Int. J. of Wireless and Mobile Computing   »   2016 Vol.11, No.1

 

 

Title: Swarm collective behaviour driven by artificial physics

 

Authors: Liping Xie; Jianchao Zeng; Shimin Jiao

 

Addresses:
Division of Industrial and System Engineering, and Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi 030024, China
Division of Industrial and System Engineering, and Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi 030024, China
Division of Industrial and System Engineering, and Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, No. 66 Waliu Road, Wanbailin District, Taiyuan, Shanxi 030024, China

 

Abstract: What kind of interaction and collaborative law among social creatures gives rise to swarm intelligence behaviour? Humans have cognitive limitation and therefore lack understanding of the essence of swarm intelligence. This leads to the emergence of the internal mechanism of swarm intelligence behaviour. In this paper, an artificial physics method to construct the swarm model is introduced. In the model, each individual is regarded as a physical particle. There exists virtual force among individuals, and each individual repels other individuals that are closer than R, while attracting individuals that are farther than R in distance. The law of force between any two individuals is defined and the potential field existence of the model is proved. The influence of the different values of the parameter p to swarm collective behaviour is analysed by drawing the force law curve. The simulation examples illustrate the effectiveness of the swarm model.

 

Keywords: artificial physics; swarm behaviour; virtual force; swarm intelligence; collective behaviour; simulation.

 

DOI: 10.1504/IJWMC.2016.079457

 

Int. J. of Wireless and Mobile Computing, 2016 Vol.11, No.1, pp.68 - 74

 

Submission date: 03 Feb 2016
Date of acceptance: 11 May 2016
Available online: 27 Sep 2016

 

 

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