Connect4 reinforcement learning by AlphaGo Zero methods.

AlphaZero implementation for Othello, Connect-Four and Tic-Tac-Toe based on "Mastering the game of Go without human knowledge" and "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm" by DeepMind.

board games for your terminal!

Master Thesis project that provides a training framework for two player games. TicTacToe and Othello have already been implemented.

Visualisation of MCTS in Unity with C# for different games, being created for my third year university project at the University of York

Four-In-A-Row in Flutter

HybridAlpha - a mix between AlphaGo Zero and AlphaZero for multiple games

Minimal AlphaZero in PyTorch, trained on Connect4 on a 6x6 board.

A browser-based Connect 4 game made with Phaser 3! https://iammanish17.github.io/Connect4/

Connect 4 Game implemented using minimax alpha beta pruning algorithm

AI for the Connect 4 game

Connect 4 is a token game created with Python and module Numpy. Place 4 tokens in a row (vertically, horizontally, or diagonally) before your opponent wins. Single-player against Artificial Intelligence and multiplayer also available.

A multi-agent implementation of the game Connect-4 using MCTS, Minimax and Exptimax algorithms.

Connect 4 game with online multiplayer

University project in the course ICT Seminar 3. Using Tsetlin Machine for Pattern Recognition in the game Connect Four.

Basic AI engine written in C# that implements the alpha–beta pruning algorithm to create two-player, zero-sum games like Tic Tac Toe, Connect 4, or Chess.

AI for the game "Connect Four". Available on PyPI.

Connect 4 AI using Monte Carlo Tree Search algorithm.

A connect-n game coded in Java 10 with frequent use of streams and optionals

Connect-4 AI inspired by the AlphaZero paper that uses Monte-Carlo Tree Search, and a neural policy and value estimator neural network trained with samples generated from self play between previous iterations of the model.