The impact of reputation-based heterogeneous evaluation and learning on cooperation in spatial public goods game

Ran Lv, Jia-Li Qian, Qing-Yi Hao, Chao-Yun Wu, Ning Guo and Xiang Ling

Chaos, Solitons & Fractals, 2024, vol. 181, issue C

Abstract: In general, individuals with high reputation are more likely to be noticed. Moreover, the society also has different evaluation tendencies towards the positive or negative behaviors of high-reputation individuals. Motivated by this reality, this paper develops spatial public goods game model from three perspectives, which involve a dynamic reputation threshold based on local reputation and global reputation, heterogeneous evaluation of individual reputation, reputation-based method for selecting the target neighbor for strategy learning. Numerical experiments indicate highly positive evaluation on the cooperation strategy of individuals with high reputation always favors cooperation. And highly negative evaluation of the defection strategy of individuals with high reputation can promote cooperation under strong dilemma, while leniently negative evaluation of the defection strategy of individuals with high reputation is conducive to cooperation under weak dilemma. For different tendencies in reputation evaluation, the learning mechanism that individuals preferentially select individuals with high reputation as strategy learning objects is beneficial for promoting cooperative behavior of the system. In the strong dilemma environment, the proportion of attention to local average reputation and global average reputation has different effects on the cooperative behavior of the system under different evaluation tendencies for high reputation individuals.

Keywords: Spatial public goods game; Cooperative behavior; Heterogeneity; Reputation (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002200

DOI: 10.1016/j.chaos.2024.114668

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