DocumentCode
2911834
Title
Response threshold model of aggregation in a swarm: A theoretical and simulative comparison
Author
Bailong, Liu ; Rubo, Zhang ; Changting, Shi
Author_Institution
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin
fYear
2008
fDate
1-6 June 2008
Firstpage
1103
Lastpage
1109
Abstract
Swarm Intelligence(SI) which is inspired by social animals has been paid more and more attention. It always appeals to the collective behaviors observed in social animals. Aiming at the feature and factors in self-organization of SI system, the aggregation behavior is studied. Firstly the response threshold model of the system is built according to the rules in aggregation. Then the stability of the steady-state solutions of the model is analyzed and the bifurcation of the steady-state solution is obtained. Finally, the effects of the parameter are analyzed based on the theory model. And the Monte Carlo simulations which give certain differences against theory results are also analyzed. All of the theoretical and simulative results show that the aggregation behavior is impacted by the relationship between the swarm size and the response threshold and sensitivity significantly. It is also proved that complex behavior emerges from local interaction of individuals. The work of this paper gives the mechanism in the emergent complex pattern of self-organized aggregation and the factors which affect the system evolution.
Keywords
Monte Carlo methods; artificial intelligence; Monte Carlo simulation; aggregation behavior; response threshold model; steady-state solution bifurcation; swarm intelligence; Animals; Ant colony optimization; Artificial intelligence; Bifurcation; Birds; Mathematical model; Negative feedback; Particle swarm optimization; Stability analysis; Steady-state;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4630934
Filename
4630934
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