♟ Python Chess AI

A chess engine built from scratch in Python with a graphical interface (Pygame) and an AI opponent powered by the Minimax algorithm with alpha-beta pruning.

Personal project — built to explore game theory, tree search algorithms, and board evaluation heuristics.

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Features

• Full chess GUI with drag-and-drop piece movement
• Legal move validation using python-chess
• AI opponent playing as Black
• Minimax search with configurable depth
• Alpha-beta pruning for performance optimization
• Position evaluation based on piece values and positional tables

How the AI works

The AI evaluates every possible move using a recursive tree search:

1. Minimax — explores the game tree by alternating between maximizing (White) and minimizing (Black) scores
2. Alpha-beta pruning — cuts off branches that can't influence the final decision, reducing the number of positions evaluated
3. Evaluation function — assigns a score to each board state based on material (piece values) and positional bonuses (center control, king safety)

Tech stack

Component	Technology
Language	Python
GUI	Pygame
Chess logic	python-chess
Algorithm	Minimax + Alpha-Beta pruning

Getting started

git clone https://github.com/AmZzPYJS/Python-Chess-AI.git
cd Python-Chess-AI
pip install -r requirements.txt
python main.py

Project structure

Python-Chess-AI/
├── main.py              # Entry point — game loop and GUI rendering
├── requirements.txt     # Dependencies
├── screen/              # Screenshots
├── LICENSE
└── README.md

What I learned

• Implementing a tree search algorithm (Minimax) and understanding its time complexity
• How alpha-beta pruning drastically reduces the search space
• Designing a board evaluation function with piece-square tables
• Building an interactive GUI with Pygame's event loop
• Working with the python-chess library for move generation and validation

License

MIT