August 22, 2012

VOI-aware MCTS

Filed under: Uncategorized — dvd @ 10:01 am

A poster for the paper VOI-aware MCTS to appear at ECAI 2012. The paper is a short version of the second part of Selecting Computations: Theory and Application (UAI 2012).


UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB1, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs from MAB in that in MCTS it is usually only the final “arm pull” (the actual move selection) that collects a reward, rather than all “arm pulls”. In this paper, an MCTS sampling policy based on Value of Information (VOI) estimates of rollouts is suggested. Empirical evaluation of the policy and comparison to UCB1 and UCT is performed on random MAB instances as well as on Computer Go.

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