{"title":"Social norms and cooperation in a collective-risk social dilemma: comparing reinforcing learning and norm-based approaches","authors":"N. Payette, Áron Székely, G. Andrighetto","doi":"10.1109/RO-MAN47096.2020.9223561","DOIUrl":null,"url":null,"abstract":"Human cooperation is both powerful and puzzling. Large-scale cooperation among genetically unrelated individuals makes humans unique with respect to all other animal species. Therefore, learning how cooperation emerges and persists is a key question for social scientists. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking.We present here a version of the Experience-Weighted Attraction (EWA) reinforcement learning model that integrates norm-based considerations into its utility function that we call EWA+Norms. We compare the behaviour of this hybrid model to the standard EWA when applied to a collective risk social dilemma in which groups of individuals must reach a threshold level of cooperation to avoid the risk of catastrophe. We find that standard EWA is not sufficient for generating cooperation, but that EWA+Norms is. Next step is to compare simulation results with human behaviour in large-scale experiments.","PeriodicalId":383722,"journal":{"name":"2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RO-MAN47096.2020.9223561","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Human cooperation is both powerful and puzzling. Large-scale cooperation among genetically unrelated individuals makes humans unique with respect to all other animal species. Therefore, learning how cooperation emerges and persists is a key question for social scientists. Recently, scholars have recognized the importance of social norms as solutions to major local and large-scale collective action problems, from the management of water resources to the reduction of smoking in public places to the change in fertility practices. Yet a well-founded model of the effect of social norms on human cooperation is still lacking.We present here a version of the Experience-Weighted Attraction (EWA) reinforcement learning model that integrates norm-based considerations into its utility function that we call EWA+Norms. We compare the behaviour of this hybrid model to the standard EWA when applied to a collective risk social dilemma in which groups of individuals must reach a threshold level of cooperation to avoid the risk of catastrophe. We find that standard EWA is not sufficient for generating cooperation, but that EWA+Norms is. Next step is to compare simulation results with human behaviour in large-scale experiments.