N.E.A.T Implementation in Python

This project implements the classic Flappy Bird game with a twist: the bird's actions are controlled by a neural network trained using the NEAT (Neuro-Evolution of Augmenting Topologies) library.

Features

• Trainable AI using NEAT for bird control
• Pixel-perfect collision detection
• Animated bird with smooth movement
• Scrolling background and base
• Fitness scoring based on bird survival time
• Customizable game configuration (optional)

Getting Started

Prerequisites

• Python 3.x
• Pygame library:

  pip install pygame

• NEAT library:

  pip install neat-python

• Check the REQUIREMENTS folder for better assistance.

Run the Game

1. Clone or download the repository.
2. Open a terminal in the project directory.
3. Run the script:

   python3 game.py

Training the AI

The game is configured to run for 50 generations by default. You can modify this behavior in the game.py script.

The NEAT library offers various configuration options for fine-tuning the training process. Refer to the NEAT documentation for details.

Project Structure

flappy_bird_neat/
├── config.txt         # (Optional: NEAT configuration file)
├── imgs/              # Image assets
│   ├── base.png
│   ├── bg.png
│   ├── bird1.png
│   ├── bird2.png
│   ├── bird3.png
│   └── pipe.png
├── main.py            # Entry point for the game
├── neat/              # NEAT library modules (installed package)
├── pygame/            # Pygame library modules (installed package)
├── game.py            # Script to run the game and train the AI

Further Enhancements

• Implement different obstacle types (varying heights, gaps)
• Introduce a reward system for the AI (points for passing pipes)
• Visualize the neural network's structure and weights
• Add a user-controllable bird mode (optional)

Feel free to explore and customize the code to create your own variations of the Flappy Bird game!

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With these steps, you should have all your project dependencies installed and ready to go. Happy coding! 🎉