Abstract
Currently, many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals and make great progress in theory and practical application. However, in the case of multi-agent system consisting of large number of individuals, the existing control strategies cannot perfectly meet the actual demand of collective motions, those issues would cause the failure of large-scale collective motion. Thus, the research on the steady-state analysis of collective motion is more crucial. Based on the Lennard-Jones potential function and a self-organization process, this paper proposes a topological communication model to simulate the collective behaviors of real society. The structure of the collective motion at stable state are analyzed systematically by changing the number of agents in the group, the number of interconnections and the initial position. This work could provide a theoretical basis for the establishment of mass events and the prevention of mass incidents caused by social collective behavior.
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Acknowledgments
This research reported herein was supported by the NSFC of China under Grants No. 71571091 and 71771112.
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Wei, H., Shen, M., Chen, X. (2020). Steady-State Analysis of Multi-agent Collective Behavior. In: Cassenti, D. (eds) Advances in Human Factors and Simulation. AHFE 2019. Advances in Intelligent Systems and Computing, vol 958. Springer, Cham. https://doi.org/10.1007/978-3-030-20148-7_7
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DOI: https://doi.org/10.1007/978-3-030-20148-7_7
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