/20.
+//
+
+#ifndef EAGLE0_AISCORECALCULATOR_HPP
+#define EAGLE0_AISCORECALCULATOR_HPP
+
+#include <future>
+
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+
+namespace shardok {
+
+using shardok::PlayerId;
+using std::future;
+using std::vector;
+
+using ScoreValue = double;
+
+// Forward declarations
+class ShardokEngine;
+struct AIStrategy;
+
+/// Abstract base class for AI scoring algorithms.
+/// Allows testing different scoring strategies by implementing different scorers.
+class AIScoreCalculator {
+public:
+    virtual ~AIScoreCalculator() = default;
+
+    // Rule of five: explicitly default or delete copy/move operations
+    AIScoreCalculator(const AIScoreCalculator &) = default;
+    AIScoreCalculator &operator=(const AIScoreCalculator &) = default;
+    AIScoreCalculator(AIScoreCalculator &&) = default;
+    AIScoreCalculator &operator=(AIScoreCalculator &&) = default;
+
+protected:
+    AIScoreCalculator() = default;
+
+public:
+    /// Evaluate the score of a guessed game state based on the current AI strategy.
+    /// DOES NOT perform lookahead - this is pure state evaluation.
+    /// For lookahead search, use AICommandEvaluator which depends on this interface.
+    [[nodiscard]] virtual auto GuessedStateScore(
+            bool isDefender,
+            const GameStateW &state,
+            const AIStrategy &aiStrategy,
+            const CoordsSet &allCastleCoords) const -> ScoreValue = 0;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AISCORECALCULATOR_HPP

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

@@ -7,9 +7,9 @@
 #include <algorithm>
 #include <ranges>
 
-#include "AIAttackLocations.hpp"
-#include "AIDistanceDebuf.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIDistanceDebuf.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/victory_condition.hpp"
 
@@ -43,8 +43,8 @@ auto AttackerDebufForOnFireCriticalTile(
         const vector<const Unit*>& extinguishingUnits,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings,
-        const int braveWaterActionPointCost,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         const bool lateGame) -> double {
     double minDebuf = 99999.9;
 
@@ -60,8 +60,8 @@ auto AttackerDebufForOnFireCriticalTile(
                 extinguishingUnits,
                 apdCache,
                 alCache,
-                settings,
-                braveWaterActionPointCost,
+                battalionTypeGetter,
+                braveWaterCost,
                 lateGame,
                 /* includeUndead = */ false);
         if (newDebuf < minDebuf) minDebuf = newDebuf;
@@ -77,8 +77,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
         const vector<const Unit*>& claimableUnits,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings,
-        const int braveWaterActionPointCost,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         const bool lateGame) -> double {
     return UNHELD_VALUE * DefenderDistanceBuf(
                                   criticalTileLocation,
@@ -87,8 +87,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
                                   claimableUnits,
                                   apdCache,
                                   alCache,
-                                  settings,
-                                  braveWaterActionPointCost,
+                                  battalionTypeGetter,
+                                  braveWaterCost,
                                   lateGame,
                                   /* includeUndead = */ false);
 }
@@ -100,8 +100,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
         const vector<const Unit*>& attackerUnits,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings,
-        const int braveWaterActionPointCost,
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost,
         const bool lateGame) {
     const double baseUnitValue =
             defenderUnit->battalion().size() +
@@ -117,8 +117,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
                    attackerUnits,
                    apdCache,
                    alCache,
-                   settings,
-                   braveWaterActionPointCost,
+                   battalionTypeGetter,
+                   braveWaterCost,
                    lateGame,
                    /* includeUndead = */ false);
 }
@@ -126,10 +126,7 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
 auto DefenderHoldsCriticalTilesVictoryScore(
         const GameStateW& gameState,
         const CoordsSet& criticalTileLocations,
-        const PlayerInfo* player,
-        const APDCache& /*apdCache*/,
-        const ALCache& /*alCache*/,
-        const SettingsGetter& /*settings*/) -> ScoreValue {
+        const PlayerInfo* player) -> ScoreValue {
     ScoreValue total = 0.0;
 
     const auto rc = gameState->hex_map()->row_count();
@@ -159,7 +156,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
         const PlayerInfo* player,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings) -> ScoreValue {
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> ScoreValue {
     vector<const Unit*> playerUnits{};
     vector<const Unit*> claimablePlayerUnits{};
     for (const Unit* unit : *gameState->units()) {
@@ -175,7 +173,6 @@ auto AttackerHoldsCriticalTilesVictoryScore(
         return criticalTileLocations.size() * MAX_DEFENDER_HELD_VALUE;
     }
 
-    const int braveWaterActionPointCost = settings.Backing().brave_water_action_point_cost();
     const MapId mapId = apdCache->GetMapId(gameState->hex_map());
 
     ScoreValue total = 0.0;
@@ -202,8 +199,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                             claimablePlayerUnits,
                             apdCache,
                             alCache,
-                            settings,
-                            braveWaterActionPointCost,
+                            battalionTypeGetter,
+                            braveWaterCost,
                             IsLateGame(gameState));
                     total += BADLY_HELD_VALUE;
                 }
@@ -215,8 +212,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                         playerUnits,
                         apdCache,
                         alCache,
-                        settings,
-                        braveWaterActionPointCost,
+                        battalionTypeGetter,
+                        braveWaterCost,
                         IsLateGame(gameState));
             }
         } else if (terrain->modifier().fire().present()) {
@@ -227,8 +224,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                     claimablePlayerUnits,
                     apdCache,
                     alCache,
-                    settings,
-                    braveWaterActionPointCost,
+                    battalionTypeGetter,
+                    braveWaterCost,
                     IsLateGame(gameState));
         } else {
             total -= AttackerDebufForUnoccupiedCriticalTile(
@@ -238,8 +235,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                     claimablePlayerUnits,
                     apdCache,
                     alCache,
-                    settings,
-                    braveWaterActionPointCost,
+                    battalionTypeGetter,
+                    braveWaterCost,
                     IsLateGame(gameState));
         }
     }
@@ -252,7 +249,8 @@ auto LastPlayerStandingVictoryScore(
         const PlayerInfo* player,
         const APDCache& apdCache,
         const ALCache& alCache,
-        const SettingsGetter& settings) -> ScoreValue {
+        const BattalionTypeGetter& battalionTypeGetter,
+        ActionPoints braveWaterCost) -> ScoreValue {
     if (!std::ranges::contains(
                 *player->victory_conditions(),
                 net::eagle0::shardok::storage::fb::
@@ -285,8 +283,8 @@ auto LastPlayerStandingVictoryScore(
                                                  playerUnits,
                                                  apdCache,
                                                  alCache,
-                                                 settings,
-                                                 5,
+                                                 battalionTypeGetter,
+                                                 braveWaterCost,
                                                  IsLateGame(gameState),
                                                  /* includeUndead = */ true);
     }