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3

This is a massive question. There are two basic approaches, with the key difference being the search algorithm. The first approach, currently used by the world's strongest engine Stockfish, involves minimax as the search algorithm. It then calls the NNUE to evaluate the position at the end of the search tree. The minimax algorithm involves a lot of human ...


1

AlphaZero algorithm was implemented in Leela Chess Zero and was actually one of the leaders at least before Stockfish implemented its own NN assistant algorithm. Here: https://en.wikipedia.org/wiki/Leela_Chess_Zero NNs: https://training.lczero.org/networks/?show_all=0 Code: https://github.com/LeelaChessZero/lc0/releases It has distributive learning on Nvidia ...


1

I would recommend a classical AI approach. I suggest you implement a Minimax with depth limiting or A* with depth limiting. In these scenarios, you basically rebuild the game tree and try all moves and observe what happens ("OK, if I move this here, I gain advantage, if I move this there, I gain more advantage, etc....") If you are dead set on ...


5

I'm not an expert in the field, but I want to draw your attention to reinforcement learning (which is also mentioned in the Wikipedia article on AlphaZero). The book "Reinforcement Learning: An Introduction" (Richard S. Sutton and Andrew G. Barto) is a good starting point. Seems to be kind of "the bible" for starting with reinforcement ...


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