A classic Connect Four game featuring two-player mode and an AI opponent powered by Monte Carlo Tree Search (MCTS), offering an exciting and strategic gameplay experience.

Text based classic Rummy game with an AI that uses ISMCTS. Data Structures and Algorithms course project, University of Helsinki

Java based alpha zero reinforcement learning. The generic base module allows implementation of any adversary board game. Example implementation for Tic Tac Toe.

Chinese Checkers computer player implementing Monte Carlo Tree Search

Tetris AI on botzone.org

Ultimate Tic Tac Toe for Android

In this project, my primary goal was to implement an AI player class powered by the Monte Carlo Tress Search algorithm which can play for a win as well as defend a defeat to compete with a Human player.

Tic-Tac-Toe game using the Monte Carlo Tree Search algorithm, implemented in Java.

Dice Shogi for CodinGame

Abstract Strategy Board Games

This projects seeks to explore the performance and dynamics of agents playing in a full Java implemetation of the game Imperial (http://bit.ly/Imperial-wiki). An array of different agent architectures are used ranging from simple rule-based to MCTS-Deep-Neural-Network agents.

MCTS/minimax turn-based game AI for Java

Reversi monte carlo tree search for android

This is the AI we created for a university course. It plays the famous game, Kalah.

model-based RL solvers for some card games

This repository contains the AI engine for a simplified version of Heartstone game

Sztuczna inteligencja w grach, semestr zimowy 2017/2018 II UWr

Cranes problem with Monte Carlo Tree Search algorithm