IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v482y2017icp286-295.html
   My bibliography  Save this article

The evolution of cooperation in the Prisoner’s Dilemma and the Snowdrift game based on Particle Swarm Optimization

Author

Listed:
  • Wang, Xianjia
  • Lv, Shaojie
  • Quan, Ji

Abstract

This paper studies the evolution of cooperation in the Prisoner’s Dilemma (PD) and the Snowdrift (SD) game on a square lattice. Each player interacting with their neighbors can adopt mixed strategies describing an individual’s propensity to cooperate. Particle Swarm Optimization (PSO) is introduced into strategy update rules to investigate the evolution of cooperation. In the evolutionary game, each player updates its strategy according to the best strategy in all its past actions and the currently best strategy of its neighbors. The simulation results show that the PSO mechanism for strategy updating can promote the evolution of cooperation and sustain cooperation even under unfavorable conditions in both games. However, the spatial structure plays different roles in these two social dilemmas, which presents different characteristics of macroscopic cooperation pattern. Our research provides insights into the evolution of cooperation in both the Prisoner’s Dilemma and the Snowdrift game and maybe helpful in understanding the ubiquity of cooperation in natural and social systems.

Suggested Citation

  • Wang, Xianjia & Lv, Shaojie & Quan, Ji, 2017. "The evolution of cooperation in the Prisoner’s Dilemma and the Snowdrift game based on Particle Swarm Optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 286-295.
  • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:286-295
    DOI: 10.1016/j.physa.2017.04.080
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117303941
    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.2017.04.080?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. Yuhui Shi, 2011. "An Optimization Algorithm Based on Brainstorming Process," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 2(4), pages 35-62, October.
    2. Huang, Keke & Zheng, Xiaoping & Yang, Yeqing & Wang, Tao, 2015. "Behavioral evolution in evacuation crowd based on heterogeneous rationality of small groups," Applied Mathematics and Computation, Elsevier, vol. 266(C), pages 501-506.
    3. Ernst Fehr & Simon Gächter, 2002. "Altruistic punishment in humans," Nature, Nature, vol. 415(6868), pages 137-140, January.
    4. Chen Liu & Wen-Bo Du & Wen-Xu Wang, 2014. "Particle Swarm Optimization with Scale-Free Interactions," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    5. Jianlei Zhang & Chunyan Zhang & Tianguang Chu & Matjaž Perc, 2011. "Resolution of the Stochastic Strategy Spatial Prisoner's Dilemma by Means of Particle Swarm Optimization," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-7, July.
    6. 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.
    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. Wang, Xianjia & Lv, Shaojie, 2019. "The roles of particle swarm intelligence in the prisoner’s dilemma based on continuous and mixed strategy systems on scale-free networks," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 213-220.
    2. Tian, Yue & Gao, Shun & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2024. "Particle swarm intelligence promotes cooperation by adapting interaction radii in co-evolutionary games," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    3. Zheng, Liping & Xu, Hedong & Tian, Cunzhi & Fan, Suohai, 2021. "Evolutionary dynamics of information in the market: Transmission and trust," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    4. Lv, Shaojie & Song, Feifei, 2022. "Particle swarm intelligence and the evolution of cooperation in the spatial public goods game with punishment," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    5. Gu, Cuiling & Wang, Xianjia & Ding, Rui & Zhao, Jinhua & Liu, Yang, 2022. "Evolutionary dynamics of multi-player snowdrift games based on the Wright-Fisher process," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Wang, Jianwei & Xu, Wenshu & Zhang, Xingjian & Zhao, Nianxuan & Yu, Fengyuan, 2023. "Redistribution based on willingness to cooperate promotes cooperation while intensifying equality in heterogeneous populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    7. Wang, Xianjia & Yang, Zhipeng & Liu, Yanli & Chen, Guici, 2023. "A reinforcement learning-based strategy updating model for the cooperative evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    8. Ye, Wenxing & Fan, Suohai, 2020. "Evolutionary traveler’s dilemma game based on particle swarm optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    9. Quan, Ji & Yang, Xiukang & Wang, Xianjia, 2018. "Spatial public goods game with continuous contributions based on Particle Swarm Optimization learning and the evolution of cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 973-983.
