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Distributed Seeking of Nash Equilibria in Mobile Sensor Networks
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0001-9940-5929
Department of Industrial and Enterprise Systems Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA.
2010 (English)In: Proc. 49th IEEE Conference on Decision and Control (CDC), IEEE , 2010, 5598-5603 p.Conference paper (Refereed)
Abstract [en]

In this paper we consider the problem of distributedconvergence to a Nash equilibrium based on minimalinformation about the underlying noncooperative game. We assume that the players/agents generate their actions based only on measurements of local cost functions, which are corrupted with additive noise. Structural parameters of theirown and other players’ costs, as well as the actions of the other players are unknown. Furthermore, we assume that theagents may have dynamics: their actions can not be changedinstantaneously. We propose a method based on a stochasticextremum seeking algorithm with sinusoidal perturbations and we prove its convergence, with probability one, to a Nashequilibrium. We discuss how the proposed algorithm can be adopted for solving coordination problems in mobile sensornetworks, taking into account specific motion dynamics of the sensors. The local cost functions can be designed such that some specific overall goal is achieved. We give an example in which each agent/sensor needs to fulfill a locally defined goal, while maintaining connectivity with neighboring agents. The proposed algorithms are illustrated through simulations.

Place, publisher, year, edition, pages
IEEE , 2010. 5598-5603 p.
Keyword [en]
Noncooperative games, learning, Nash equilibrium, extremum seeking control, convergence, stochastic optimization, mobile sensor networks, multi-agent control
National Category
Information Science
URN: urn:nbn:se:kth:diva-47696DOI: 10.1109/CDC.2010.5717257ISI: 000295049106059ScopusID: 2-s2.0-79953131420ISBN: 978-1-4244-7745-6OAI: diva2:456056
49th IEEE Conference on Decision and Control (CDC), Atlanta, GA , USA
© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111121Available from: 2011-11-21 Created: 2011-11-11 Last updated: 2012-02-07Bibliographically approved

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