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Aspiration-driven strategy evolutionary dynamics under strong selection

  • Regular Article - Statistical and Nonlinear Physics
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A Publisher Correction to this article was published on 13 September 2022

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Abstract

Strategy update rules based on self-evaluation are very common in practice. Most of the previous studies on the update of aspiration-based self-evaluation strategies were based on the assumption that people’s adjustment intensity was low. Whether the successful propagation of human behavioral traits falls within this parameter is unclear. Therefore, it will be necessary to derive analytical results applicable to any selected intensity. In this paper, we focus on the effect of selection intensity on the level of population cooperation, and mainly focus on strong selection. We derive the results of the analysis for any selection intensity. The results show that under the condition of strong selection intensity, the evolution of cooperative strategy is strongly driven by aspiration, and significantly increase the cooperative strategy proportion compared with the results under weak selection. In addition, there is a critical cost-benefit ratio, which makes the proportion of cooperative strategy decrease sharply. The critical cost-benefit ratio decreases as the value of aspiration increase. However, when the selection intensity was weak, the aspiration value has a little effect on the proportion of cooperative strategies. We also reveal, essentially, the cause of the effect of aspiration value on the proportion of cooperative strategies at stable equilibrium time is the effect of aspiration value on the probability of strategy update under different configurations. In addition, the theoretical results are verified by Monte Carlo numerical simulation and the results are qualitatively consistent for different system sizes and structures. The apparent difference in the level of cooperation between strong and weak selection will be crucial to our basic understanding of human behavior and may lead to new insights into human self-evaluation.

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Data Availability Statement

This manuscript has no associated data or the data will not be deposited. [Authors’ comment: The original data of this study are available from the corresponding author upon reasonable request.]

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Acknowledgements

The authors acknowledge financial support from the National Natural Science Foundation of China (Grants nos. 11475074, 11975111 and 12047501) and the Fundamental Research Funds for the Central Universities (lzujbky-2019-85).

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Authors and Affiliations

  1. Lanzhou Center for Theoretical Physics and Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou University, Lanzhou, 730000, Gansu, China

    Bin-Quan Li & Jian-Yue Guan

Authors
  1. Bin-Quan Li
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  2. Jian-Yue Guan
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Contributions

B.-Q. Li discusses ideas with J.-Y. Guan. B.-Q. Li completes the numerical simulation and theoretical calculation. B.-Q. Li wrote the manuscript. The manuscript was revised by J.-Y. Guan.

Corresponding author

Correspondence to Bin-Quan Li.

Additional information

The original online version of this article was revised: The article included an incorrect Open Access licence text which was removed.

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Li, BQ., Guan, JY. Aspiration-driven strategy evolutionary dynamics under strong selection. Eur. Phys. J. B 95, 90 (2022). https://doi.org/10.1140/epjb/s10051-022-00356-3

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