#计算机科学#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)
#计算机科学#An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.
翻译 - 星际争霸II中的OpenDILab决策AI
#计算机科学#The official implementation of Self-Play Fine-Tuning (SPIN)
#计算机科学#The official implementation of Self-Play Preference Optimization (SPPO)
A Massively Parallel Large Scale Self-Play Framework
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.
#计算机科学#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 ...
The exact codes used by the team "liveinparis" at the kaggle football competition ranked 6th/1141
A very fast implementation of AlphaZero, applied to games like Splendor, Santorini, The Little Prince, … Browser version available
TD-Gammon implementation
Backgammon OpenAI Gym
AI agents for the bavarian card game Schafkopf trained with reinforcement learning
#计算机科学#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
#计算机科学#Using self-play, MCTS, and a deep neural network to create a hearthstone ai player
Self-Play Boxing Match made with Unity Machine Learning Agents