A mean field stochastic game for battery state-dependent power management

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

Abstract

We consider large population of interacting mobile devices with individual state dynamics. Each mobile device has its own battery. The battery state is a modeled as a Markov decision process. The mobile devices are coupled via their payoff functions. Each mobile chooses a dynamic power management strategy in order to have a satisfactory long-term payoff. We propose a mean field stochastic game formulation when the number of mobile devices is very large. We establish a connection between finite stochastic game modeling and the evolutionary game modelling at the infinite population. Sufficient conditions for stationary mean field equilibria are given.

Original languageEnglish (US)
Title of host publicationProceedings of the 18th IFAC World Congress
Pages4839-4844
Number of pages6
Volume18
EditionPART 1
DOIs
StatePublished - Dec 1 2011
Event18th IFAC World Congress - Milano, Italy
Duration: Aug 28 2011Sep 2 2011

Other

Other18th IFAC World Congress
CountryItaly
CityMilano
Period8/28/119/2/11

Fingerprint

Mobile devices
Power management (telecommunication)

Keywords

  • Dynamic control and games
  • Large-scale systems
  • Mean field
  • Stochastic games

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Hamidou, T. (2011). A mean field stochastic game for battery state-dependent power management. In Proceedings of the 18th IFAC World Congress (PART 1 ed., Vol. 18, pp. 4839-4844) https://doi.org/10.3182/20110828-6-IT-1002.01228

A mean field stochastic game for battery state-dependent power management. / Hamidou, Tembine.

Proceedings of the 18th IFAC World Congress. Vol. 18 PART 1. ed. 2011. p. 4839-4844.

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

Hamidou, T 2011, A mean field stochastic game for battery state-dependent power management. in Proceedings of the 18th IFAC World Congress. PART 1 edn, vol. 18, pp. 4839-4844, 18th IFAC World Congress, Milano, Italy, 8/28/11. https://doi.org/10.3182/20110828-6-IT-1002.01228
Hamidou T. A mean field stochastic game for battery state-dependent power management. In Proceedings of the 18th IFAC World Congress. PART 1 ed. Vol. 18. 2011. p. 4839-4844 https://doi.org/10.3182/20110828-6-IT-1002.01228
Hamidou, Tembine. / A mean field stochastic game for battery state-dependent power management. Proceedings of the 18th IFAC World Congress. Vol. 18 PART 1. ed. 2011. pp. 4839-4844
@inproceedings{40ba092d1f5d4c1f814727600f467cb2,
title = "A mean field stochastic game for battery state-dependent power management",
abstract = "We consider large population of interacting mobile devices with individual state dynamics. Each mobile device has its own battery. The battery state is a modeled as a Markov decision process. The mobile devices are coupled via their payoff functions. Each mobile chooses a dynamic power management strategy in order to have a satisfactory long-term payoff. We propose a mean field stochastic game formulation when the number of mobile devices is very large. We establish a connection between finite stochastic game modeling and the evolutionary game modelling at the infinite population. Sufficient conditions for stationary mean field equilibria are given.",
keywords = "Dynamic control and games, Large-scale systems, Mean field, Stochastic games",
author = "Tembine Hamidou",
year = "2011",
month = "12",
day = "1",
doi = "10.3182/20110828-6-IT-1002.01228",
language = "English (US)",
isbn = "9783902661937",
volume = "18",
pages = "4839--4844",
booktitle = "Proceedings of the 18th IFAC World Congress",
edition = "PART 1",

}

TY - GEN

T1 - A mean field stochastic game for battery state-dependent power management

AU - Hamidou, Tembine

PY - 2011/12/1

Y1 - 2011/12/1

N2 - We consider large population of interacting mobile devices with individual state dynamics. Each mobile device has its own battery. The battery state is a modeled as a Markov decision process. The mobile devices are coupled via their payoff functions. Each mobile chooses a dynamic power management strategy in order to have a satisfactory long-term payoff. We propose a mean field stochastic game formulation when the number of mobile devices is very large. We establish a connection between finite stochastic game modeling and the evolutionary game modelling at the infinite population. Sufficient conditions for stationary mean field equilibria are given.

AB - We consider large population of interacting mobile devices with individual state dynamics. Each mobile device has its own battery. The battery state is a modeled as a Markov decision process. The mobile devices are coupled via their payoff functions. Each mobile chooses a dynamic power management strategy in order to have a satisfactory long-term payoff. We propose a mean field stochastic game formulation when the number of mobile devices is very large. We establish a connection between finite stochastic game modeling and the evolutionary game modelling at the infinite population. Sufficient conditions for stationary mean field equilibria are given.

KW - Dynamic control and games

KW - Large-scale systems

KW - Mean field

KW - Stochastic games

UR - http://www.scopus.com/inward/record.url?scp=84866769514&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866769514&partnerID=8YFLogxK

U2 - 10.3182/20110828-6-IT-1002.01228

DO - 10.3182/20110828-6-IT-1002.01228

M3 - Conference contribution

SN - 9783902661937

VL - 18

SP - 4839

EP - 4844

BT - Proceedings of the 18th IFAC World Congress

ER -