ChineseChess-AlphaZero and AlphaGo-Zero-Gobang
About ChineseChess-AlphaZero
NeymarL/ChineseChess-AlphaZero
Implement AlphaZero/AlphaGo Zero methods on Chinese chess.
This project helps Chinese chess enthusiasts and researchers develop and play against a powerful AI opponent. It takes game data (either self-generated or from existing online games) and trains an AI using advanced AlphaZero methods. The output is a highly skilled Chinese chess AI that you can play against directly within a graphical interface or integrate with other Chinese chess GUIs.
About AlphaGo-Zero-Gobang
YoujiaZhang/AlphaGo-Zero-Gobang
AlphaGo-Zero-Gobang 是一个基于强化学习的五子棋(Gobang)模型，主要用以了解AlphaGo Zero的运行原理的Demo，即神经网络是如何指导MCTS做出决策的，以及如何自我对弈学习。源码+教程
This project helps demonstrate how an AI can learn to play the game of Gobang (five-in-a-row) through self-play, inspired by AlphaGo Zero. It takes the rules of Gobang as input and produces an AI player capable of learning optimal moves and playing against a human. This is for AI enthusiasts, students, or researchers interested in understanding the practical application of reinforcement learning and Monte Carlo Tree Search (MCTS) in game AI.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work