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

Connect 4 game with online multiplayer

AI for the Connect 4 game

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

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.

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

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.

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.

Connect Four game written in Pygame