DocumentCode
3206090
Title
A study of high-performance optimization algorithm based on Phantom Go
Author
Hu Guangfei ; Li Fei ; Qiu Hongkun ; Wang Yajie
Author_Institution
Comput. Inst., Shenyang Aerosp. Univ., Shenyang, China
fYear
2015
fDate
23-25 May 2015
Firstpage
5822
Lastpage
5825
Abstract
Phantom Go as an important branch of computer games is emerging. Monte Carlo algorithm is widely used in this kind of incomplete information games currently. However, there is a tradeoff between run time and its effectiveness. In this paper, based on the characteristics of Phantom Go, a novel algorithm is put forward, which merges Open Multi-Processing and Compute Unified Device Architecture parallel computing methods into the Monte Carlo algorithm. It improves the ability of Phantom Go to some extent.
Keywords
Monte Carlo methods; computer games; multiprocessing systems; optimisation; parallel architectures; Monte Carlo algorithm; Phantom Go; compute unified device architecture parallel computing methods; computer games; high-performance optimization algorithm; incomplete information games; open multiprocessing; Computational modeling; Computers; Games; Graphics processing units; Monte Carlo methods; Parallel processing; Phantoms; Compute Unified Device Architecture; Monte Carlo; Open Multi-Processing; Phantom Go;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7161848
Filename
7161848
Link To Document