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Promote of cooperation in networked multiagent system based on fitness control

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  • Deng, Wenfeng
  • Huang, Keke
  • Yang, Chunhua
  • Zhu, Hongqiu
  • Yu, Zhaofei

Abstract

How did cooperative strategy evolve remains an open question across disciplines. In most previous studies, they mainly consider the analyzing of game dynamics on the networked multiagent system under different mechanisms. However, there often exists a “government” who regulates the strategies of agents centralized or decentralized in reality. Motivated by this fact, we introduce a fitness control method in this paper, and investigate the strength of external fitness control on the game dynamics in networked multiagent system. According to the classic Monte Carlo simulation, we found that the fitness control rule can significantly enhance the cooperation level in networked multiagent system. In particular, we found that the stronger the local fitness control is, the more widespread cooperative strategy becomes. More interestingly, we found that although the local fitness control is less information needed, it is more powerful in cooperation promotion than that of global fitness control rule. Thus, it is practically significant and will provide a new insight into the control of game dynamics in networked multiagent system for the further research.

Suggested Citation

  • Deng, Wenfeng & Huang, Keke & Yang, Chunhua & Zhu, Hongqiu & Yu, Zhaofei, 2018. "Promote of cooperation in networked multiagent system based on fitness control," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 805-811.
  • Handle: RePEc:eee:apmaco:v:339:y:2018:i:c:p:805-811
    DOI: 10.1016/j.amc.2018.08.002
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    References listed on IDEAS

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    1. Su, Qi & Li, Aming & Wang, Long, 2017. "Spatial structure favors cooperative behavior in the snowdrift game with multiple interactive dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 299-306.
    2. Zhenhua Pei & Baokui Wang & Jinming Du, 2016. "Effects of income redistribution on the evolution of cooperation in spatial public goods games," Papers 1611.01531, arXiv.org.
    3. Huang, Keke & Chen, Xiaofang & Yu, Zhaofei & Yang, Chunhua & Gui, Weihua, 2018. "Heterogeneous cooperative belief for social dilemma in multi-agent system," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 572-579.
    4. Lucas Molleman & Pieter van den Berg & Franz J. Weissing, 2014. "Consistent individual differences in human social learning strategies," Nature Communications, Nature, vol. 5(1), pages 1-9, May.
    5. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    6. Swami Iyer & Timothy Killingback, 2016. "Evolution of Cooperation in Social Dilemmas on Complex Networks," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-25, February.
    7. Huang, Keke & Zheng, Xiaoping & Su, Yunpeng, 2015. "Effect of heterogeneous sub-populations on the evolution of cooperation," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 681-687.
    8. Manfred Milinski & Christian Hilbe & Dirk Semmann & Ralf Sommerfeld & Jochem Marotzke, 2016. "Humans choose representatives who enforce cooperation in social dilemmas through extortion," Nature Communications, Nature, vol. 7(1), pages 1-9, April.
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    Cited by:

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