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

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

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

An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.

The official implementation of Self-Play Fine-Tuning (SPIN)

The official implementation of Self-Play Preference Optimization (SPPO)

A Massively Parallel Large Scale Self-Play Framework

SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning

Train a neural network to PvP in Old School RuneScape using reinforcement learning.

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

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.

Search Self-Play: Pushing the Frontier of Agent Capability without Supervision

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

The exact codes used by the team "liveinparis" at the kaggle football competition ranked 6th/1141

Backgammon OpenAI Gym

TD-Gammon implementation

AI agents for the bavarian card game Schafkopf trained with reinforcement learning

MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs

A Self Play reinforcement learning Agent learns to play TicTacToe using the ML-Agents Framework in Unity.

This is the implementation of paper Model Free Episodic Control

A UCI-compatible four-player chess engine

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

Code base for Social Robot Tree Search (SoRTS).

Self-Play Boxing Match made with Unity Machine Learning Agents

A gym environment to train chatbots.

A clean and easy implementation of MuZero, AlphaZero and Self-Play reinforcement learning algorithms for any game.

Code repository for On the interaction between supervision and self-play in emergent communication (ICLR 2020)

A reinforcement learning agent trained without prior human knowledge

Python + PyTorch. Advanced Reinforcement Learning (SAC/PPO/A2C) for ✨autonomous Robot Sumo combat featuring competitive self-play in continuous action spaces.

(AAAI24 oral) Implementation of RPPO(Risk-sensitive PPO) and RPBT(Population-based self-play with RPPO)