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🐍 Red Snake AI

A DQN-based snake game with customizable skins. Train an AI to master the classic snake game or play it yourself!

Features

  • Deep Q-Learning AI agent
  • Multiple snake skins (Classic Red/Gold/Neon)
  • Human playable mode
  • Real-time training visualization
  • Performance tracking via wandb

Quick Start

  1. Clone the repository: 
    git clone https://github.com/me0w00f/red-snake-ai.git
  2. Navigate to the project directory: 
    cd red-snake-ai
  3. Install dependencies: 
    pip install -r requirements.txt

Game Details

Controls

  • Use Arrow Keys to change direction
  • Press P to pause the game
  • Press ESC to quit

Gameplay

  • The snake starts with a length of 3 segments
  • Each food item eaten adds 1 segment and 10 points
  • The snake speed increases every 50 points
  • Game ends if the snake hits the walls or itself

Display

  • Score is shown in the top-right corner
  • High score is saved between sessions
  • Game grid is 20x20 cells
  • Food appears randomly on the grid

AI training

This project serves as an excellent dataset for AI training purposes. The game's deterministic nature and clear rule set make it ideal for:

  • Reinforcement Learning algorithms
  • Deep Q-Learning implementations
  • Path-finding optimization
  • Pattern recognition training

The game state can be easily converted into numerical data, allowing AI models to:

  • Learn optimal movement patterns
  • Predict collision scenarios
  • Develop food-seeking strategies
  • Analyze performance metrics

Contributing

Contributions are welcome! If you have any ideas or improvements, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.