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

MuZero

[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)

Implement AlphaZero/AlphaGo Zero methods on Chinese chess.

♟️ Vectorized RL game environments in JAX

Easily train AlphaZero-like agents on any environment you want!

A Multi-threaded Implementation of AlphaZero (C++)

Free Book about Deep-Learning approaches for Chess (like AlphaZero, Leela Chess Zero and Stockfish NNUE)

An asynchronous/parallel method of AlphaGo Zero algorithm with Gomoku

A pytorch based Gomoku game model. Alpha Zero algorithm based reinforcement Learning and Monte Carlo Tree Search model.

A gobang robot based on reinforcement learning.

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

A functional Alpha Zero that plays Othello using Keras

AlphaGo-Zero-Gobang 是一个基于强化学习的五子棋(Gobang)模型，主要用以了解AlphaGo Zero的运行原理的Demo，即神经网络是如何指导MCTS做出决策的，以及如何自我对弈学习。源码+教程

fast + parallel AlphaZero in JAX

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.

A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)

Learning from zero (mostly based off of AlphaZero) in General Game Playing.

PyTorch implementation of AlphaZero Connect from scratch (with results)

A fast, generalized, and modified implementation of Deepmind's distinguished AlphaZero in PyTorch.