An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

Code and other material for the book "Deep Learning and the Game of Go"

Reversi reinforcement learning by AlphaGo Zero methods.

Congratulation to DeepMind! This is a reengineering implementation (on behalf of many other git repo in /support/) of DeepMind's Oct19th publication: [Mastering the Game of Go without Human Knowledge]. The supervised learning approach is more practical for individuals. (This repository has single purpose of education only)

A student implementation of Alpha Go Zero

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.

Reinforcing Your Learning of Reinforcement Learning

PyTorch implementation of AlphaZero Connect from scratch (with results)

A PyTorch implementation of DeepMind's AlphaZero agent to play Go and Gomoku board games

alphaGo版本的五子棋(gobang, gomoku)

Computer go engine using Monte-Carlo Tree Search written in Python3.

Unofficial attempt to rebuild AlphaGo Zero

A very fast implementation of AlphaZero, applied to games like Splendor, Santorini, The Little Prince, … Browser version available

alphaGoZero论文的实现

Solving board games like Connect4 using Deep Reinforcement Learning

Board Game Reinforcement Learning using AlphaZero method. including Makhos (Thai Checkers), Reversi, Connect Four, Tic-tac-toe game rules

Deep Reinforcement Learning to Play 2048 (with Keras)

An implementation of the AlphaGo Zero and the AlphaZero algorithm for othello playing.

My Simple Implementation of AlphaGo Zero on Connect4