The price of anarchy in large games

Michal Feldman, Nicole Immorlica, Brendan Lucier, Tim Roughgarden, Vasilis Syrgkanis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

38 Scopus citations

Abstract

We present an analysis framework for bounding the price of anarchy (POA) in games that have many players, as in many of the games most pertinent to computer science applications. We use this framework to demonstrate that, in many of the models in which the POA has been studied, the POA in large games is much smaller than the worst-case bound. Our framework also differentiates between mechanisms with similar worst-case performance, such as simultaneous uniform-price auctions and greedy combinatorial auctions, thereby providing new insights about which mechanisms are likely to perform well in realistic settings.

Original languageEnglish
Title of host publicationSTOC 2016 - Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing
EditorsYishay Mansour, Daniel Wichs
PublisherAssociation for Computing Machinery
Pages963-976
Number of pages14
ISBN (Electronic)9781450341325
DOIs
StatePublished - 19 Jun 2016
Event48th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2016 - Cambridge, United States
Duration: 19 Jun 201621 Jun 2016

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
Volume19-21-June-2016
ISSN (Print)0737-8017

Conference

Conference48th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2016
Country/TerritoryUnited States
CityCambridge
Period19/06/1621/06/16

Funding

FundersFunder number
Seventh Framework Programme
European Research Council337122
Seventh Framework Programme

    Keywords

    • Combinatorial auctions
    • Large games
    • Price of anarchy
    • Smoothness

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