Revisiting log-linear learning: Asynchrony, completeness and payoff-based implementation

Jason R. Marden, Jeff S. Shamma

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

22 Scopus citations

Abstract

The theory of learning in games has sought to understand how and why equilibria emerge in non-cooperative games. Traditionally, social science literature develops descriptive game theoretic models for players, analyzes the limiting behavior, and generalizes the results for larger classes of games. Recently, there has been a significant amount of research seeking to understand these behavioral models not from a descriptive point of view, but rather from a prescriptive point of view [1]-[4]. The goal is to use these behavioral models as a prescriptive control approach in distributed multi-agent systems where the guaranteed limiting behavior would represent a desirable operating condition.

Original languageEnglish (US)
Title of host publication2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
Pages1171-1172
Number of pages2
DOIs
StatePublished - Dec 1 2010
Event48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010 - Monticello, IL, United States
Duration: Sep 29 2010Oct 1 2010

Publication series

Name2010 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010

Other

Other48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010
Country/TerritoryUnited States
CityMonticello, IL
Period09/29/1010/1/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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