IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v355y2019icp213-220.html
   My bibliography  Save this article

The roles of particle swarm intelligence in the prisoner’s dilemma based on continuous and mixed strategy systems on scale-free networks

Author

Listed:
  • Wang, Xianjia
  • Lv, Shaojie

Abstract

Understanding and explaining the widespread emergence of cooperation in social dilemmas remains a great challenge. Previous researches have shown that complex networks with high heterogeneity especially scale-free networks can remarkably facilitate cooperation in the case of accumulated payoff, but fail in the case of average payoff. In this paper, we investigate the role of particle swarm optimization (PSO) strategy update rules in the evolution of cooperation in the prisoner’s dilemma (PD) on scale-free networks, when each player obtains the average payoff normalized with its degree. In the meantime, considering whether goods and resources are divisible, PSO strategy update rules based on continuous and mixed strategy systems are proposed respectively. The simulation results show that the PSO strategy update rules can promote cooperation in the continuous strategy system, but lead to the severe collapse of cooperation in the mixed strategy system. The nodes with low or medium degree play an important role to facilitate cooperative behaviors.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:apmaco:v:355:y:2019:i:c:p:213-220
    DOI: 10.1016/j.amc.2019.02.048
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319301523
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.02.048?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. 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.
    2. Vincent A. A. Jansen & Minus van Baalen, 2006. "Altruism through beard chromodynamics," Nature, Nature, vol. 440(7084), pages 663-666, March.
    3. 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.
    4. Gabrielle Demange & Ahmet Alkan & David Gale, 1991. "Fair Allocation of Indivisible Goods and Money and Criteria of Justice," Post-Print halshs-00670945, HAL.
    5. Zhou, Tianwei & Ding, Shuai & Fan, Wenjuan & Wang, Hao, 2016. "An improved public goods game model with reputation effect on the spatial lattices," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 130-135.
    6. 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.
    7. Josephson, Jens, 2008. "A numerical analysis of the evolutionary stability of learning rules," Journal of Economic Dynamics and Control, Elsevier, vol. 32(5), pages 1569-1599, May.
    8. 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.
    9. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    10. 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.
    11. Andrew M. Colman, 2006. "The puzzle of cooperation," Nature, Nature, vol. 440(7085), pages 744-745, April.
    12. 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.
    13. 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.
    14. 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.
    15. Alkan, Ahmet & Demange, Gabrielle & Gale, David, 1991. "Fair Allocation of Indivisible Goods and Criteria of Justice," Econometrica, Econometric Society, vol. 59(4), pages 1023-1039, July.
    16. Yang, Han-Xin & Rong, Zhihai, 2015. "Mutual punishment promotes cooperation in the spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 230-234.
    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. Gu, Cuiling & Wang, Xianjia & Zhao, Jinhua & Ding, Rui & He, Qilong, 2020. "Evolutionary game dynamics of Moran process with fuzzy payoffs and its application," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    2. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The interplay of behaviors and attitudes in public goods game considering environmental investment," Applied Mathematics and Computation, Elsevier, vol. 382(C).
    3. 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).
    4. Chen, Wei & Wang, Jianwei & Yu, Fengyuan & He, Jialu & Xu, Wenshu & Wang, Rong, 2021. "Effects of emotion on the evolution of cooperation in a spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    5. 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).
    6. Ji, Kaipeng & Zhao, Peng & Zhou, Xiaowei & Chen, Yuhong & Dong, Zhengyang & Zheng, Jianguo & Fu, Jianzhong & Zhou, Huamin, 2022. "Uniform Initialization in Response Space for PSO and its Applications," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    7. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2022. "Hybrid learning promotes cooperation in the spatial prisoner’s dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    8. 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).
    9. Xie, Yunya & Bai, Yu & Zhang, Yankun & Peng, Zhengyin, 2024. "Trust-induced cooperation under the complex interaction of networks and emotions," Chaos, Solitons & Fractals, Elsevier, vol. 182(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. 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).
    2. 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).
    3. 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).
    4. 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.
    5. 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).
    6. 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).
    7. 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).
    8. 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).
    9. Quan, Ji & Tang, Caixia & Zhou, Yawen & Wang, Xianjia & Yang, Jian-Bo, 2020. "Reputation evaluation with tolerance and reputation-dependent imitation on cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    10. Rodrigo A. Velez, 2022. "A polynomial algorithm for maxmin and minmax envy-free rent division on a soft budget," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 59(1), pages 93-118, July.
    11. Quan, Ji & Tang, Caixia & Wang, Xianjia, 2021. "Reputation-based discount effect in imitation on the evolution of cooperation in spatial public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    12. Dall’Aglio, Marco, 2023. "Fair division of goods in the shadow of market values," European Journal of Operational Research, Elsevier, vol. 307(2), pages 785-801.
    13. Francisco Sánchez Sánchez, 2022. "Envy-Free Solutions to the Problem of Room Assignment and Rent Division," Group Decision and Negotiation, Springer, vol. 31(3), pages 703-721, June.
    14. Andersson, Tommy & Andersson, Christer & Talman, Adolphus Johannes Jan, 2010. "Sets in Excess Demand in Ascending Auctions with Unit-Demand Bidders," Working Papers 2010:15, Lund University, Department of Economics, revised 28 Jun 2012.
    15. T. Andersson & C. Andersson & A. Talman, 2013. "Sets in excess demand in simple ascending auctions with unit-demand bidders," Annals of Operations Research, Springer, vol. 211(1), pages 27-36, December.
    16. Quan, Ji & Zhou, Yawen & Wang, Xianjia & Yang, Jian-Bo, 2020. "Information fusion based on reputation and payoff promotes cooperation in spatial public goods game," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    17. Tierney, Ryan, 2019. "The problem of multiple commons: A market design approach," Games and Economic Behavior, Elsevier, vol. 114(C), pages 1-27.
    18. 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.
    19. Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
    20. Hanaki, Nobuyuki & Ishikawa, Ryuichiro & Akiyama, Eizo, 2009. "Learning games," Journal of Economic Dynamics and Control, Elsevier, vol. 33(10), pages 1739-1756, October.

    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:apmaco:v:355:y:2019:i:c:p:213-220. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.