吉林大学学报(工学版) ›› 2011, Vol. 41 ›› Issue (6): 1694-1698.

• paper • Previous Articles     Next Articles

Computer solution of static evaluation problems based on positional analysis and genetic algorithm

YU Lei1,3,WEI Jun2,TIAN Feng3,LIU Jin-gao3   

  1. 1.School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;2.Teaching Center of Basic Courses, Jilin University, Changchun 130062, China;3.School of Information Science and Technology, East China Normal University, Shanghai 200062, China
  • Received:2010-01-07 Online:2011-11-01 Published:2011-11-01

PDF (PC)

582

Abstract:

An approach based on Go knowledge to calculate the static evaluation value is proposed, and the parameter of the model is further optimized by genetic algorithm. Through this approach, various static evaluation models based on different levels can be obtained. The results of text show that, compared with the original model, the accuracy and operation speed of the proposed approach are promoted by 93% and 35% respectively. We expect that, with such operation capacity, this model can be applied in the module of the middle game and end game of computer Go. This model has a practical utilization in researches on computer games, artificial intelligence and game software.

Key words:  artificial intelligence, static evaluation, positional analysis, genetic algorithm

CLC Number: 

  • TP182
[1] WU Wei-nan,CUI Nai-gang,GUO Ji-feng,ZHAO Yang-yang. Distributed integrated method for mission planning of heterogeneous unmanned aerial vehicles [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1827-1837.
[2] JIAO Yu-ling, ZHANG Peng, TIAN Guang-dong, XING Xiao-cui, ZOU Lian-hui. Slotting optimization of automated warehouse based on multi-population GA [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1398-1404.
[3] LI Qi-liang, CAO Guan-ning, LI Xuan, YANG Zhi-gang, ZHONG Li-yuan. Multi-parameters aerodynamic optimization of sedan [J]. 吉林大学学报(工学版), 2018, 48(3): 670-676.
[4] SUN Wen, WANG Qing-nian, WANG Jun-nian. Yaw-moment control of motorized vehicle for energy conservation during cornering [J]. 吉林大学学报(工学版), 2018, 48(1): 11-19.
[5] HU Yun-feng, WANG Chang-yong, YU Shu-you, SUN Peng-yuan, CHEN Hong. Structure parameters optimization of common rail system for gasoline direct injection engine [J]. 吉林大学学报(工学版), 2018, 48(1): 236-244.
[6] WANG Zhan-zhong, ZHAO Li-ying, CAO Ning-bo. Hazardous material transportation scheduling model based on mutilayer coding genetic algorithm [J]. 吉林大学学报(工学版), 2017, 47(3): 751-755.
[7] ZHENG Ming, ZHUO Mu-gui, ZHANG Shu-gong, ZHOU You, LIU Gui-xia. Reconstruction for gene regulatory network based on hybrid parallel genetic algorithm and threshold value method [J]. 吉林大学学报(工学版), 2017, 47(2): 624-631.
[8] ZHAO Yun-peng, YU Tian-lai, JIAO Yu-bo, GONG Ya-feng, SONG Gang. Damage identification method and factor evaluation for irregular-shaped bridge [J]. 吉林大学学报(工学版), 2016, 46(6): 1858-1866.
[9] CHEN Jin, LI Song-lin, SUN Zhen-ye, CHEN Gang. Integrated design of aerodynamic and structural performance for wind turbine dedicated airfoil [J]. 吉林大学学报(工学版), 2016, 46(6): 1940-1945.
[10] WEI Li-ying, LI Ming-jun. Bus priority signal timing model considering the influence of traffic guidance [J]. 吉林大学学报(工学版), 2016, 46(3): 777-784.
[11] GUO Yu-quan, LI Xiong-fei, LIU Xin. Heuristic genetic algorithm associated with spectral analysis uncovering multi-scale community of complex networks [J]. 吉林大学学报(工学版), 2015, 45(5): 1592-1600.
[12] LIU Lei, YANG Dong. Multi-objective genetic optimization algorithm for SLA-aware service composition problem [J]. 吉林大学学报(工学版), 2015, 45(1): 267-273.
[13] NA Jing-xin, GAO Jian-feng. Top-down design method based on local search and global optimization for cross-sectional size of bus body [J]. 吉林大学学报(工学版), 2014, 44(6): 1564-1570.
[14] WEI Gan, YANG Zhi-gang, LI Qi-liang. Aerodynamic optimization method for car body based on process costing genetic algorithm [J]. 吉林大学学报(工学版), 2014, 44(6): 1578-1582.
[15] YAN Chu-liang, HAO Yun-xiao, LIU Ke-ge. Fatigue life prediction of materials based on BP neural networks optimized by genetic algorithm [J]. 吉林大学学报(工学版), 2014, 44(6): 1710-1715.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd