Distributed correlated Q-learning for dynamic transmission control of sensor networks

Jane Wei Huang, Quanyan Zhu, Vikram Krishnamurthy, Tamer Basar

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

Abstract

This paper considers a Markovian dynamical game theoretic setting for distributed transmission control in a wireless sensor network. The available spectrum bandwidth is modeled as a Markov chain. A distributed algorithm named correlated Q-learning algorithm is proposed to obtain the correlated equilibrium policies of the system. This algorithm has the decentralized feature and is easily implementable in a real system. Numerical example is also provided to verify the performances of the proposed algorithms.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Proceedings
Pages1982-1985
Number of pages4
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010 - Dallas, TX, United States
Duration: Mar 14 2010Mar 19 2010

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010
CountryUnited States
CityDallas, TX
Period3/14/103/19/10

Keywords

  • Distributed algorithms
  • Game theory
  • Multisensor systems
  • Stochastic games

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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