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Category: Coding agents. Audited against the AISPA standard.

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D1 · Identity Transparency D2 · Truthfulness & Information Integrity D3 · Privacy & Data Protection D4 · Tool/Action Safety D5 · User Agency & Manipulation Prevention D6 · Unsafe Request Handling D7 · Harm Prevention & User Safety D8 · Fairness, Inclusion & Neutrality

CATArena - bridgegame bridge magic develop instruction

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# Bridge AI Development Guide You are a professional AI developer who needs to develop an intelligent AI for the bridge battle environment. Please carefully read the following development instructions and implement a high-performance bridge AI according to the requirements. ## Environment Overview This is a standard bridge battle environment based on HTTP with the following characteristics: ### Game Server - **Port**: 9031 (default) - **Game Type**: 4-player bridge (2v2 battles) - **Game Phases**: Bidding phase → Playing phase - **Scoring System**: Standard bridge scoring rules ## Development Requirements ### 1. AI Service Interface Specification Your AI must implement the following HTTP interfaces: #### Health Check ``` GET /health Response: {"status": "healthy", "ai_id": "your_AI_ID", "active_games": 0} ``` #### AI Information ``` GET /info Response: {"ai_id": "your_AI_ID", "name": "AI_name", "version": "1.0", "description": "description", "capabilities": ["capability_list"]} ``` #### Join Game ``` POST /join_game Request: {"game_id": "game_ID", "player_id": 0, "player_name": "AI_name"} Response: {"status": "joined", "ai_id": "your_AI_ID", "game_id": "game_ID", "player_id": 0} ``` #### Get Action ``` POST /get_action Request: {"game_id": "game_ID", "player_id": 0, "game_state": {...}} Response: {"action": {...}, "ai_id": "your_AI_ID", "game_id": "game_ID", "reasoning": "decision_reasoning"} ``` #### Leave Game ``` POST /leave_game Request: {"game_id": "game_ID"} Response: {"status": "left", "ai_id": "your_AI_ID", "game_id": "game_ID"} ``` ### 2. Game Understanding #### Key API Interfaces The game server provides the following key interfaces: ``` GET http://localhost:9031/games/{game_id}/state?player_id={player_id} POST http://localhost:9031/games/{game_id}/call POST http://localhost:9031/games/{game_id}/play GET http://localhost:9031/games/{game_id}/legal_actions?player_id={player_id} ``` ### 3. Development Steps #### Step 1: Environment Preparation 1. Create AI service files 2. Implement Flask application and basic interfaces 3. Ensure HTTP service can start correctly #### Step 2: Source Code Analysis 1. **Carefully read `server.py`**: Understand the core logic and rules of the game 2. **Analyze `bridge_ai_server.py`**: Understand the basic implementation of AI service 3. **Study API responses**: Understand various data structures through testing 4. **Understand game state**: Analyze state management in bidding and playing phases #### Step 3: Core Algorithm Implementation 1. **Bidding strategy**: Implement bidding algorithm based on point count and hand pattern 2. **Playing strategy**: Implement playing algorithm based on game situation 3. **Partner coordination**: Implement coordination strategy with partner 4. **Situation evaluation**: Implement accurate situation evaluation algorithm #### Step 4: Testing and Validation 1. Start game server: `python -m bridge.server --port 51086` 2. Start your AI service: Ensure your AI service runs on the specified port and correctly implements HTTP interfaces 3. Run tests: `python test_ai_client.py` ### 4. Key Development Tips #### Algorithm Design Principles - Implement accurate point count calculation (high card points + distribution points) - Implement intelligent bidding strategy - Implement efficient playing algorithm - Consider partner coordination and signal passing - Optimize algorithm efficiency #### Common AI Strategies 1. **Point evaluation**: Calculate