IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v361y2019icp661-669.html
   My bibliography  Save this article

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

Author

Listed:
  • Nagashima, Keisuke
  • Tanimoto, Jun

Abstract

In a 2 × 2 prisoner's dilemma (PD) game, network reciprocity is one of the mechanisms for increasing social viscosity, which leads to a cooperative equilibrium. The Pairwise Fermi (PW-Fermi) rule has been accepted as an updating protocol, as its stochasticity is similar to the real-world human decision-making process. In this paper, we elucidated a modification to the PW-Fermi rule by utilizing the averaged payoff difference instead of the simple payoff difference between a focal agent and their neighbors. This led to a significantly enhanced level of network reciprocity. The mechanism of this enhancement is clarified by discussing the concepts of the enduring period (END) and the expanding period (EXP).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:apmaco:v:361:y:2019:i:c:p:661-669
    DOI: 10.1016/j.amc.2019.05.034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319304369
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2019.05.034?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. Zhen Wang & Marko Jusup & Lei Shi & Joung-Hun Lee & Yoh Iwasa & Stefano Boccaletti, 2018. "Exploiting a cognitive bias promotes cooperation in social dilemma experiments," Nature Communications, Nature, vol. 9(1), pages 1-7, December.
    2. 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.
    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. Xu, Zhixiong & Xu, Zhehang & Zhang, Wei & Han, Xiao-Pu & Meng, Fanyuan, 2024. "Memory-based spatial evolutionary prisoner’s dilemma," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    2. 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).
    3. Deng, Lili & Zhang, Xingxing & Wang, Cheng, 2021. "Coevolution of spatial ultimatum game and link weight promotes fairness," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    4. Han, Xu & Xia, Haoxiang & Zhao, Xiaowei, 2024. "Memory–based adaptive interaction willingness enhances cooperation in spatial prisoner's dilemma," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    5. 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).
    6. Quan, Ji & Yu, Junyu & Li, Xia & Wang, Xianjia, 2023. "Conditional switching between social excluders and loners promotes cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    7. 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).
    8. 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).
    9. 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).
    10. Zhang, Zhipeng & Wu, Yu’e & Zhang, Shuhua, 2022. "Reputation-based asymmetric comparison of fitness promotes cooperation on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    11. Li, Cong & Xu, Hedong & Fan, Suohai, 2021. "Evolutionary compromise game on assortative mixing networks," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    12. 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).
    13. 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).
    14. Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2022. "Adaptive persistence based on environment comparison enhances cooperation in evolutionary games," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    15. Han, Xu & Zhao, Xiaowei & Xia, Haoxiang, 2021. "Evolution of cooperation through aspiration-based adjustment of interaction range in spatial prisoner’s dilemma game," Applied Mathematics and Computation, Elsevier, vol. 393(C).
    16. Geng, Yini & Liu, Yifan & Lu, Yikang & Shen, Chen & Shi, Lei, 2022. "Reinforcement learning explains various conditional cooperation," Applied Mathematics and Computation, Elsevier, vol. 427(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. 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).
    2. Yang, Xuenan & Peng, Yu & Xiao, Yue & Wu, Xue, 2019. "Nonlinear dynamics of a duopoly Stackelberg game with marginal costs," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 185-191.
    3. Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.
    4. Wang, Qiuling & Du, Chunpeng, 2019. "Impact of expansion of priority range on cooperation in the prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 129(C), pages 77-80.
    5. Gao, Lei & Li, Yaotang & Wang, Zhen & Wang, Rui-Wu, 2022. "Asymmetric strategy setup solve the Prisoner’s Dilemma of the evolution of mutualism," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    6. Ahsan Habib, Md. & Tanaka, Masaki & Tanimoto, Jun, 2020. "How does conformity promote the enhancement of cooperation in the network reciprocity in spatial prisoner's dilemma games?," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    7. Utsumi, Shinobu & Tatsukawa, Yuichi & Tanimoto, Jun, 2022. "Does a resource-storing mechanism favor “the wealthy do not fight”?—An approach from evolutionary game theory," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    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. Dehghani, Sedigheh & Nazarimehr, Fahimeh & Jafari, Sajad, 2021. "How can cultural conditions affect society’s decisions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    10. 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).
    11. Cheng, Yuan & Xue, Yanbo & Chang, Meng, 2020. "Career choice as an extended spatial evolutionary public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    12. Iwamura, Yoshiro & Nagashima, Keisuke & Tanimoto, Jun, 2020. "Evolutionary dynamics of a 3-strategy game: Cooperator, defector and costly cooperative loner strategic types," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    13. Ueda, Masahiko, 2020. "Common knowledge equilibrium of Boolean securities in distributed information market," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    14. Sun, Peng & Zhang, Jun, 2020. "Group decision under uncertain information," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).
    15. Yang, Han-Xin & Yang, Jing, 2019. "Reputation-based investment strategy promotes cooperation in public goods games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 886-893.
    16. Gao, Hongyu & Wang, Juan & Zhang, Fan & Li, Xiaopeng & Xia, Chengyi, 2021. "Cooperation dynamics based on reputation in the mixed population with two species of strategists," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    17. Li, Bin-Quan & Wu, Zhi-Xi & Guan, Jian-Yue, 2022. "Critical thresholds of benefit distribution in an extended snowdrift game model," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    18. Wu, Yu’e & Zhang, Zhipeng & Wang, Xinyu & Yan, Ming & Zhang, Qingfeng & Zhang, Shuhua, 2021. "Evolution of cooperation in the multigame on a two-layer square network," Applied Mathematics and Computation, Elsevier, vol. 400(C).
    19. Feng, Meiling & Li, Xuezhu & Zhao, Dawei & Xia, Chengyi, 2023. "Evolutionary dynamics with the second-order reputation in the networked N-player trust game," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    20. Guan, Junbiao & Wang, Kaihua, 2020. "Cooperative evolution in pedestrian room evacuation considering different individual behaviors," Applied Mathematics and Computation, Elsevier, vol. 369(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:361:y:2019:i:c:p:661-669. 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.