Chess AI Development with Alpha-Beta Pruning
Nathanael Mbale
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:
Install dependencies :
Usage
Run the script to start the AI:
Modify
depth in the code to adjust the AI’s difficulty level.How It Works
The AI uses:
Minimax Algorithm – To determine the best possible move by evaluating future positions.
Alpha-Beta Pruning – To eliminate unnecessary calculations and speed up decision-making.
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.
Made with ❤️ by Nathanael Mbale.
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Posted Dec 27, 2025
Developed Chess AI using Alpha-Beta Pruning to optimize Minimax.
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