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Impact of separation of interaction and replacement neighborhoods on spatial reciprocity

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  • Huang, Shasha
  • Luo, Dang

Abstract

Elucidating the evolution of cooperation is one of the greatest challenges in both evolutionary biology and social science. However, vast majority of existing studies simply assume that the interaction neighborhood and replacement neighborhood are symmetric, irrespective of the size of both neighborhoods. In this paper, we consider the asymmetrical setup, namely, the separation of interaction neighborhood and replacement neighborhood, into the prisoner’s dilemma game. In detail, it is assumed that there exist two types of players: player A possessing Moore interaction neighborhood and von Neumann replacement neighborhood and player B having von Neumann interaction neighborhood and Moore replacement neighborhood. Importantly, the fraction of former player is τ (the latter is 1−τ), and this ration keeps constant during the whole process. By means of Monte Carlo simulations, it is unveiled that cooperation can be promoted to the highest level at middle τ, which is related to the formation of giant cluster. Moreover, we also inspect the impact of uncertainty on the phase diagrams and find that middle τ completely changes the evolution trend of low or middle value. It is thus suggested the separation of interaction and replacement neighborhoods may shed new light into the solution of social dilemmas.

Suggested Citation

  • Huang, Shasha & Luo, Dang, 2015. "Impact of separation of interaction and replacement neighborhoods on spatial reciprocity," Applied Mathematics and Computation, Elsevier, vol. 253(C), pages 318-323.
  • Handle: RePEc:eee:apmaco:v:253:y:2015:i:c:p:318-323
    DOI: 10.1016/j.amc.2014.12.098
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    1. Kohei Miyaji & Jun Tanimoto & Zhen Wang & Aya Hagishima & Naoki Ikegaya, 2013. "Direct Reciprocity in Spatial Populations Enhances R-Reciprocity As Well As ST-Reciprocity," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    2. Shi, Dong-Mei & Yang, Han-Xin & Hu, Mao-Bin & Du, Wen-Bo & Wang, Bing-Hong & Cao, Xian-Bin, 2009. "Preferential selection promotes cooperation in a spatial public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(21), pages 4646-4650.
    3. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, April.
    4. Xia, Cheng-yi & Ma, Zhi-qin & Wang, Zhen & Wang, Juan, 2012. "Evaluating fitness by integrating the highest payoff within the neighborhood promotes cooperation in social dilemmas," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6440-6447.
    5. Zhen Wang & Lin Wang & Zi-Yu Yin & Cheng-Yi Xia, 2012. "Inferring Reputation Promotes the Evolution of Cooperation in Spatial Social Dilemma Games," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    6. Changbing Tang & Zhen Wang & Xiang Li, 2014. "Moderate Intra-Group Bias Maximizes Cooperation on Interdependent Populations," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-7, February.
    7. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    8. Tanimoto, Jun & Nakata, Makoto & Hagishima, Aya & Ikegaya, Naoki, 2012. "Spatially correlated heterogeneous aspirations to enhance network reciprocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 680-685.
    9. repec:hhs:iuiwop:487 is not listed on IDEAS
    10. Zhang, Hai-Feng & Jin, Zhen & Wang, Zhen, 2014. "Cooperation and popularity in spatial games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 86-94.
    11. Wang, Zhen & Du, Wen-Bo & Cao, Xian-Bin & Zhang, Lian-Zhong, 2011. "Integrating neighborhoods in the evaluation of fitness promotes cooperation in the spatial prisoner’s dilemma game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1234-1239.
    12. Shijun Wang & Máté S Szalay & Changshui Zhang & Peter Csermely, 2008. "Learning and Innovative Elements of Strategy Adoption Rules Expand Cooperative Network Topologies," PLOS ONE, Public Library of Science, vol. 3(4), pages 1-9, April.
    13. Cheng-Yi Xia & Sandro Meloni & Yamir Moreno, 2012. "Effects Of Environment Knowledge On Agglomeration And Cooperation In Spatial Public Goods Games," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(supp0), pages 1-17.
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