Multiple Tree for Partially Observable Monte-Carlo Tree Search

被引：0
|
作者：
Auger, David [1 ]
机构：
[1] Univ Paris 11, TAO, LRI, Inria Saclay IDP,UMR Cnrs 8623, F-91405 Orsay, France
来源：
APPLICATIONS OF EVOLUTIONARY COMPUTATION, PT I | 2011年 / 6624卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We propose an algorithm for computing approximate Nash equilibria of partially observable games using Monte-Carlo tree search based on recent bandit methods. We obtain experimental results for the game of phantom tic-tac-toe, showing that strong strategies can be efficiently computed by our algorithm.
引用
收藏
页码：53 / 62
页数：10
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