Efficient Learning Equilibrium

Ronen I. Brafman, Moshe Tennenholtz

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

10 Scopus citations

Abstract

We introduce efficient learning equilibrium (ELE), a normative approach to learning in non cooperative settings. In ELE, the learning algorithms themselves are required to be in equilibrium. In addition, the learning algorithms arrive at a desired value after polynomial time, and deviations from a prescribed ELE become irrational after polynomial time. We prove the existence of an ELE in the perfect monitoring setting, where the desired value is the expected payoff in a Nash equilibrium. We also show that an ELE does not always exist in the imperfect monitoring case. Yet, it exists in the special case of common-interest games. Finally, we extend our results to general stochastic games.

Original languageEnglish
Title of host publicationNIPS 2002
Subtitle of host publicationProceedings of the 15th International Conference on Neural Information Processing Systems
EditorsSuzanna Becker, Sebastian Thrun, Klaus Obermayer
PublisherMIT Press Journals
Pages1603-1610
Number of pages8
ISBN (Electronic)0262025507, 9780262025508
StatePublished - 1 Jan 2002
Event15th International Conference on Neural Information Processing Systems, NIPS 2002 - Vancouver, Canada
Duration: 9 Dec 200214 Dec 2002

Publication series

NameNIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Conference

Conference15th International Conference on Neural Information Processing Systems, NIPS 2002
Country/TerritoryCanada
CityVancouver
Period9/12/0214/12/02

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Information Systems

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