IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v567y2021ics0378437120310244.html
   My bibliography  Save this article

Social hierarchy promotes the cooperation prevalence

Author

Listed:
  • Liang, Rizhou
  • Zhang, Jiqiang
  • Zheng, Guozhong
  • Chen, Li

Abstract

Social hierarchy is important that cannot be ignored in human socioeconomic activities and in the animal world. Here we incorporate this factor into the evolutionary game to see what impact it could have on the cooperation outcome. The probabilistic strategy adoption between two players is then not only determined by their payoffs, but also by their hierarchy difference — players in the high rank are more likely to reproduce their strategies than the peers in the low rank. Through simulating the evolution of Prisoners’ dilemma game with three hierarchical distributions, we find that the levels of cooperation are enhanced in all cases, and the enhancement is optimal in the uniform case. The enhancement is due to the fact that the presence of hierarchy facilitates the formation of cooperation clusters with high-rank players acting as the nucleation cores. This mechanism remains valid on Barabási–Albert scale-free networks, in particular the cooperation enhancement is maximal when the hubs are of higher social ranks. We also study a two-hierarchy model, where similar cooperation promotion is revealed and some theoretical analyses are provided. Our finding may partially explain why the social hierarchy is so ubiquitous on this planet.

Suggested Citation

  • Liang, Rizhou & Zhang, Jiqiang & Zheng, Guozhong & Chen, Li, 2021. "Social hierarchy promotes the cooperation prevalence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
  • Handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310244
    DOI: 10.1016/j.physa.2020.125726
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120310244
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2020.125726?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Francisco C. Santos & Marta D. Santos & Jorge M. Pacheco, 2008. "Social diversity promotes the emergence of cooperation in public goods games," Nature, Nature, vol. 454(7201), pages 213-216, July.
    3. Ádám Kun & Ulf Dieckmann, 2013. "Resource heterogeneity can facilitate cooperation," Nature Communications, Nature, vol. 4(1), pages 1-8, December.
    4. Jason Olejarz & Whan Ghang & Martin A. Nowak, 2015. "Indirect Reciprocity with Optional Interactions and Private Information," Games, MDPI, vol. 6(4), pages 1-20, September.
    5. Máté Nagy & Zsuzsa Ákos & Dora Biro & Tamás Vicsek, 2010. "Hierarchical group dynamics in pigeon flocks," Nature, Nature, vol. 464(7290), pages 890-893, April.
    6. 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.
    7. Martin A. Nowak & Karl Sigmund, 2005. "Evolution of indirect reciprocity," Nature, Nature, vol. 437(7063), pages 1291-1298, October.
    8. Szolnoki, Attila & Perc, Matjaž & Danku, Zsuzsa, 2008. "Towards effective payoffs in the prisoner’s dilemma game on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(8), pages 2075-2082.
    9. Shu, Feng & Liu, Xingwen & Fang, Kai & Chen, Hao, 2018. "Memory-based snowdrift game on a square lattice," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 15-26.
    10. Marco Tomassini & Enea Pestelacci & Leslie Luthi, 2007. "Social Dilemmas And Cooperation In Complex Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1173-1185.
    11. Christoph Hauert & Michael Doebeli, 2004. "Spatial structure often inhibits the evolution of cooperation in the snowdrift game," Nature, Nature, vol. 428(6983), pages 643-646, April.
    12. Wu, Zhi-Xi & Guan, Jian-Yue & Xu, Xin-Jian & Wang, Ying-Hai, 2007. "Evolutionary prisoner's dilemma game on Barabási–Albert scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 672-680.
    13. Yang, Han-Xin & Chen, Xiaojie, 2018. "Promoting cooperation by punishing minority," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 460-466.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yu, Fengyuan & Wang, Jianwei & He, Jialu, 2022. "Inequal dependence on members stabilizes cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Zhang, Jing & Li, Zhao & Zhang, Jiqiang & Ma, Lin & Zheng, Guozhong & Chen, Li, 2023. "Emergence of oscillatory cooperation in a population with incomplete information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Fengyuan & Wang, Jianwei & He, Jialu, 2022. "Inequal dependence on members stabilizes cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Yongkui Liu & Xiaojie Chen & Lin Zhang & Long Wang & Matjaž Perc, 2012. "Win-Stay-Lose-Learn Promotes Cooperation in the Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    3. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    4. Lv, Shaojie & Wang, Xianjia, 2020. "The impact of heterogeneous investments on the evolution of cooperation in public goods game with exclusion," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    5. Jin, Jiahua & Chu, Chen & Shen, Chen & Guo, Hao & Geng, Yini & Jia, Danyang & Shi, Lei, 2018. "Heterogeneous fitness promotes cooperation in the spatial prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 141-146.
    6. 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.
    7. Yanlong Zhang, 2015. "Partially and Wholly Overlapping Networks: The Evolutionary Dynamics of Social Dilemmas on Social Networks," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 1-14, June.
    8. Wes Maciejewski & Feng Fu & Christoph Hauert, 2014. "Evolutionary Game Dynamics in Populations with Heterogenous Structures," PLOS Computational Biology, Public Library of Science, vol. 10(4), pages 1-16, April.
    9. Kokubo, Satoshi & Wang, Zhen & Tanimoto, Jun, 2015. "Spatial reciprocity for discrete, continuous and mixed strategy setups," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 552-568.
    10. Zu, Jinjing & Xu, Fanxin & Jin, Tao & Xiang, Wei, 2022. "Reward and Punishment Mechanism with weighting enhances cooperation in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    11. Dong, Yukun & Xu, Hedong & Fan, Suohai, 2019. "Memory-based stag hunt game on regular lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 247-255.
    12. Wang, Hanchen & Sun, Yichun & Zheng, Lei & Du, Wenbo & Li, Yumeng, 2018. "The public goods game on scale-free networks with heterogeneous investment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 396-404.
    13. Shu, Feng & Liu, Yaojun & Liu, Xingwen & Zhou, Xiaobing, 2019. "Memory-based conformity enhances cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 480-490.
    14. Wang, Chaoqian & Huang, Chaochao, 2022. "Between local and global strategy updating in public goods game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    15. Du, Faqi & Fu, Feng, 2013. "Quantifying the impact of noise on macroscopic organization of cooperation in spatial games," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 35-44.
    16. Li, Yan & Ye, Hang, 2015. "Effect of migration based on strategy and cost on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 156-165.
    17. Thomas Chadefaux & Dirk Helbing, 2010. "How Wealth Accumulation Can Promote Cooperation," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-7, October.
    18. Ping Zhu & Guiyi Wei, 2014. "Stochastic Heterogeneous Interaction Promotes Cooperation in Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    19. Deng, Zheng-Hong & Huang, Yi-Jie & Gu, Zhi-Yang & Liu, Dan & Gao, Li, 2018. "Multi-games on interdependent networks and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 83-90.
    20. Chen, Qiao & Chen, Tong & Wang, Yongjie, 2019. "Cleverly handling the donation information can promote cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 363-373.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310244. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.