A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
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Updated
Jun 6, 2024 - Jupyter Notebook
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation
An environment of the board game Go using OpenAI's Gym API
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.
Learning from zero (mostly based off of AlphaZero) in General Game Playing.
AlphaGo Zero implementation using Flux.jl
AlphaZero-like AI solution for playing Ultimate Tic-Tac-Toe in the browser
Using self-play, MCTS, and a deep neural network to create a hearthstone ai player
Deep Reinforcement Learning for Chess
An implementation of the AlphaZero algorithm for adversarial games to be used with the machine learning framework of your choice
A gomoku AI based on Alpha Zero paper.
HybridAlpha - a mix between AlphaGo Zero and AlphaZero for multiple games
A simplified version of Shogi with the AI is trained by alpha-zero-type training method
presentation on AlphaZero for AI seminar (http://ktiml.mff.cuni.cz/~bartak/ui_seminar/)
hyper optimized alpha zero implementation to play gomoku (distributed training with ray, mcts with cython)
A clean and easy implementation of MuZero, AlphaZero and Self-Play reinforcement learning algorithms for any game.
Visual representation of RTS game, supported by deep reinforcement learning algorithm Alpha Zero written in python.
Alpha Zero Implemented through Libtorch/pytorch
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