Emergent behaviors of collective intelligence systems, exemplified by swarm model, have attracted broad interests in recent years. However, current research mostly stops at observational interpretations and qualitative descriptions of emergent phenomena and is essentially short of quantitative analysis and evaluation. In this paper, we conduct a quantitative study on the emergence of swarm model by using chaos analysis of complex dynamic systems. This helps to achieve a more exact understanding of emergent phenomena. In particular, we evaluate the emergent behaviors of swarm model quantitatively by using the chaos and stability analysis of swarm model based on largest Lyapunov exponent. It is concluded that swarm model is at the edge of chaos when emergence occurs, and whether chaotic or stable at the beginning, swarm model will converge to stability with the elapse of time along with interactions among agents.


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    Title :

    Analysis of the emergence in swarm model based on largest Lyapunov exponent


    Contributors:
    Wu, Yu (author) / Su, Jie (author) / Tang, Hong (author) / Tianfield, Huaglory (author)

    Publication date :

    2011-01-01


    Remarks:

    Wu , Y , Su , J , Tang , H & Tianfield , H 2011 , ' Analysis of the emergence in swarm model based on largest Lyapunov exponent ' , Mathematical Problems in Engineering , vol. 2011 , 745257 . https://doi.org/10.1155/2011/745257



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629





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