IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v390y2021ics0096300320306342.html
   My bibliography  Save this article

Evolutionary compromise game on assortative mixing networks

Author

Listed:
  • Li, Cong
  • Xu, Hedong
  • Fan, Suohai

Abstract

Different from the cooperative game, in reality, heterogeneous individuals who choose to cooperate usually need to make a consistent strategic decision instead of directly entering the process of dividing payoffs. During the process of making consensus decisions, subjective psychology is a key factor affecting the final result, especially when individuals have similar abilities. Considering the subjective attitudes and objective abilities, this paper proposes a compromise game to model the dynamic change of subjective compromise value of individuals, which is a kind of psychological game. Here, the compromise value represented by parameter α is the strategy in game, which ranges from 0 to 1. And in terms of the continuous nature of compromise value α, we use particle swarm optimization to update strategies. Moreover, the subjective attitudes are profoundly affected by social surroundings, and thus we simulate this model on diverse assortative mixing networks by regulating the assortativity coefficient r. Simulations show that the compromise value of individuals gradually decreases as the assortativity of networks increases, and the compromise values of high-degree individuals are much higher than that of low-degree individuals in networks. Through the simulation results, we find that the subjective compromise of individual is greatly relevant with environment, which is important for the development of individuals. When meeting the individuals who have the similar ability, individuals from disassortative network tend to persist himself compared with individuals from assortative networks.

Suggested Citation

  • Li, Cong & Xu, Hedong & Fan, Suohai, 2021. "Evolutionary compromise game on assortative mixing networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
  • Handle: RePEc:eee:apmaco:v:390:y:2021:i:c:s0096300320306342
    DOI: 10.1016/j.amc.2020.125681
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320306342
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2020.125681?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. Tanimoto, Jun, 2010. "The effect of assortativity by degree on emerging cooperation in a 2×2 dilemma game played on an evolutionary network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3325-3335.
    2. Alam, Muntasir & Kuga, Kazuki & Tanimoto, Jun, 2019. "Three-strategy and four-strategy model of vaccination game introducing an intermediate protecting measure," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 408-422.
    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. F. Débarre & C. Hauert & M. Doebeli, 2014. "Social evolution in structured populations," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
    5. Xu, Hedong & Tian, Cunzhi & Xiao, Xinrong & Fan, Suohai, 2018. "Evolutionary investors’ power-based game on networks," Applied Mathematics and Computation, Elsevier, vol. 330(C), pages 125-133.
    6. Wu, Yu’e & Zhang, Zhipeng & Chang, Shuhua, 2019. "Reciprocal reward promotes the evolution of cooperation in structured populations," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 230-236.
    7. Rong-Hua Li & Jeffrey Xu Yu & Jiyuan Lin, 2013. "Evolution of Cooperation in Spatial Traveler's Dilemma Game," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-11, March.
    8. Xu, Hedong & Fan, Suohai & Tian, Cunzhi & Xiao, Xinrong, 2019. "Evolutionary investor sharing game on networks," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 138-145.
    9. 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.
    10. Alam, Muntasir & Tanaka, Masaki & Tanimoto, Jun, 2019. "A game theoretic approach to discuss the positive secondary effect of vaccination scheme in an infinite and well-mixed population," Chaos, Solitons & Fractals, Elsevier, vol. 125(C), pages 201-213.
    11. Xiaojie Chen & Attila Szolnoki, 2018. "Punishment and inspection for governing the commons in a feedback-evolving game," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-15, July.
    12. Wang, Xu-Wen & Nie, Sen & Jiang, Luo-Luo & Wang, Bing-Hong & Chen, Shi-Ming, 2017. "Role of delay-based reward in the spatial cooperation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 153-158.
    13. 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).
    14. Alam, Muntasir & Nagashima, Keisuke & Tanimoto, Jun, 2018. "Various error settings bring different noise-driven effects on network reciprocity in spatial prisoner's dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 338-346.
    15. Nagashima, Keisuke & Tanimoto, Jun, 2019. "A stochastic Pairwise Fermi rule modified by utilizing the average in payoff differences of neighbors leads to increased network reciprocity in spatial prisoner's dilemma games," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 661-669.
    16. 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.
    17. Basu, Kaushik, 1994. "The Traveler's Dilemma: Paradoxes of Rationality in Game Theory," American Economic Review, American Economic Association, vol. 84(2), pages 391-395, May.
    18. Li, Cong & Xu, Hedong & Fan, Suohai, 2020. "Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    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. 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).

    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. 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).
    2. Li, Cong & Xu, Hedong & Fan, Suohai, 2020. "Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game," Applied Mathematics and Computation, Elsevier, vol. 370(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. Shi, Juan & Hu, Die & Tao, Rui & Peng, Yunchen & Li, Yong & Liu, Jinzhuo, 2021. "Interaction between populations promotes cooperation in voluntary prisoner's dilemma," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    5. Wang, Jianwei & Wang, Rong & Yu, Fengyuan & Wang, Ziwei & Li, Qiaochu, 2020. "Learning continuous and consistent strategy promotes cooperation in prisoner’s dilemma game with mixed strategy," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    6. Kulsum, Umma & Alam, Muntasir & Kamrujjaman, Md., 2024. "Modeling and investigating the dilemma of early and delayed vaccination driven by the dynamics of imitation and aspiration," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    7. 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.
    8. Song, Qun & Cao, Zhaoheng & Tao, Rui & Jiang, Wei & Liu, Chen & Liu, Jinzhuo, 2020. "Conditional neutral punishment promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 368(C).
    9. Li, Wen-Jing & Jiang, Luo-Luo & Perc, Matjaž, 2021. "A limited mobility of minorities facilitates cooperation in social dilemmas," Applied Mathematics and Computation, Elsevier, vol. 391(C).
    10. You, Tao & Wang, Peng & Jia, Danyang & Yang, Fei & Cui, Xiaodong & Liu, Chen, 2020. "The effects of heterogeneity of updating rules on cooperation in spatial network," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    11. Zhu, Peican & Wang, Xiaoyu & Jia, Danyang & Guo, Yangming & Li, Shudong & Chu, Chen, 2020. "Investigating the co-evolution of node reputation and edge-strategy in prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    12. Quan, Ji & Yang, Wenjun & Li, Xia & Wang, Xianjia & Yang, Jian-Bo, 2020. "Social exclusion with dynamic cost on the evolution of cooperation in spatial public goods games," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    13. Yunsheng Deng & Jihui Zhang, 2022. "The choice-decision based on memory and payoff favors cooperation in stag hunt game on interdependent networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(2), pages 1-13, February.
    14. 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).
    15. 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.
    16. 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).
    17. Benjamin Allen & Christine Sample & Robert Jencks & James Withers & Patricia Steinhagen & Lori Brizuela & Joshua Kolodny & Darren Parke & Gabor Lippner & Yulia A Dementieva, 2020. "Transient amplifiers of selection and reducers of fixation for death-Birth updating on graphs," PLOS Computational Biology, Public Library of Science, vol. 16(1), pages 1-20, January.
    18. Huang, Shaoxu & Liu, Xuesong & Hu, Yuhan & Fu, Xiao, 2023. "The influence of aggressive behavior on cooperation evolution in social dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    19. Fulin Guo, 2023. "Experience-weighted attraction learning in network coordination games," Papers 2310.18835, arXiv.org.
    20. 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).

    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:390:y:2021:i:c:s0096300320306342. 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.