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Meta-Zeta is a Gobang model based on reinforcement learning. It is mainly used to understand the demo of the operating principle of AlphaGo Zero, that is, how the neural network guides MCTS to make decisions, and how to learn by itself. Source code + tutorial
License: MIT License