Indirect reciprocity investigates how social norms promote cooperation by continuously monitoring and assessing social interactions. This study shows that nuanced assessments of observations can mitigate disagreements and errors in situations where information is private and unreliable. Such quantitative assessments are error-correcting and may help sustain cooperation in natural populations.
Indirect reciprocity describes how cooperation arises in a community when its members value their reputation. Here, the authors show that nuanced assessments of observations can mitigate disagreements and errors when the opinions of community members are not synchronized. The field of indirect reciprocity investigates how social norms can foster cooperation when individuals continuously monitor and assess each other's social interactions. By adhering to certain social norms, cooperating individuals can improve their reputation and, in turn, receive benefits from others. Eight social norms, known as the leading eight, have been shown to effectively promote the evolution of cooperation as long as information is public and reliable. These norms categorize group members as either 'good' or 'bad'. In this study, we examine a scenario where individuals instead assign nuanced reputation scores to each other, and only cooperate with those whose reputation exceeds a certain threshold. We find both analytically and through simulations that such quantitative assessments are error-correcting, thus facilitating cooperation in situations where information is private and unreliable. Moreover, our results identify four specific norms that are robust to such conditions, and may be relevant for helping to sustain cooperation in natural populations.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据