Alphazero gomokuAn implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Alpha Zero GeneralA clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
quoridor-aiQuoridor AI based on Monte Carlo tree search
MCTS-agent-pythonMonte Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games …
AnimalChessAnimal Fight Chess Game(斗兽棋) written in rust.
UCThelloUCThello - a board game demonstrator (Othello variant) with computer AI using Monte Carlo Tree Search (MCTS) with UCB (Upper Confidence Bounds) applied to trees (UCT in short)
connect4Solving board games like Connect4 using Deep Reinforcement Learning
ludorum.jsA board game framework, focused not on graphics or user interfaces, but on artificial players design, implementation and testing.
alpha sigmaA pytorch based Gomoku game model. Alpha Zero algorithm based reinforcement Learning and Monte Carlo Tree Search model.
alphastoneUsing self-play, MCTS, and a deep neural network to create a hearthstone ai player
HypernetsA General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.