On asynchronous implementations of fictitious play for distributed learning

Brian Swenson, Soummya Kar, Joao Xavier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The classical Fictitious Play (FP) algorithm is defined within a framework of synchronous repeated play. In practice, the global synchronization assumed in classical FP can be difficult to achieve in large-scale multi-agent settings. The paper considers FP with asynchronous updates-a variant of FP in which players are permitted to be either "active" or "idle" in each stage of the repeated play process. The FP process with asynchronous updates is shown to be a generalization of classical FP. Analytical convergence results are given for the asynchronous variant of FP. Furthermore, the paper studies an asynchronous continuous-time embedding of FP. The continuous- time embedded FP process may be implemented in a real-world setting where no global clock is available. Sufficient conditions for convergence of the continuous-time embedded process are provided as a consequence of the convergence analysis for FP with asynchronous updates. Example implementations that attain the sufficient condition are presented.

Original languageEnglish (US)
Title of host publicationConference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1119-1124
Number of pages6
ISBN (Electronic)9781467385763
DOIs
StatePublished - Feb 26 2016
Event49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States
Duration: Nov 8 2015Nov 11 2015

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2016-February
ISSN (Print)1058-6393

Other

Other49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015
Country/TerritoryUnited States
CityPacific Grove
Period11/8/1511/11/15

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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