Chess AI using Alpha-Beta Pruning

Overview

This Chess AI was built using the Alpha-Beta Pruning algorithm to optimize the Minimax decision-making process. The AI evaluates board positions and makes efficient moves by pruning unnecessary branches in the search tree, improving performance.

Features

• Implements Alpha-Beta Pruning to enhance Minimax efficiency.
• Supports basic chess rules and move generation.
• Written in Python for ease of use and modification.
• Can play against a human player or another AI instance.

Installation

Ensure you have Python installed, then clone the repository:

git clone https://github.com/nathanaelmbale/Chess-Ai.git
cd Chess-Ai

Install dependencies :

pip install -r requirements.txt

Usage

Run the script to start the AI:

python ChessMain.py

Modify depth in the code to adjust the AI’s difficulty level.

How It Works

The AI uses:

1. Minimax Algorithm – To determine the best possible move by evaluating future positions.
2. Alpha-Beta Pruning – To eliminate unnecessary calculations and speed up decision-making.
3. Evaluation Function – To assess board states based on material, position, and other heuristics.

Future Improvements

• Implement a GUI using Pygame or Tkinter.
• Improve the evaluation function for better strategic play.
• Add support for opening books and endgame databases.
• Using a library like Tensorflow to train the Ai

Contributions

Feel free to fork the repository and submit pull requests for improvements!

License

This project is licensed under the MIT License.

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Made with ❤️ by Nathanael Mbale.