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A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play based reinforcement learning based on the AlphaGo ...
A PyTorch implementation of DeepMind's AlphaZero agent to play Go and Free-style Gomoku board game. This project is part of my book The Art of Reinforcement ...
This repo demonstrates an implementation of AlphaZero framework for Chess, using python and PyTorch. We all know that AlphaGo, created by DeepMind, ...
AlphaZero is an algorithm for training an agent to play perfect information games from pure self-play. It uses Monte Carlo Tree Search (MCTS) with the prior and ...
This package provides a generic, simple and fast implementation of Deepmind's AlphaZero algorithm: ... Many simple Python implementations can be found on Github ...
C++ & Cython based efficient and extendable implementation of AlphaZero based on Deepmind's papers Mastering the game of Go without Human Knowledge and A ...
This package provides a generic, simple and fast implementation of Deepmind's AlphaZero algorithm: The core algorithm is only 2,000 lines of pure, ...
2022/1/26 -So now I have finished the Libtorch AlphaZero implementation. I made in total the following changes: Adapt LibTorch AlphaZero to work with ...
AlphaZero-Othello is an implementation of the AlphaZero algorithm that learns to play Othello. It is written in pure Python, using the PyTorch library to ...
AlphaZero is a Reinforcement Learning algorithm which is effectively combine MCTS(Monte-Carlo Tree Search) with Actor-Critic. Alpha-Omok team wanted to apply ...