> I came up with a nifty implementation in Python that outperforms the naive impl by 30x, allowing a pure python MCTS/NN interop implementation. See https://www

> I came up with a nifty implementation in Python that outperforms the naive impl by 30x, allowing a pure python MCTS/NN interop implementation. See https://www.moderndescartes.com/essays/deep_dive_mcts/ https://www.moderndescartes.com/essays/deep_dive_mcts/ Great post! Chasing pointers in the MCTS tree is definitely a slow approach. Although typically there are ~ 900 "considerations" per move for alphazero. I've found getting value/policy predictions from a neural network (or GBDT[1]) for the node expansions during those considerations is at least an order of magnitude slower than the MCTS tree-hopping logic. [1] https://github.com/cgreer/alpha-zero-boosted https://github.com/cgreer/alpha-zero-boosted