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Replicator dynamics of the Hawk-Dove game with different stochastic noises in infinite populations

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  • Yuan, Hairui
  • Meng, Xinzhu

Abstract

This paper investigates the dynamic system of the Hawk-Dove game with deterministic and stochastic interference and considers the two-player game and N-player game, respectively. First, we introduce the replicator dynamics equations of the Hawk-Dove game for the two-player and N-player cases and prove the stability of the unique equilibrium point. When the system reaches a stable state, we find that the frequency of individuals adopting D-strategy depends upon the number of players. As the number of players increases, the frequency of D-strategy increases. Second, we ponder two forms of stochastic noise, additive noise and multiplicative noise, and use the potential function method to prove the stochastic stability of equilibria of the two-player and N-player game systems respectively. The additive noise causes the frequency of players who use D-strategy to oscillate at the stochastically stable equilibrium. Then, we use Itô’s formula and the strong law of large numbers to prove that the frequency of D-strategy is almost surely exponentially stable (ASES) and persistent. We obtain a threshold value for multiplicative noise, when the multiplicative noise value is greater than the threshold value, the frequency of D-strategy x=0 is ASES. Conversely, when the multiplicative noise value is less than the threshold value, the frequency of D-strategy is persistent. The results show that noise interference has an important effect on the replicator dynamics of Hawk-Dove game, this improves the study of game dynamics without noise. Finally, numerical simulations are used to show our theoretical results.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003460
    DOI: 10.1016/j.amc.2022.127272
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    1. Liu, Qun & Jiang, Daqing, 2019. "Dynamical behavior of a stochastic multigroup SIR epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    2. Deng, Zheng-Hong & Wang, Zi-Ren & Wang, Huan-Bo & Huang, Yijie, 2021. "Impact of informers on the evolution of cooperation in prisoner's dilemma game," Chaos, Solitons & Fractals, Elsevier, vol. 149(C).
    3. Erez Lieberman & Christoph Hauert & Martin A. Nowak, 2005. "Evolutionary dynamics on graphs," Nature, Nature, vol. 433(7023), pages 312-316, January.
    4. Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, December.
    5. Kang, Bingyi & Chhipi-Shrestha, Gyan & Deng, Yong & Hewage, Kasun & Sadiq, Rehan, 2018. "Stable strategies analysis based on the utility of Z-number in the evolutionary games," Applied Mathematics and Computation, Elsevier, vol. 324(C), pages 202-217.
    6. Marco Alberto Javarone, 2016. "Statistical physics of the spatial Prisoner’s Dilemma with memory-aware agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-6, February.
    7. Marco Alberto Javarone, 2016. "Statistical physics of the spatial Prisoner’s Dilemma with memory-aware agents," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-6, February.
    8. Wang, Lei & Xia, Chengyi & Wang, Li & Zhang, Ying, 2013. "An evolving Stag-Hunt game with elimination and reproduction on regular lattices," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 69-76.
    9. Zhang, W. & Li, Y.S. & Xu, C. & Hui, P.M., 2016. "Cooperative behavior and phase transitions in co-evolving stag hunt game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 161-169.
    10. Lahkar, Ratul & Mukherjee, Saptarshi, 2019. "Evolutionary implementation in a public goods game," Journal of Economic Theory, Elsevier, vol. 181(C), pages 423-460.
    11. repec:hhs:iuiwop:487 is not listed on IDEAS
    12. 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).
    13. Usui, Yuki & Ueda, Masahiko, 2021. "Symmetric equilibrium of multi-agent reinforcement learning in repeated prisoner’s dilemma," Applied Mathematics and Computation, Elsevier, vol. 409(C).
    14. 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).
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    1. Ma, Yuanlin & Yu, Xingwang, 2023. "Impact of correlated Gaussian colored noises on stability and stationary probability density for the randomly forced two-species competitive Gompertz model," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).

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