4.6 Article

Indirect reciprocity with stochastic and dual reputation updates

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PLOS COMPUTATIONAL BIOLOGY
卷 19, 期 7, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1011271

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This study extends the framework of indirect reciprocity by considering reputation updates for passive receivers and allowing for stochastic social norms. The results provide a new perspective on previous findings and can serve as a foundation for future research.
Author summaryIndirect reciprocity is a mechanism for cooperation based on social norms. The respective field explores which norms are stable, and how changes in a social norm affect a population's cooperation rate. Here, we generalize a classical framework of indirect reciprocity in two ways. First, we allow for norms in which also the reputations of passive receivers are updated. Second, we allow social norms to have a stochastic component. We use this general framework to characterize all cooperative norms that are evolutionarily stable. Our results provide a new perspective for understanding previous findings, and they can serve as a foundation for future studies in this area. Cooperation is a crucial aspect of social life, yet understanding the nature of cooperation and how it can be promoted is an ongoing challenge. One mechanism for cooperation is indirect reciprocity. According to this mechanism, individuals cooperate to maintain a good reputation. This idea is embodied in a set of social norms called the leading eight. When all information is publicly available, these norms have two major properties. Populations that employ these norms are fully cooperative, and they are stable against invasion by alternative norms. In this paper, we extend the framework of the leading eight in two directions. First, we include norms with 'dual' reputation updates. These norms do not only assign new reputations to an acting donor; they also allow to update the reputation of the passive recipient. Second, we allow social norms to be stochastic. Such norms allow individuals to evaluate others with certain probabilities. Using this framework, we characterize all evolutionarily stable norms that lead to full cooperation in the public information regime. When only the donor's reputation is updated, and all updates are deterministic, we recover the conventional model. In that case, we find two classes of stable norms: the leading eight and the 'secondary sixteen'. Stochasticity can further help to stabilize cooperation when the benefit of cooperation is comparably small. Moreover, updating the recipients' reputations can help populations to recover more quickly from errors. Overall, our study highlights a remarkable trade-off between the evolutionary stability of a norm and its robustness with respect to errors. Norms that correct errors quickly require higher benefits of cooperation to be stable.

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