{"title":"Environmental-feedback-driven time-varying reputation update solve social dilemmas","authors":"Yang Wang , Shounan Lu","doi":"10.1016/j.amc.2025.129562","DOIUrl":null,"url":null,"abstract":"<div><div>The reputation mechanism serves as a critical component in sustaining the efficient functioning of social systems. Building upon existing research, this study introduces a novel time-varying reputation update rule that incorporates environmental feedback. Specifically, we establish that the reputation reward for cooperation follows a positive yet non-linear relationship with the proportion of cooperators, while the reputation penalty for defection exhibits a negative but equally non-linear correlation with the cooperator ratio. Our research yields two significant contributions: First, our findings reveal two key insights: The proposed mechanism significantly enhances cooperative behavior compared to traditional version, demonstrating superior performance in improving network reciprocity utility, and compared to homogeneous reputation, time-varying reputation update perform better in enhancing cooperation under low social dilemma. Second, we extend this framework by developing three additional time-varying reputation update rules that incorporate environmental feedback. Comparative analysis demonstrates that different reputation mechanisms exhibit varying levels of effectiveness in promoting cooperation under different intensities of social dilemmas. The reward conditions during the initial cooperative evolution will influence the spread of cooperative behavior in future systems. These findings not only deepen our theoretical understanding of reputation dynamics but also provide insights for designing context-specific reputation systems.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":"507 ","pages":"Article 129562"},"PeriodicalIF":3.4000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Computation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0096300325002887","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The reputation mechanism serves as a critical component in sustaining the efficient functioning of social systems. Building upon existing research, this study introduces a novel time-varying reputation update rule that incorporates environmental feedback. Specifically, we establish that the reputation reward for cooperation follows a positive yet non-linear relationship with the proportion of cooperators, while the reputation penalty for defection exhibits a negative but equally non-linear correlation with the cooperator ratio. Our research yields two significant contributions: First, our findings reveal two key insights: The proposed mechanism significantly enhances cooperative behavior compared to traditional version, demonstrating superior performance in improving network reciprocity utility, and compared to homogeneous reputation, time-varying reputation update perform better in enhancing cooperation under low social dilemma. Second, we extend this framework by developing three additional time-varying reputation update rules that incorporate environmental feedback. Comparative analysis demonstrates that different reputation mechanisms exhibit varying levels of effectiveness in promoting cooperation under different intensities of social dilemmas. The reward conditions during the initial cooperative evolution will influence the spread of cooperative behavior in future systems. These findings not only deepen our theoretical understanding of reputation dynamics but also provide insights for designing context-specific reputation systems.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.