Skip to content

Latest commit

 

History

History
47 lines (35 loc) · 1.98 KB

README.md

File metadata and controls

47 lines (35 loc) · 1.98 KB
Raw

Chess Game with Minimax Algorithm Engine

This project provides an overview and guidance for implementing a simple chess game with a Minimax algorithm-based engine. The Minimax algorithm is a decision-making algorithm used in two-player games, such as chess, to find the optimal move for a player, assuming the opponent plays perfectly.

Introduction

This project focuses on creating a chess game where the computer opponent uses the Minimax algorithm for decision-making. The Minimax algorithm evaluates possible future game states to determine the best move.

Dependencies

  • Python (>=3.6)
  • Pygame library (for chess board visualization and interaction)

Install the required dependencies using:

pip install pygame

Getting Started

Clone the repository:

git clone https://github.com/ChieBKAI/minimax-chess-engine.git
cd chess-game-minimax

Minimax Algorithm Overview

The Minimax algorithm is a decision-making algorithm commonly used in two-player games with perfect information, like chess. It explores the game tree, considering all possible moves and opponent responses, to find the best move for the current player.

The algorithm minimizes the possible loss for a worst-case scenario (hence "min") while assuming the opponent maximizes their advantage (hence "max").

Implementation

The implementation is organized into modules:

  • ChessMain.py: Defines user interface.
  • ChessEngine.py: Defines the chess game logic.
  • ChienKoNgu.py (my fun name): Implements the Minimax algorithm for the computer opponent.

Game play

  • Press 'z' to Undo move
  • Press 'r' to reset the board to begin state
  • Press 'e' to play as white side
  • Press 'q' to play as black side
  • Press 'z' or 'r' will disable the AI. If you want to play with AI after that, just press 'e' or 'q'.

Game play

References

Creating a Chess Engine in Python