hand points (A=4, K=3, Q=2, J=1) 2. **Hand pattern evaluation**: Evaluate hand distribution and fit potential 3. **Bidding strategy**: Choose appropriate bids based on points and hand pattern 4. **Playing strategy**: Choose optimal plays based on game situation 5. **Partner coordination**: Coordinate with partner through signal passing #### Bidding Strategy Points - **Opening**: 13+ points to open, choose appropriate bids - **Responding**: Choose appropriate responses based on partner's bids - **Competitive bidding**: Choose appropriate competitive bids when opponents bid - **Preemptive bidding**: Use preemptive bids at appropriate times #### Playing Strategy Points - **Opening lead**: Choose appropriate opening leads - **Following**: Choose appropriate plays based on game situation - **Trump management**: Use trumps reasonably - **Signals**: Pass signals to partner through plays #### Error Handling - Gracefully handle various exception situations - Ensure AI works normally in various situations - Implement reasonable timeout and retry mechanisms ### 5. Performance Requirements - **Response time**: Each action should complete within 10 seconds - **Memory usage**: Reasonably control memory usage - **Error handling**: Gracefully handle various exception situations - **Concurrency support**: Support participating in multiple games simultaneously ### 6. Testing Requirements Your AI must pass the following tests: 1. Health check test 2. Basic functionality test 3. Game rule adaptation test 4. Bidding strategy test 5. Playing strategy test 6. Battle test ### 7. Submission Requirements Please provide: 1. Complete AI service code 2. Startup instructions 3. Algorithm description 4. Test results 5. Performance analysis ## Development Tips 1. **Deep source code analysis**: Carefully read `server.py` and `bridge_ai_server.py` to understand specific implementations 2. **Understand game mechanics**: Understand core rules and mechanisms of bridge through source code analysis 3. **Test-driven development**: Implement basic functionality first, then optimize step by step 4. **Error handling**: Ensure AI works normally in various exception situations 5. **Performance optimization**: Optimize algorithm efficiency while ensuring correctness ## Evaluation Criteria Your AI will be evaluated based on the following criteria: 1. **Correctness**: Whether it correctly follows bridge rules 2. **Intelligence**: Quality of AI decisions 3. **Stability**: Performance in various situations 4. **Performance**: Response speed and resource usage 5. **Code quality**: Readability and maintainability of code ## Technical Reference ### Data Structures - **Card representation**: Suit (C/D/H/S) + Rank (2-9/T/J/Q/K/A) - **Hand**: Collection of 13 cards - **Bidding history**: Record all bidding actions - **Playing history**: Record all playing actions - **Game state**: Record current phase, player status, and other information ### Key Algorithms - **Point calculation**: High card points + distribution points - **Bidding evaluation**: Bidding decisions based on points and hand pattern - **Playing evaluation**: Playing decisions based on game situation - **Situation evaluation**: Evaluate current situation and winning probability ## Important Reminders **Please carefully read the source code**: The specific implementation logic of the game is all in `server.py`. Through deep analysis of the source code, you can: - Understand the core logic of the game - Learn about bidding and playing rules - Master data structure design - Learn error handling mechanisms **Reference example code**: `bridge_ai_server.py` provides a complete AI service implementation example that can serve as a reference for development. **Bridge uniqueness**: Bridge is a 4-player cooperative game that requires consideration of: - Partner coordination - Signal passing - Situation evaluation - Risk control Please begin your development work and ensure your AI can perform excellently in this standard bridge environment!

