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Third party interventions mitigate conflicts on interdependent networks

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  • Song, Zhao
  • Guo, Hao
  • Jia, Danyang
  • Perc, Matjaž
  • Li, Xuelong
  • Wang, Zhen

Abstract

Interventions from third parties, such as governmental agencies or organizations, play an important role in mitigating conflicts in modern human societies. The goal thereby is to pacify disputants, although this is subject to failure on account of self-interest from all involved. To study how relationships between disputants and third parties evolve, we propose an interdependent network model, where one layer is occupied by disputants and the other layer is occupied by third parties. Disputants play a prisoner’s dilemma game, where defection is the dominant strategy, whereas third parties play a snowdrift game, where cooperation and defection coexist more commonly. Moreover, third parties have the ability to mediate a conflict on the other layer by enforcing a snowdrift game onto disputants, for which they can receive a fee. We show that third party interventions improve the evolution of cooperation between disputants, and also, that the improvement of cooperation in turn promotes interventions. Nonetheless, non-intervention does not go extinct, which enables defectors to survive, thus creating a feedback loop between the two networks layers. The evolutionary dynamics is characterized by fascinating spatial pattern formation, which we explore by means of Monte Carlo simulations and via replicator equations.

Suggested Citation

  • Song, Zhao & Guo, Hao & Jia, Danyang & Perc, Matjaž & Li, Xuelong & Wang, Zhen, 2021. "Third party interventions mitigate conflicts on interdependent networks," Applied Mathematics and Computation, Elsevier, vol. 403(C).
  • Handle: RePEc:eee:apmaco:v:403:y:2021:i:c:s009630032100268x
    DOI: 10.1016/j.amc.2021.126178
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    Cited by:

    1. Xiaopeng Li & Zhonglin Wang & Jiuqiang Liu & Guihai Yu, 2023. "The Sense of Cooperation on Interdependent Networks Inspired by Influence-Based Self-Organization," Mathematics, MDPI, vol. 11(4), pages 1-16, February.
    2. Gao, Yanli & Liang, Chongsheng & Zhou, Jie & Chen, Shiming, 2023. "Robustness optimization of aviation-high-speed rail coupling network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    3. You, Tao & Yang, Haochun & Wang, Jian & Zhang, Peng & Chen, Jinchao & Zhang, Ying, 2023. "Cooperative behavior under the influence of multiple experienced guiders in Prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 458(C).
    4. Guo, Yujie & Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2023. "Network adaption based on environment feedback promotes cooperation in co-evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    5. Song, Sha & Pan, Qiuhui & Zhu, Wenqiang & He, Mingfeng, 2023. "Evolution of cooperation in games with dual attribute strategy," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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