Popular GitHub Repositories for Monte Carlo Tree Search

A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

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

Monte Carlo tree search in JAX

A tool for retrosynthetic planning

A Hearthstone AI based on Monte Carlo tree search and neural nets written in modern C++.

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

A library of reasoning algorithms for AI agents

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

fast + parallel AlphaZero in JAX

Various C# implementations of game AI

? Python implementation of single-player Monte-Carlo Tree Search.

Using self-play, MCTS, and a deep neural network to create a hearthstone ai player

A general purpose game playing A.I. framework based on the Monte Carlo tree search algorithm.

Online Signal Temporal Logic (STL) Monte-Carlo Tree Search for Guided Imitation Learning

Monte Carlo Tree Search Self-Refine (MCTSr)

KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search

MONTE 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 and planning problems. In this project I used a board game called "HEX" as a platform to test different simulation strategies in MCTS field.

[ICLR 2025 Oral] OptionZero: A method for autonomously discovering and utilizing options in the MuZero algorithm

Homing Piegon is an inference framework implementing Variational Message Passing. It can be used to implement an Active Inference agent that performs planning using a Tree Search algorithm that can been seen as a form of Bayesian Model Expansion.

hyper optimized alpha zero implementation to play gomoku (distributed training with ray, mcts with cython)