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A multi-community homogeneous small-world network and its fundamental characteristics

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  • Tanimoto, Jun

Abstract

We introduce a new small-world network–which we call the multi-community homogeneous-small-world network–that is divided into multiple communities that are relatively isolated, similar to sparsely connected islands. A generating algorithm is presented and its network parameters are explored. To elucidate the fundamental characteristics of the proposed topology, we adopt spatial prisoner’s dilemma games as a template for discussion. Comparing with a conventional homogeneous small-world network, more enhanced network reciprocity is observed in games where a stag hunt-type dilemma is large. With intensive analysis, we find how this enhancement is brought about.

Suggested Citation

  • Tanimoto, Jun, 2016. "A multi-community homogeneous small-world network and its fundamental characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 88-97.
  • Handle: RePEc:eee:phsmap:v:460:y:2016:i:c:p:88-97
    DOI: 10.1016/j.physa.2016.04.044
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    References listed on IDEAS

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    1. A. Szolnoki & M. Perc & G. Szabó, 2008. "Diversity of reproduction rate supports cooperation in the prisoner's dilemma game on complex networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(4), pages 505-509, February.
    2. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
    3. Tanimoto, Jun, 2015. "The impact of initial cooperation fraction on the evolutionary fate in a spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 263(C), pages 171-188.
    4. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
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    Cited by:

    1. Feng, Shumin & Xin, Mengwei & Lv, Tianling & Hu, Baoyu, 2019. "A novel evolving model of urban rail transit networks based on the local-world theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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