4.7 Article

Redistribution promotes cooperation in spatial public goods games under aspiration dynamics

Journal

APPLIED MATHEMATICS AND COMPUTATION
Volume 363, Issue -, Pages -

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2019.124629

Keywords

Aspiration dynamics; Spatial public goods game; Income redistribution; Evolutionary game theory; Evolution of cooperation

Funding

  1. National Natural Science Foundation of China (NSFC) [61703082]
  2. Fundamental Research Funds for the Central Universities [N160403001]
  3. Major Program of National Natural Science Foundation of China [71790614]
  4. National Key Research and Development Program of China [2016YFB0901900]
  5. Fund for Innovative Research Groups of the National Natural Science Foundation of China [71621061]
  6. Major International Joint Research Project of the National Natural Science Foundation of China [71520107004]
  7. 111 Project [B16009]

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Redistribution is an important regulation mechanism commonly used to benefit the whole society by transferring capital to low-income members. How redistribution influences the evolution of cooperation, which has a crucial impact on the sustainable development of society, is studied in this paper. Spatial public goods game models are established and players utilize aspiration dynamics as the updating rule where strategies are chosen by comparing payoffs with an expected aspiration. Both the homogeneous aspiration and heterogeneous aspiration distributions are considered. It is found that redistribution significantly promotes the cooperation. However, with the increase of individual greed, the growth rate of cooperation level has a peak with the increase of redistribution proportion. Furthermore, the effect of redistribution on cooperative promotion under different aspiration distributions varies with the proportion of redistribution. Moreover, the evolutionary results in heterogeneous networks and regular graphs are compared. It is found that the promotion of redistribution for cooperation is more evident in heterogeneous networks, especially when hub nodes have larger aspirations. (C) 2019 Elsevier Inc. All rights reserved.

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