A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
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Updated
May 16, 2024 - Jupyter Notebook
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
A very fast implementation of AlphaZero, applied to games like Splendor, Santorini, The Little Prince, … Browser version available
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Computer go engine using Monte-Carlo Tree Search written in Python3.
A PyTorch implementation of DeepMind's AlphaZero agent to play Go and Gomoku board games
Unofficial attempt to rebuild AlphaGo Zero
SAI: a fork of Leela Zero with variable komi.
Java based alpha zero reinforcement learning. The generic base module allows implementation of any adversary board game. Example implementation for Tic Tac Toe.
♟️ A combination of Reinforcement Learning and Alpha-Beta Search in Chinese chess
Switchable Lightweight Anti-symmetric Processing (SLAP) with CNN - Application in Gomoku Reinforcement Learning
AlphaCC Zero: A Decision-Making Algorithm in Reinforcement Learning for Chinese Chess (SRTP)
😼 AlphaZero Gomoku
Chess reinforcement learning by AlphaGo Zero methods.
Personal implementation of deep learning algorithms in the RL space to learn.
Solving board games like Connect4 using Deep Reinforcement Learning
Reversi reinforcement learning by AlphaGo Zero methods.
Implementation of Alpha Go Zero - Reinforcement Learning Project, COL870 @iit-delhi
Congratulation to DeepMind! This is a reengineering implementation (on behalf of many other git repo in /support/) of DeepMind's Oct19th publication: [Mastering the Game of Go without Human Knowledge]. The supervised learning approach is more practical for individuals. (This repository has single purpose of education only)
Code and other material for the book "Deep Learning and the Game of Go"
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