Approximately optimal mechanism design via differential privacy

Kobbi Nissim, Rann Smorodinsky, Moshe Tennenholtz

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

83 Scopus citations

Abstract

We study the implementation challenge in an abstract interdependent values model and an arbitrary objective function. We design a generic mechanism that allows for approximate optimal implementation of insensitive objective functions in ex-post Nash equilibrium. If, furthermore, values are private then the same mechanism is strategy proof. We cast our results onto two specific models: pricing and facility location. The mechanism we design is optimal up to an additive factor of the order of magnitude of one over the square root of the number of agents and involves no utility transfers. Underlying our mechanism is a lottery between two auxiliary mechanisms - - with high probability we actuate a mechanism that reduces players influence on the choice of the social alternative, while choosing the optimal outcome with high probability. This is where differential privacy is employed. With the complementary probability we actuate a mechanism that may be typically far from optimal but is incentive compatible. The joint mechanism inherits the desired properties from both.

Original languageEnglish
Title of host publicationITCS 2012 - Innovations in Theoretical Computer Science Conference
Pages203-213
Number of pages11
DOIs
StatePublished - 6 Feb 2012
Event3rd Conference on Innovations in Theoretical Computer Science, ITCS 2012 - Cambridge, MA, United States
Duration: 8 Jan 201210 Jan 2012

Publication series

NameITCS 2012 - Innovations in Theoretical Computer Science Conference

Conference

Conference3rd Conference on Innovations in Theoretical Computer Science, ITCS 2012
Country/TerritoryUnited States
CityCambridge, MA
Period8/01/1210/01/12

Keywords

  • differential privacy
  • facility location
  • mechanism design
  • monopolist pricing

ASJC Scopus subject areas

  • Computational Theory and Mathematics

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