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
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;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7161848
