Abstract

Indirect reciprocity is a key mechanism that promotes cooperation in social dilemmas by means of reputation. Although it has been a common practice to represent reputations by binary values, either ‘good’ or ‘bad’, such a dichotomy is a crude approximation considering the complexity of reality. In this work, we studied norms with three different reputations, i.e., ‘good’, ‘neutral’, and ‘bad’. Through massive supercomputing for handling more than thirty billion possibilities, we fully identified which norms achieve cooperation and possess evolutionary stability against behavioural mutants. By systematically categorizing all these norms according to their behaviours, we found similarities and dissimilarities to their binary-reputation counterpart, the leading eight. We obtained four rules that should be satisfied by the successful norms, and the behaviour of the leading eight can be understood as a special case of these rules. A couple of norms that show counter-intuitive behaviours are also presented. We believe the findings are also useful for designing successful norms with more general reputation systems.

Highlights

  • We have focused on the third-order norms, second-order norms are included in the third-order CESS’s as a subset

  • From more than thirty billion possibilities, we filtered out “core” CESS norms that constitute the counterpart of the well-known leading eight

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Summary

Introduction

Part of the results is obtained by using the Fugaku computer at RIKEN Center for Computational Science (Proposal number ra000002). We appreciate the APCTP for its hospitality during the completion of this work.

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