A Implementation of Alpha Zero for Chess in MLX
A chess engine implementation inspired by AlphaZero, using MLX for neural network computations and Monte Carlo Tree Search (MCTS) for move selection.
In plain words
This is a chess engine built using MLX for neural network computations combined with Monte Carlo Tree Search for selecting moves, following the AlphaZero approach. It is designed for developers and chess enthusiasts interested in AI-driven game playing systems. The implementation leverages MLX's efficient computation capabilities to train and run neural networks that evaluate chess positions alongside MCTS algorithms to explore possible move sequences.
written from the facts on this page · September 2026
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