Minmax (minimax) algorithm with Alpha-Beta (𝛼−𝛽, ab) Pruning optimization for the Checkers (Draughts) game in Python 3. Same minimax algorithm works for chess, tic tac toe or similar games.

Halma game with an AI player, move validation, and dynamic board sizing

Implementations of artificial intelligence agents that plays Pac-Man

Lichess BOT engine

Tic-Tac-Toe game written in Python and using pyGame; you can play versus another player or the computer on 2 difficulties: normal (random choices) and hard (minimax algorithm)

Chess AI using neural networks to predict move value

Game of isolation done as part of the Nanodegree program from Udacity

Implementation of reinforcement learning algorithms to solve pacman game. Part of CS188 AI course from UC Berkeley.

minimax algorithm implementation for tic tac toe

Developed a chess game agent using Minimax Algorithm in Python Language

A game of knight's Isolation between two AIs, to test minimax alpha-beta search and Monte Carlo tree search

A Python framework for implementing AI agents that use adversarial strategies in two-player, zero-sum games.

👻 🎮 This is my implementation in the famous Berkeley pacman artificial intelligence project: http://ai.berkeley.edu/project_overview.html.

Unbeatable Noughts And Crosses AI

This is a checkers game, that use minimax seach with alpha-beta prunning.

Adversarial search agent to play the game "Isolation": minimax search, minimax + alpha-beta pruning + iterative deepening

Array of AI Search algorithms is employed to playing Pac-Man ⍩⃝.

In this project, agents are designed for the classic version of Pacman, including ghosts. Mini-max, Alpha-Beta pruning, Expectimax techniques were used to implement multi-agent pacman adversarial search.

AI projects on: minimax algorithm, variations of nqueens problem, and policy iteration in Markov Decision Processes