ANALYSIS OF UCT ALGORITHM POLICIES IN IMPERFECT INFORMATION GAME
For the problem of mini-max tree search,Upper Confidence Bound (UCB) algorithm for multi-armed bandit problem has already been extended to algorithm UCT (UCB applied to Trees).It has shown advantages in the search tree with high branching factors and attained a great success in several domains such as Go program.In this paper,exploration and exploitation balance factor (EBF) is introduced as important parameter in UCT policies.Based on a known domain,which is called Siguo game,the performances for the different parameterized policies of UCT algorithm are compared and analysis is provided also.Following,some hypotheses about the cause of the problems are presented.Moreover,the suggested method about adoption and parameterization of UCT policies is provided for different type and characteristics of game problems.
Computer game Imperfect information UCT Monte-Carlo sampling Exploration-exploitation
Jiajia Zhang Xuan Wang Ling Yang Jia Ji Dongsheng Zhi
Intelligence Computing Research Center Harbin Institute of Technology Shenzhen Graduate School,C302,HIT Campus Shenzhen University Town,NanShan District,XiLi,Shenzhen 518055,China
国际会议
杭州
英文
168-173
2012-10-30（万方平台首次上网日期，不代表论文的发表时间）