Sequential empirical coordination under an output entropy constraint

Ehsan Shafieepoorfard, Maxim Raginsky

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

Abstract

This paper considers the problem of sequential empirical coordination, where the objective is to achieve a given value of the expected uniform deviation between state-action empirical averages and statistical expectations under a given strategic probability measure, with respect to a universal Glivenko-Cantelli class of test functions. A communication constraint is imposed on the Shannon entropy of the resulting action sequence. It is shown that the fundamental limit on the output entropy is given by the minimum of the mutual information between the state and the action processes under all strategic measures that have the same marginal state process as the target measure and approximate the target measure to desired accuracy with respect to the underlying Glivenko-Cantelli seminorm. The fundamental limit is shown to be asymptotically achievable by tree-structured codes.

Original languageEnglish (US)
Title of host publication2016 IEEE 55th Conference on Decision and Control, CDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7347-7352
Number of pages6
ISBN (Electronic)9781509018376
DOIs
StatePublished - Dec 27 2016
Event55th IEEE Conference on Decision and Control, CDC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

Name2016 IEEE 55th Conference on Decision and Control, CDC 2016

Other

Other55th IEEE Conference on Decision and Control, CDC 2016
CountryUnited States
CityLas Vegas
Period12/12/1612/14/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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