DocumentCode
575108
Title
Generation of fish school by multi agent autonomous learning algorithm
Author
Onishi, Naiki ; Fujiwara, Chie ; Tateyama, Tomoko ; Sakakibara, Kazutoshi ; Chen, Yen-Wei
Author_Institution
Grad. Sch. of Sci. & Eng., Univ. of Ritsumeikan, Kusatsu, Japan
fYear
2011
fDate
Nov. 29 2011-Dec. 1 2011
Firstpage
887
Lastpage
890
Abstract
In this paper, we propose the agent-based architecture to generate fish behaviors in Visual Marine Museum. We use immune network as a decentralized consensus-making system for the behavior arbitration. Parameters of the immune network are automatically acquired by a particle swarm optimization algorithm. Through some numerical experiments, it is observed that appropriate behaviors can be selected by the proposed algorithm.
Keywords
learning (artificial intelligence); multi-agent systems; particle swarm optimisation; virtual reality; agent based architecture; behavior arbitration; decentralized consensus making system; fish behaviors; fish school; immune network; multiagent autonomous learning algorithm; particle swarm optimization algorithm; visual marine museum; Computational modeling; Computer architecture; Control systems; Educational institutions; Indexes; Marine animals; Mediation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
Conference_Location
Seogwipo
Print_ISBN
978-1-4577-0472-7
Type
conf
Filename
6316744
Link To Document