Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
Name : 35th Fuzzy System Symposium
Number : 35
Location : [in Japanese]
Date : August 29, 2019 - August 31, 2019
Monte Carlo tree search (MCTS) has a problem that in a huge game where there are hundreds of millions of branching factors of a search tree, a large number of hands are not considered at all in the first step. Grouping nodes is one solution to this problem. To investigate the effect of introducing abstract nodes by grouping on the efficiency of MCTS based on the existing research on grouping nodes, we proposed a method to create game trees randomly, and played experimental matches between grouping AI and no grouping AI. As a result of the experiment, it was shown that the efficiency of the MCTS could be greatly improved by grouping when the branching factor of the search tree is large, or by grouping to reduce more branching factor and increase the depth by that amount.
