DocumentCode :
176562
Title :
UCT algorithm in Amazons human-computer games
Author :
Xiali Li ; Liang Hou ; Licheng Wu
Author_Institution :
Sch. of Inf. Eng., MINZU Univ. of China, Beijing, China
fYear :
2014
fDate :
May 31 2014-June 2 2014
Firstpage :
3358
Lastpage :
3361
Abstract :
The main difficulty of Amazons games is the huge branch factor. Traditional NegaMax Search and Alpha-Beta Search can only search a few layers and can´t improve the games effectively. Monte-Carlo Algorithm can improve the games but it needs a huge amount of computing. This paper studies applying UCT algorithm to the Amazons games to overcome this problem in order to balance the search efficiency and computing load. In UCT mini-max tree search, the algorithm select tree node according to the node´s UCB (Upper Confidence Bound) value. Then evaluate the selected node and return the optimal moves. Using C++ programming language, we implemented Amazons human-computer games software. The experiments show that UCT algorithm can implement the search work in Amazons human-computer games and get satisfactory search efficiency.
Keywords :
Monte Carlo methods; computer games; trees (mathematics); Alpha-Beta Search; Amazons human-computer games; C++ programming language; Monte Carlo algorithm; NegaMax Search; UCT algorithm; UCT mini-max tree search; computing load; search efficiency; upper confidence bound va;ue; Algorithm design and analysis; Computers; Games; Monte Carlo methods; Search problems; Software; Software algorithms; Amazons; Artificial Intelligence; Computer Games; Monte-Carlo; UCT Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
Type :
conf
DOI :
10.1109/CCDC.2014.6852755
Filename :
6852755
Link To Document :
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