Exogenous empirical-evidence equilibria in perfect-monitoring repeated games yield correlated equilibria

Handle URI:
http://hdl.handle.net/10754/550517
Title:
Exogenous empirical-evidence equilibria in perfect-monitoring repeated games yield correlated equilibria
Authors:
Dudebout, Nicolas; Shamma, Jeff S. ( 0000-0001-5638-9551 )
Abstract:
This paper proves that exogenous empirical-evidence equilibria (xEEEs) in perfect-monitoring repeated games induce correlated equilibria of the associated one-shot game. An empirical-evidence equilibrium (EEE) is a solution concept for stochastic games. At equilibrium, agents' strategies are optimal with respect to models of their opponents. These models satisfy a consistency condition with respect to the actual behavior of the opponents. As such, EEEs replace the full-rationality requirement of Nash equilibria by a consistency-based bounded-rationality one. In this paper, the framework of empirical evidence is summarized, with an emphasis on perfect-monitoring repeated games. A less constraining notion of consistency is introduced. The fact that an xEEE in a perfect-monitoring repeated game induces a correlated equilibrium on the underlying one-shot game is proven. This result and the new notion of consistency are illustrated on the hawk-dove game. Finally, a method to build specific correlated equilibria from xEEEs is derived.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
IEEE
Journal:
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference/Event name:
2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Issue Date:
15-Dec-2014
DOI:
10.1109/CDC.2014.7039539
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7039539
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorDudebout, Nicolasen
dc.contributor.authorShamma, Jeff S.en
dc.date.accessioned2015-04-23T13:55:50Zen
dc.date.available2015-04-23T13:55:50Zen
dc.date.issued2014-12-15en
dc.identifier.doi10.1109/CDC.2014.7039539en
dc.identifier.urihttp://hdl.handle.net/10754/550517en
dc.description.abstractThis paper proves that exogenous empirical-evidence equilibria (xEEEs) in perfect-monitoring repeated games induce correlated equilibria of the associated one-shot game. An empirical-evidence equilibrium (EEE) is a solution concept for stochastic games. At equilibrium, agents' strategies are optimal with respect to models of their opponents. These models satisfy a consistency condition with respect to the actual behavior of the opponents. As such, EEEs replace the full-rationality requirement of Nash equilibria by a consistency-based bounded-rationality one. In this paper, the framework of empirical evidence is summarized, with an emphasis on perfect-monitoring repeated games. A less constraining notion of consistency is introduced. The fact that an xEEE in a perfect-monitoring repeated game induces a correlated equilibrium on the underlying one-shot game is proven. This result and the new notion of consistency are illustrated on the hawk-dove game. Finally, a method to build specific correlated equilibria from xEEEs is derived.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7039539en
dc.rights(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleExogenous empirical-evidence equilibria in perfect-monitoring repeated games yield correlated equilibriaen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalDecision and Control (CDC), 2014 IEEE 53rd Annual Conference onen
dc.conference.date15 December 2014 through 17 December 2014en
dc.conference.name2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014en
dc.eprint.versionPost-printen
dc.contributor.institutionDecision and Control Laboratory, Georgia Institute of Technology, Atlanta, GA 30332 USAen
kaust.authorShamma, Jeff S.en
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