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Nondestructive Intervention to Multi-Agent Systems through an Intelligent Agent

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  • Jing Han
  • Lin Wang

Abstract

For a given multi-agent system where the local interaction rule of the existing agents can not be re-designed, one way to intervene the collective behavior of the system is to add one or a few special agents into the group which are still treated as normal agents by the existing ones. We study how to lead a Vicsek-like flocking model to reach synchronization by adding special agents. A popular method is to add some simple leaders (fixed-headings agents). However, we add one intelligent agent, called ‘shill’, which uses online feedback information of the group to decide the shill's moving direction at each step. A novel strategy for the shill to coordinate the group is proposed. It is strictly proved that a shill with this strategy and a limited speed can synchronize every agent in the group. The computer simulations show the effectiveness of this strategy in different scenarios, including different group sizes, shill speed, and with or without noise. Compared to the method of adding some fixed-heading leaders, our method can guarantee synchronization for any initial configuration in the deterministic scenario and improve the synchronization level significantly in low density groups, or model with noise. This suggests the advantage and power of feedback information in intervention of collective behavior.

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  • Jing Han & Lin Wang, 2013. "Nondestructive Intervention to Multi-Agent Systems through an Intelligent Agent," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.
    • Handle: RePEc:plo:pone00:0061542
    DOI: 10.1371/journal.pone.0061542
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    References listed on IDEAS

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    1. Jesús Gómez-Gardeñes & Gorka Zamora-López & Yamir Moreno & Alex Arenas, 2010. "From Modular to Centralized Organization of Synchronization in Functional Areas of the Cat Cerebral Cortex," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-11, August.
    2. Dirk Helbing & Illés Farkas & Tamás Vicsek, 2000. "Simulating dynamical features of escape panic," Nature, Nature, vol. 407(6803), pages 487-490, September.
    3. Iain D. Couzin & Jens Krause & Nigel R. Franks & Simon A. Levin, 2005. "Effective leadership and decision-making in animal groups on the move," Nature, Nature, vol. 433(7025), pages 513-516, February.
    4. Xin Wang & Jing Han & Huawei Han, 2011. "Special Agents Can Promote Cooperation in the Population," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-9, December.
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    Cited by:

    1. Yi Zou & Wenjie Zhan & Yuan Shao, 2014. "Evolution with Reinforcement Learning in Negotiation," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-7, July.

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