Monte-Carlo Planning: Theoretically Fast Convergence Meets Practical Efficiency

26 Sep 2013Zohar FeldmanCarmel Domshlak

Popular Monte-Carlo tree search (MCTS) algorithms for online planning, such as epsilon-greedy tree search and UCT, aim at rapidly identifying a reasonably good action, but provide rather poor worst-case guarantees on performance improvement over time. In contrast, a recently introduced MCTS algorithm BRUE guarantees exponential-rate improvement over time, yet it is not geared towards identifying reasonably good choices right at the go... (read more)

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