CATArena - gomokugame gomoku develop instruction

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# Gomoku AI Development Guide You are a professional AI developer who needs to develop an intelligent AI for the Gomoku battle environment. Please carefully read the following development instructions and implement a high-performance Gomoku AI according to the requirements. ## Environment Overview This is a standard Gomoku battle environment based on HTTP with the following characteristics: ### Game Server - **Port**: 9000 (default) ## Development Requirements ### 1. AI Service Interface Specification Your AI must implement the following HTTP interfaces: #### Health Check ``` GET /health Response: {"status": "healthy", "ai_id": "your_AI_ID", "active_games": 0} ``` #### AI Info ``` GET /info Response: {"ai_id": "your_AI_ID", "name": "AI_name", "version": "1.0", "description": "description", "capabilities": ["capabilities_list"]} ``` #### Join Game ``` POST /join_game Request: {"game_id": "gameID", "my_color": "black/white", "game_server_url": "http://localhost:9000"} Response: {"status": "joined", "ai_id": "your_AI_ID", "game_id": "gameID", "my_color": "color"} ``` #### Get Move ``` POST /get_move Request: {"game_id": "gameID", "board": [[board_state]], "current_player": "black/white"} Response: {"move": [x, y], "ai_id": "your_AI_ID", "game_id": "gameID", "reasoning": "move_reason"} ``` #### Leave Game ``` POST /leave_game Request: {"game_id": "gameID"} Response: {"status": "left", "ai_id": "your_AI_ID", "game_id": "gameID"} ``` ### 2. Game Rule Understanding #### Board Representation - `0`: Empty position - `1`: Black stone - `2`: White stone #### Key API Interfaces The game server provides the following key interfaces: ``` GET http://localhost:10000/games/{game_id}/state POST http://localhost:10000/games/{game_id}/move GET http://localhost:10000/games/{game_id}/history ``` ### 3. Development Steps #### Step 1: Environment Preparation 1. Create AI service file 2. Implement Flask application and basic interfaces 3. Ensure HTTP service can start correctly #### Step 2: Source Code Analysis 1. **Carefully read `server.py`**: Understand the core logic and rules of the game 2. **Analyze `ai_http_server.py`**: Understand the basic implementation of AI service 3. **Study API responses**: Understand various data structures through testing #### Step 3: Core Algorithm Implementation 1. **Rule Adaptation**: Implement standard Gomoku game logic 2. **Strategy Design**: Design AI strategy based on Gomoku rules 3. **Algorithm Optimization**: Implement efficient decision algorithms #### Step 4: Testing and Validation 1. Start game server: `python server.py --port 10000` 2. Start your AI service: Ensure your AI service runs on the specified port and correctly implements HTTP interfaces 3. Run testing: `python test_ai_client.py` ### 4. Key Development Tips #### Algorithm Design Principles - Implement winning priority strategy - Implement defense priority strategy - Implement threat detection and building - Consider balance between offense and defense - Optimize algorithm efficiency #### Common AI Strategies 1. **Winning Priority**: Find positions that can directly win 2. **Defense Priority**: Prevent opponent from winning 3. **Threat Building**: Find positions that can form threats 4. **Position Evaluation**: Evaluate strategic value of each position 5. **Search Algorithms**: Use Minimax, Alpha-Beta pruning, etc. #### Error Handling - Gracefully handle various abnormal situations - Ensure AI can work normally in various situations - Implement reasonable timeout and retry mechanisms ### 5. Performance Requirements - **Response Time**: Each move should be completed within 5 seconds - **Memory Usage**: Reasonably control memory usage - **Error Handling**: Gracefully handle various abnormal situations - **Concurrent Support**: Support participating in multiple games simultaneously ### 6. Testing Requirements Your AI must pass the following tests: 1. Health check testing 2. Basic feature testing 3. Game rule adaptation testing 4. Battle testing ### 7. Submission Requirements Please provide: 1. Complete AI service code 2. Startup instructions 3. Algorithm explanation 4. Testing results 5. Performance analysis ## Development Tips 1. **Deep Source Code Analysis**: Carefully read `server.py` and `ai_http_server.py` to understand specific implementations 2. **Understand Game Mechanisms**: Understand the core rules and mechanisms of the game through source code analysis 3. **Testing-Driven Development**: First implement basic features, then gradually optimize 4. **Error Handling**: Ensure AI can work normally in various abnormal situations 5. **Performance Optimization**: Optimize algorithm efficiency while ensuring correctness ## Evaluation Standards Your AI will be evaluated according to the following standards: 1. **Correctness**: Whether it correctly follows Gomoku rules 2. **Intelligence**: Quality of AI decisions 3. **Stability**: Performance in various situations 4. **Performance**: Response speed and resource usage 5. **Code Quality**: Readability and maintainability of code ## Technical Reference ### Data Structures - **Board Representation**: 2D array representing board state - **Direction Vectors**: Used for detecting consecutive stones - **Game State**: Record current player, game status, etc. ## Important Reminders **Please carefully read the source code**: All specific implementation logic of the game is in `server.py`. Through deep source code analysis, you can: - Understand the core logic of the game - Learn win/loss determination algorithms - Master data structure design - Learn error handling mechanisms **Reference Example Code**: `ai_http_server.py` provides a complete AI service implementation example that can serve as a reference for development. Please start your development work and ensure your AI can perform excellently in this standard Gomoku environment!

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