Cooperation with bottom-up reputation dynamics

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Abstract

Cooperation among selfish agents can be promoted by allowing agents to condition behavior on reputation. Social norms - dictating how agents update the reputations of others - are central in determining whether this mechanism is effective. In particular, norms that reward justified defection have been shown to promote cooperation. A major limitation of existing models is that they assume all agents adopt a uniform norm, in a top down fashion. Here we show that when agents can spontaneously adopt novel norms, a learning process will see them drift towards socially undesirable outcomes. We present a model where agents can choose both how to react to reputations and how to assign the reputations of others - making social norms emergent. In this scenario cooperation can only be achieved when the space of norms is severely restricted. In the real world, reputation systems have a mixed record. This is often attributed to the costly nature of assigning reputations, and the ability of agents to easily whitewash their reputations. Our result suggests that even if these issues are overcome, enabling cooperation via reputation is likely to require additional mechanisms or restrictions upon the norms of the agents in the system.

Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems
EditorsNoa Agmon, Matthew E. Taylor
Place of PublicationRichland SC USA
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems
Pages269-276
Number of pages8
ISBN (Electronic)9781450363099
ISBN (Print)9781510892002
Publication statusPublished - 2019
EventInternational Conference on Autonomous Agents and Multiagent Systems 2019 - Montreal, Canada
Duration: 13 May 201917 May 2019
Conference number: 18th

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume1
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

ConferenceInternational Conference on Autonomous Agents and Multiagent Systems 2019
Abbreviated titleAAMAS 2019
CountryCanada
CityMontreal
Period13/05/1917/05/19

Keywords

  • Cooperation
  • Dynamics
  • Evolutionary game theory
  • Reputation

Cite this

Xu, J., Garcia Gallego, J., & Handfield, T. (2019). Cooperation with bottom-up reputation dynamics. In N. Agmon, & M. E. Taylor (Eds.), Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (pp. 269-276). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; Vol. 1). International Foundation for Autonomous Agents and Multiagent Systems. http://dl.acm.org/citation.cfm?id=3306127.3331703