    10. Hu, Wenjun & Zhang, Gang & Tian, Haiyan, 2019. "The stability of imitation dynamics with discrete distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 218-224.
    11. Li, Cong & Xu, Hedong & Fan, Suohai, 2021. "Evolutionary compromise game on assortative mixing networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    12. Wang, Xianjia & Chen, Wenman, 2020. "Evolutionary dynamics in spatial threshold public goods game with the asymmetric return rate mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 136(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. Chen, Ya-Shan & Yang, Han-Xin & Guo, Wen-Zhong & Liu, Geng-Geng, 2018. "Promotion of cooperation based on swarm intelligence in spatial public goods games," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 614-620.
    2. Chen, Qiao & Chen, Tong & Wang, Yongjie, 2017. "Publishing the donation list incompletely promotes the emergence of cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 48-56.
    3. Bahbouhi, Jalal Eddine & Elkouay, Abdelali & Bouderba, Saif Islam & Moussa, Najem, 2024. "The whale optimization algorithm and the evolution of cooperation in the spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    4. Wu, Yu’e & Zhang, Zhipeng & Wang, Xinyu & Chang, Shuhua, 2019. "Impact of probabilistic incentives on the evolution of cooperation in complex topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 307-314.
    5. Shuhua Chang & Xinyu Wang & Zheng Wang, 2015. "Modeling and Computation of Transboundary Industrial Pollution with Emission Permits Trading by Stochastic Differential Game," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-29, September.
    6. Qinghu Liao & Wenwen Dong & Boxin Zhao, 2023. "A New Strategy to Solve “the Tragedy of the Commons” in Sustainable Grassland Ecological Compensation: Experience from Inner Mongolia, China," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
    7. Bin Wu & Julián García & Christoph Hauert & Arne Traulsen, 2013. "Extrapolating Weak Selection in Evolutionary Games," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-7, December.
    8. 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.
    9. Egas, Martijn & Riedl, Arno, 2005. "The Economics of Altruistic Punishment and the Demise of Cooperation," IZA Discussion Papers 1646, Institute of Labor Economics (IZA).
    10. Paul Bengart & Theo Gruendler & Bodo Vogt, 2021. "Acute tryptophan depletion in healthy subjects increases preferences for negative reciprocity," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-16, March.
    11. Swami Iyer & Timothy Killingback, 2020. "Evolution of Cooperation in Social Dilemmas with Assortative Interactions," Games, MDPI, vol. 11(4), pages 1-31, September.
    12. Xiang Wei & Peng Xu & Shuiting Du & Guanghui Yan & Huayan Pei, 2021. "Reputational preference-based payoff punishment promotes cooperation in spatial social dilemmas," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 94(10), pages 1-7, October.
    13. Isamu Okada, 2020. "A Review of Theoretical Studies on Indirect Reciprocity," Games, MDPI, vol. 11(3), pages 1-17, July.
    14. Chen, Mei-huan & Wang, Li & Wang, Juan & Sun, Shi-wen & Xia, Cheng-yi, 2015. "Impact of individual response strategy on the spatial public goods game within mobile agents," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 192-202.
    15. Tu, Jing, 2018. "Contribution inequality in the spatial public goods game: Should the rich contribute more?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 9-14.
    16. Tetsushi Ohdaira & Takao Terano, 2009. "Cooperation in the Prisoner's Dilemma Game Based on the Second-Best Decision," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-7.
    17. Deng, Kuiying & Li, Zhuozheng & Kurokawa, Shun & Chu, Tianguang, 2012. "Rare but severe concerted punishment that favors cooperation," Theoretical Population Biology, Elsevier, vol. 81(4), pages 284-291.
    18. Wang, Lu & Ye, Shun-Qiang & Cheong, Kang Hao & Bao, Wei & Xie, Neng-gang, 2018. "The role of emotions in spatial prisoner’s dilemma game with voluntary participation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1396-1407.
    19. Wang, Xianjia & Lv, Shaojie, 2019. "The roles of particle swarm intelligence in the prisoner’s dilemma based on continuous and mixed strategy systems on scale-free networks," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 213-220.
    20. Haodong Niu & Keyu Li & Juan Wang, 2023. "Paid Access to Information Promotes the Emergence of Cooperation in the Spatial Prisoner’s Dilemma," Mathematics, MDPI, vol. 11(4), pages 1-15, February.

    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:482:y:2017:i:c:p:286-295. 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.