Chess Engines in Python!

Project Overview

This project is part of the Object-Oriented Programming course at the University of Wrocław. The main goal is to develop several chess engines in Python using the python-chess library, along with a playable interface created with pygame. The project includes implementations of different algorithms such as MCTS (Monte Carlo Tree Search), Negamax, and a Random Player.

Features

1. Chess Engines

   • MCTS (Monte Carlo Tree Search): A decision-making algorithm that uses randomness to explore the most promising moves and simulates game outcomes to choose the best move.
   • Negamax: A variant of the Minimax algorithm, optimized for zero-sum games like chess, with alpha-beta pruning.
   • Random Player: A simple algorithm that makes random moves.
   • Stockfish: You can play against Stockfish. Warning! Remember to specify your stockfish path in config!

2. User Interface

   • A playable interface using pygame to interact with the chess engines.
   • Visualization of the chessboard, moves, and game status.
   • Support for player vs player, player vs engine and engine vs engine modes.

Requirements

• Python 3.9.6 or later
• chess 1.10.0 or later
• pygame 2.5.2 or later

You can install the necessary dependencies using:

pip install -r requirements.txt

Installation

git clone https://github.com/igorjakus/chess.git
cd chess
pip install -r requirements.txt

(Optional) If you want to use the Stockfish engine, download it and compile it from Stockfish website. In the config.py file, specify the path to the compiled binary of Stockfish.

Configuration

Feel free to modify config.py to fine-tune your experience. I've made the editing process as easy as possible.