# 🤖 AI Agent Architecture **Date:** December 23, 2025 **Status:** 📋 In Planning ## 🎯 Goal Build an LLM-based AI agent that can play Settlers of Catan autonomously and intelligently. ## 🏗️ Overall Architecture ``` ┌─────────────────────────────────────────────────────────────┐ │ GameManager │ │ (Game coordination & decisions) │ ├─────────────────────────────────────────────────────────────┤ │ • game_loop() - Main game loop │ │ • handle_turn_rules() - Turn management │ │ • coordinate_interactions() - Player coordination │ └────────────────────┬────────────────────────────────────────┘ │ ┌────────────┼────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────┐ ┌─────────┐ ┌─────────┐ │ Game │ │ Users │ │ Viz │ │ (Core) │ │(Players)│ │(Display)│ └─────────┘ └────┬────┘ └─────────┘ │ ┌──────┴──────┐ │ │ ▼ ▼ ┌──────────┐ ┌──────────┐ │ Human │ │ AI Agent │ ← NEW! │ User │ │ (LLM) │ └──────────┘ └──────────┘ ✅ 🚧 ``` ## 📦 Existing Components ### 1️⃣ Core - The Game (game.py) **What exists:** - Complete and tested game rules - Board, player, and resource management - Action validation **Status:** ✅ Ready and stable ### 2️⃣ GameManager - Game Manager (management/game_manager.py) **What exists:** - Turn and phase management - Player coordination - Rule enforcement **Status:** ✅ Ready and stable ### 3️⃣ Actions - Action System (management/actions.py) **What exists:** - Definition of all possible game actions - Unified data structure for each action - Validation and permissions **Example:** ```python class Action: def __init__(self, action_type, player_num, **kwargs): self.action_type = action_type # BUILD_SETTLEMENT, BUILD_ROAD, etc. self.player_num = player_num self.details = kwargs # point, edge, resources, etc. ``` **Status:** ✅ Ready and stable ### 4️⃣ HumanUser - Human User (players/human_user.py) **What exists:** - CLI interaction - Getting decisions from user - Executing actions through GameManager **Status:** ✅ Ready and tested