On-line Steiner trees in the Euclidean plane
SCG '92 Proceedings of the eighth annual symposium on Computational geometry
Steiner points in tree metrics don't (really) help
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
A tight bound on approximating arbitrary metrics by tree metrics
Journal of Computer and System Sciences - Special issue: STOC 2003
Network design with weighted players
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Two-terminal routing games with unknown active players
Artificial Intelligence
The Price of Stability for Network Design with Fair Cost Allocation
SIAM Journal on Computing
On the Value of Coordination in Network Design
SIAM Journal on Computing
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
Simultaneous auctions are (almost) efficient
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
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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 "gnorance 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.