truetype bd211b6036 Implement phases 3-4 + all modules: decision engine, automapper, character creator, quest system, progression optimizer, and hybrid LLM integration
- Phase 4 (Decision Engine): ActionQueue with 7 priority tiers,
  4 behavior states (Idle/Explore/Combat/Loot), CombatAI with skill
  rotation and flee logic, GoalManager with survival override,
  DecisionEngine state machine integrated into the main game loop

- Phase 3 (Automapper): Complete hybrid SQLite/Memvid architecture
  with WorldMapper orchestrator, room fingerprinting (SHA-256),
  bidirectional exit linking, exploration queue, A* pathfinding,
  HistoricalStorage with JSON fallback, SemanticSearch with keyword
  fallback, SyncManager with configurable triggers

- Character Creator: State machine for automated character creation
  with stat rolling/optimization per class weights, race/class/gender
  selection, reroll logic with configurable thresholds

- Quest System: Quest lifecycle tracking (discover->accept->complete),
  NLP-based objective extraction (kill/fetch/talk/explore), EXP/time
  prioritization, pending kill target tracking

- Progression Optimizer: Grinding spot finder (EXP/hour), equipment
  comparison by weighted stats, skill rotation optimizer (DPS vs
  mana efficiency), session summary statistics

- LLM Integration (hybrid): Async Ollama client with retry/backoff,
  LLMBrain coordinator for quest parsing, social AI, decision advice,
  and ambiguous text parsing fallback. SocialAI for detecting and
  responding to player messages (say/tell/shout/group/trade).
  Graceful degradation when Ollama is unavailable.

All 214 tests passing.
2026-02-08 20:55:53 +01:00

MUD AI Player

An autonomous AI player for MUD (Multi-User Dungeon) text-based games.

Features

  • 🤖 Autonomous Gameplay: Simulates a human player from character creation to endgame
  • 🗺️ Auto-Mapping: Builds a complete map of the MUD world with hybrid storage (SQLite + Memvid)
  • ⚔️ Combat AI: Intelligent combat decisions, target selection, and survival tactics
  • 📜 Quest System: Automatically detects, plans, and completes quests
  • 🔍 Semantic Search: Find locations using natural language queries
  • 📊 Progression Optimizer: Finds optimal grinding spots and equipment upgrades

Architecture

The application is built with a modular architecture:

  • Core: Telnet client, ANSI parser, text parser, game state
  • Modules:
    • Character Creator: Stats rolling, class/race selection
    • Auto-Mapper: World mapping with hybrid storage (SQLite + Memvid)
    • Decision Engine: AI decision-making, combat AI, goal management
    • Quest System: Quest detection, planning, execution
    • Progression Optimizer: Grinding optimization, equipment analysis

Installation

# Install Poetry if not already installed
pip install poetry

# Install dependencies
poetry install

# Activate virtual environment
poetry shell

Using pip

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Configuration

  1. Copy the example configuration:

    cp examples/config.example.yaml config.yaml
    
  2. Edit config.yaml with your MUD server details:

    mud:
      host: "your-mud-server.com"
      port: 4000
      username: "your_username"
      password: "your_password"
    

Usage

# Run the AI player
python -m src.main

# Run with custom config
python -m src.main --config custom_config.yaml

# Run tests
pytest tests/ -v

# Run with coverage
pytest --cov=src --cov-report=html

Project Structure

mud-ai-player/
├── src/                    # Source code
│   ├── core/              # Core components
│   ├── modules/           # Specialized modules
│   ├── utils/             # Utilities
│   └── config/            # Configuration management
├── data/                  # Persistent storage
│   ├── maps/             # World maps (SQLite + Memvid)
│   ├── characters/       # Character saves
│   └── logs/             # Game logs
├── tests/                # Test suite
├── docs/                 # Documentation
└── examples/             # Example configurations

Development

# Format code
black src/ tests/

# Lint code
ruff check src/ tests/

# Run tests with watch
pytest-watch

Documentation

See the docs/ directory for detailed documentation:

License

MIT License

Contributing

Contributions are welcome! Please read the development guide before submitting PRs.

Disclaimer

This is an educational project. Please respect the rules and terms of service of any MUD you connect to. Some MUDs prohibit automated players.

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Description
An autonomous AI player for MUD (Multi-User Dungeon) text-based games.
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