DocumentCode
2650467
Title
The research of pattern symmetry problem in learning in computer Go
Author
Xin, Wei ; Yinglong, Sun ; Hui, Yang ; Jiao, Wang
Author_Institution
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2012
fDate
23-25 May 2012
Firstpage
3301
Lastpage
3306
Abstract
Pattern is a very effective approach to improve the Monte-Carlo tree search. Due to the limitation of affordable memory space, the two typical pattern sizes are 3*3 or 4*4. Pattern libraries may be constructed by hand-craft or machine learning, which are all suffered from pattern symmetry problem. This paper elaborates and classifies the pattern symmetry problem in 3*3-pattern and 4*4-pattern, and introduces the solution for solving it in learning procedure. The experimental results show that the solution is effective and the learning results are improved through solving pattern symmetry problem.
Keywords
Monte Carlo methods; computer games; learning (artificial intelligence); pattern classification; tree searching; Monte Carlo tree search; computer Go; learning procedure; pattern libraries; pattern sizes; pattern symmetry problem classification; Bayesian methods; Color; Computational modeling; Computers; Encoding; Games; Libraries; Learning; Monte-Carlo Go; Pattern; UCT;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location
Taiyuan
Print_ISBN
978-1-4577-2073-4
Type
conf
DOI
10.1109/CCDC.2012.6243085
Filename
6243085
Link To Document