This project implemented the AI with Minimax Algorithm, Alpha-Beta Pruning and Iterative Deepening algorithms to play Sudo Isolation Game.

JetBrains Academy - Python Developer - Tic-Tac-Toe with AI (+ bonus Reversi game)

This project uses pygame and the minimax algorithm to make a tic-tac-toe board where you can play against an AI.

Includes an AI agent for playing checkers

AI driven Tic-Tac-Toe game that runs on the Minimax algorithm with Alpha-Beta Pruning

AI for four in a row game using Minimax with alpha beta pruning and Monte Carlo Tree Search

An unbeatable Tic Tac Toe AI

Depth limited minimax implementation of Mancala game

A simple game of tic tac toe

An adversarial agent for playing Tic Tac Toe, offering users the option to choose board size and difficulty level. Utilizes various search algorithms including, but not limited to; Alpha-Beta Pruning, Expectimax, and Minimax. The project provides an interactive interface where users can play against the adversarial agent.

Bengal - A traditional chess engine written in python, play me on Lichess!

Minimax algorithm with alpha-beta pruning and iterative deepening

Implementation of checkers (draughts) strategy board game with AI

Connect Four w Online Multiplayer and AI.

Tic-Tac-Toe playing its Unbeatable

Using Minimax, I implemented an AI to play Tic-Tac-Toe optimally.

AI tic-tac-toe (board 3x3) by Minimax algorithm and Alpha-Beta pruning

A strategy game for 2 players. Here your opponent is an AI agent. Minimax algorithm with alpha-pruning is used to configure ai intelligence. The objective of Chain Reaction is to take control of the board by eliminating your opponents' orbs.

Super tic tac toe implementation, you can play against second player or a minimax ai