DocumentCode :
2848613
Title :
Study on a solution of pursuit-evasion differential game based on artificial fish school algorithm
Author :
Hong-yan, Shi ; Zhi-Qiang, Shang
Author_Institution :
Sch. of Inf., Northeastern Univ., Shenyang, China
fYear :
2010
fDate :
26-28 May 2010
Firstpage :
2092
Lastpage :
2096
Abstract :
A resistance model with multi-parameter in the three-dimensional space by studying on the model of pursuit-evasion differential game is constituted. Based on the researching of artificial fish school algorithm, an intelligent optimum algorithm of differential game on the basis of artificial fish school algorithm is proposed. This algorithm has definite adaptive ability, which two point boundary value problem of differential game is solved using packaging two artificial fish colonies with the initial condition of the pursuit-evasion player. With the help of setting step and visual of the fish, the numerical solutions of the model is solved, avoiding solving the complex two point boundary value problem directly. Simulation result shows that this algorithm has stronger robustness, the time of the calculation is short and the model accords with more realistic counterworking.
Keywords :
boundary-value problems; differential games; optimisation; artificial fish school algorithm; boundary value problem; intelligent optimum algorithm; pursuit-evasion differential game; resistance model; Artificial intelligence; Boundary value problems; Clustering algorithms; Constraint optimization; Educational institutions; Game theory; Marine animals; Neural networks; Pursuit algorithms; Space technology; Artificial Fish School Algorithm; Differential Game; Numerical Solutions of Differential Game; Pursuit-evasion Differential Game Model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
Type :
conf
DOI :
10.1109/CCDC.2010.5498872
Filename :
5498872
Link To Document :
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