IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v382y2020ics0096300320303192.html
   My bibliography  Save this article

Frequency-dependent strategy selection in a hunting game with a finite population

Author

Listed:
  • Zhang, Shuai
  • Clark, Ruaridh
  • Huang, Yunke

Abstract

This paper considers a hunting game in the “playing the field” model, in which an individual within a group has to choose from two survival strategies: the group hunting strategy or the individual hunting strategy. The group hunting strategy aims at hunting more dangerous, larger prey, that are far beyond a single individual’s capture ability, where the return is greater but the risk is higher. While the individual hunting strategy aims at hunting small prey that can be easily captured by an independent individual, where the return is less but the risk is lower. Evolutionary game theory is used to investigate the selection dynamics of a two-strategy game with a finite population. This reveals the existences of the stable/unstable equilibrium points and evolutionarily stable strategies when there is the frequency-dependent strategy selection in the hunting game. The evolutionarily stable state is found to be not always unique because the system of the hunting game can have multiple equilibrium points. It is shown that a stable equilibrium point will always act as an evolutionarily stable strategy, while an unstable equilibrium point cannot resist invasion from a mutation. The population fitness cannot always reach the optimum level when applying the evolutionary process with the fitness difference function.

Suggested Citation

  • Zhang, Shuai & Clark, Ruaridh & Huang, Yunke, 2020. "Frequency-dependent strategy selection in a hunting game with a finite population," Applied Mathematics and Computation, Elsevier, vol. 382(C).
  • Handle: RePEc:eee:apmaco:v:382:y:2020:i:c:s0096300320303192
    DOI: 10.1016/j.amc.2020.125355
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300320303192
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2020.125355?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. Liu, Chen & Shi, Juan & Li, Tong & Liu, Jinzhuo, 2019. "Aspiration driven coevolution resolves social dilemmas in networks," Applied Mathematics and Computation, Elsevier, vol. 342(C), pages 247-254.
    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. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    4. Jeff Gore & Hyun Youk & Alexander van Oudenaarden, 2009. "Snowdrift game dynamics and facultative cheating in yeast," Nature, Nature, vol. 459(7244), pages 253-256, May.
    5. 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).
    6. Deng, Wenfeng & Huang, Keke & Yang, Chunhua & Zhu, Hongqiu & Yu, Zhaofei, 2018. "Promote of cooperation in networked multiagent system based on fitness control," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 805-811.
    7. Liu, Run-Ran & Jia, Chun-Xiao & Rong, Zhihai, 2019. "Effects of enhancement level on evolutionary public goods game with payoff aspirations," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 242-248.
    8. Shpak, Max & Orzack, Steven Hecht & Barany, Ernest, 2013. "The influence of demographic stochasticity on evolutionary dynamics and stability," Theoretical Population Biology, Elsevier, vol. 88(C), pages 47-56.
    9. Martin A. Nowak & Akira Sasaki & Christine Taylor & Drew Fudenberg, 2004. "Emergence of cooperation and evolutionary stability in finite populations," Nature, Nature, vol. 428(6983), pages 646-650, April.
    10. Bandyopadhyay, Abhirup & Kar, Samarjit, 2018. "Coevolution of cooperation and network structure in social dilemmas in evolutionary dynamic complex network," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 710-730.
    11. Du, Jinming, 2019. "Redistribution promotes cooperation in spatial public goods games under aspiration dynamics," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    12. Gao, Bo & liu, Xuan & Hou, Shuxia & Jia, Danyang & Du, Mingjing, 2019. "Resolving public goods dilemma by giving the poor more support," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    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. Yuan, Hairui & Meng, Xinzhu, 2022. "Replicator dynamics of division of labor games with delayed payoffs in infinite populations," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    2. Yuan, Hairui & Meng, Xinzhu, 2022. "Replicator dynamics of the Hawk-Dove game with different stochastic noises in infinite populations," Applied Mathematics and Computation, Elsevier, vol. 430(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. 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).
    2. Wang, Mie & Kang, HongWei & Shen, Yong & Sun, XingPing & Chen, QingYi, 2021. "The role of alliance cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    3. Brian McLoone & Wai-Tong Louis Fan & Adam Pham & Rory Smead & Laurence Loewe, 2018. "Stochasticity, Selection, and the Evolution of Cooperation in a Two-Level Moran Model of the Snowdrift Game," Complexity, Hindawi, vol. 2018, pages 1-14, February.
    4. 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).
    5. Qi Su & Lei Zhou & Long Wang, 2019. "Evolutionary multiplayer games on graphs with edge diversity," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-22, April.
    6. Quan, Ji & Zhang, Xiyue & Chen, Wenman & Tang, Caixia & Wang, Xianjia, 2024. "Reputation-dependent social learning on the evolution of cooperation in spatial public goods games," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    7. Zhang, Mingzhen & Yang, Naiding & Zhu, Xianglin & Wang, Yan, 2022. "The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    8. Yang, Luhe & Zhang, Lianzhong & Yang, Duoxing, 2022. "Asymmetric micro-dynamics in spatial anonymous public goods game," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    9. Wang, Si-Yi & Liu, Yan-Ping & Zhang, Feng & Wang, Rui-Wu, 2021. "Super-rational aspiration induced strategy updating promotes cooperation in the asymmetric prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    10. Gao, Liyan & Pan, Qiuhui & He, Mingfeng, 2020. "Changeable updating rule promotes cooperation in well-mixed and structured populations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    11. 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.
    12. 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.
    13. Huang, Keke & Liu, Yishun & Zhang, Yichi & Yang, Chunhua & Wang, Zhen, 2018. "Understanding cooperative behavior of agents with heterogeneous perceptions in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 234-240.
    14. 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.
    15. Dimitris Iliopoulos & Arend Hintze & Christoph Adami, 2010. "Critical Dynamics in the Evolution of Stochastic Strategies for the Iterated Prisoner's Dilemma," PLOS Computational Biology, Public Library of Science, vol. 6(10), pages 1-8, October.
    16. Cheng, Fei & Chen, Tong & Chen, Qiao, 2020. "Rewards based on public loyalty program promote cooperation in public goods game," Applied Mathematics and Computation, Elsevier, vol. 378(C).
    17. 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).
    18. Wang, Jianwei & Xu, Wenshu & Yu, Fengyuan & He, Jialu & Chen, Wei & Dai, Wenhui, 2024. "Evolution of cooperation under corrupt institutions," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    19. 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).
    20. Hong, Lijun & Geng, Yini & Du, Chunpeng & Shen, Chen & Shi, Lei, 2021. "Average payoff-driven or imitation? A new evidence from evolutionary game theory in finite populations," Applied Mathematics and Computation, Elsevier, vol. 394(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:382:y:2020:i:c:s0096300320303192. 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.