Optimizing a chess engine using AI : implementation of Minmax algorithm and dealing with the horizon effect, well known in chess AI engins.es

A Chess engine using the Minimax Algorithm with Alpha-Beta Pruning. Add an evaluation function for making AI decisions and optimize its performance using bitboards.

It is a fully functional Chess Bot built using Python, Pygame, and python-chess, featuring a graphical interface, smooth animations, and an optimized depth-5 AI engine using classical game search techniques.

AI ChessBot using Minimax & Alpha-Beta pruning with transposition tables, piece weights, killer moves, and configurable depth. Supports Normal & Endgame modes. Demonstrates AI strategy, performance optimization, and algorithmic problem-solving in a full-featured chess engine.

Modern Chess AI is a Python-based chess engine with a sleek Tkinter GUI featuring red/green themed boards and modern Unicode glyphs. It uses Minimax with Alpha–Beta pruning, piece-square tables, and move/unmove optimizations for fast, responsive play. Features adjustable AI depth, algebraic notation input, check/checkmate detection etc.

This project implements a chess engine in Python using the Minimax algorithm with Alpha-Beta pruning. The AI evaluates moves strategically, reducing the number of nodes analyzed to improve efficiency. It includes modules for board representation, piece movement logic, and AI decision-making. Ideal for studying search algorithms and optimization