NDLI: UCT algorithm in Amazons human-computer games

Content Provider	IEEE Xplore Digital Library
Author	Xiali Li Liang Hou Licheng Wu
Copyright Year	2014
Description	Author affiliation: Sch. of Inf. Eng., MINZU Univ. of China, Beijing, China (Xiali Li; Liang Hou; Licheng Wu)
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.
Starting Page	3358
Ending Page	3361
File Size	121551
Page Count	4
File Format	PDF
ISBN	9781479937073
e-ISBN	9781479937080
DOI	10.1109/CCDC.2014.6852755
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computers Monte Carlo methods Computer Games Software algorithms Artificial Intelligence Games Monte-Carlo Search problems Software Amazons UCT Algorithm
Content Type	Text
Resource Type	Article

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