This project is a simple implementation of the classic Flappy Bird game with an added twist – it incorporates an AI agent trained using the NEAT (NeuroEvolution of Augmenting Topologies) algorithm to play the game. The AI learns to navigate through pipes and accumulate a higher score over generations.

• Installation
• Usage
• Game Controls
• Training the AI
• Configuration
• Dependencies
• Contributing
• License

1. Clone the repository:

   git clone https://github.com/your-username/flappybird-ai.git
   cd flappybird-ai

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the game:

   python flappybird_ai.py

The game can be played manually or left to run autonomously with the AI taking control. The AI is trained using the NEAT algorithm and evolves over multiple generations to improve its performance.

• Space Bar: Jump (Manual mode)
• Close Window Button: Quit the game

The AI is trained automatically during the execution of the game. It uses the NEAT algorithm to evolve neural networks for the bird entities. The training progress and generation statistics are displayed on the game window.

The game's behavior and AI training parameters can be configured using the config-feedforward.txt file. Adjustments to parameters such as mutation rates, population size, and neural network architecture can be made to experiment with different training strategies.

• Python 3.x
• Pygame
• NEAT-Python

Install the required dependencies using the provided requirements.txt file.

pip install -r requirements.txt

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.

This project is licensed under the MIT License. Feel free to use, modify, and distribute the code for your own purposes.