The Evolution of Reputation-Based Cooperation in Regular Networks

TL;DR

This paper investigates how different reputation assessment rules influence the evolution of cooperation in regular social networks, revealing that simple standing is the most robust rule for promoting cooperation.

Contribution

It introduces a new individual-based model analyzing the interplay of reputation and network structure, comparing four moral assessment rules in the context of cooperation evolution.

Findings

Simple standing is the most robust assessment rule for cooperation.

The effectiveness of assessment rules depends on benefit-to-cost ratio, network degree, and error conditions.

Different rules lead to varied cooperation dynamics depending on network parameters.

Abstract

Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules---shunning, image scoring, stern judging, and simple standing---and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule---simple standing---is the most robust among the four assessment rules in promoting cooperation in regular networks.