TY - GEN

T1 - Bayesian ignorance

AU - Alon, Noga

AU - Emek, Yuval

AU - Feldman, Michal

AU - Tennenholtz, Moshe

PY - 2010

Y1 - 2010

N2 - 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.

AB - 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.

KW - Bayesian games

KW - Local vs. global view

KW - Network cost sharing

UR - http://www.scopus.com/inward/record.url?scp=77956249028&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77956249028&partnerID=8YFLogxK

U2 - 10.1145/1835698.1835785

DO - 10.1145/1835698.1835785

M3 - Conference contribution

AN - SCOPUS:77956249028

SN - 9781605588889

T3 - Proceedings of the Annual ACM Symposium on Principles of Distributed Computing

SP - 384

EP - 391

BT - PODC'10 - Proceedings of the 2010 ACM Symposium on Principles of Distributed Computing

T2 - 29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2010

Y2 - 25 July 2010 through 28 July 2010

ER -