Bayesian optimization for backpropagation in Monte-Carlo tree search

25 Jan 2020Yueqin LiNengli Lim

In large domains, Monte-Carlo tree search (MCTS) is required to estimate the values of the states as efficiently and accurately as possible. However, the standard update rule in backpropagation assumes a stationary distribution for the returns, and particularly in min-max trees, convergence to the true value can be slow because of averaging... (read more)

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