Bayesian ignorance

Noga Alon, Yuval Emek, Michal Feldman, Moshe Tennenholtz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We quantify the effect of Bayesian ignorance by comparing the social cost obtained in a Bayesian game by agents with local views to the expected social cost of agents having global views. Both benevolent agents, whose goal is to minimize the social cost, and selfish agents, aiming at minimizing their own individual costs, are considered. When dealing with selfish agents, we consider both best and worst equilibria outcomes. While our model is general, most of our results concern the setting of network cost sharing (NCS) games. We provide tight asymptotic results on the effect of Bayesian ignorance in directed and undirected NCS games with benevolent and selfish agents. Among our findings we expose the counter-intuitive phenomenon that "ignorance is bliss": Bayesian ignorance may substantially improve the social cost of selfish agents. We also prove that public random bits can replace the knowledge of the common prior in attempt to bound the effect of Bayesian ignorance in settings with benevolent agents. Together, our work initiates the study of the effects of local vs. global views on the social cost of agents in Bayesian contexts.

Original languageEnglish (US)
Title of host publicationPODC'10 - Proceedings of the 2010 ACM Symposium on Principles of Distributed Computing
Pages384-391
Number of pages8
DOIs
StatePublished - Sep 8 2010
Externally publishedYes
Event29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2010 - Zurich, Switzerland
Duration: Jul 25 2010Jul 28 2010

Publication series

NameProceedings of the Annual ACM Symposium on Principles of Distributed Computing

Other

Other29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2010
CountrySwitzerland
CityZurich
Period7/25/107/28/10

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Keywords

  • Bayesian games
  • Local vs. global view
  • Network cost sharing

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