Efficient Sampling Method for Monte Carlo Tree Search Problem

Kazuki TERAOKA, Kohei HATANO, Eiji TAKIMOTO
2014 IEICE transactions on information and systems  
We consider Monte Carlo tree search problem, a variant of Min-Max tree search problem where the score of each leaf is the expectation of some Bernoulli variables and not explicitly given but can be estimated through (random) playouts. The goal of this problem is, given a game tree and an oracle that returns an outcome of a playout, to find a child node of the root which attains an approximate min-max score. This problem arises in two player games such as computer Go. We propose a simple and
more » ... se a simple and efficient algorithm for Monte Carlo tree search problem. key words: Monte Carlo tree search, random sampling, game, UCT Kazuki Teraoka received B.E and M.E. degrees from Kyushu University in 2010 and 2012, respectively. He now works for Fujitsu Limited. Kohei Hatano
doi:10.1587/transinf.e97.d.392 fatcat:udirs5uk55d2fiyv2ih7gitlsm