A game-theoretic formulation of the homogeneous self-reconfiguration problem

Handle URI:
http://hdl.handle.net/10754/606858
Title:
A game-theoretic formulation of the homogeneous self-reconfiguration problem
Authors:
Pickem, Daniel; Egerstedt, Magnus; Shamma, Jeff S. ( 0000-0001-5638-9551 )
Abstract:
In this paper we formulate the homogeneous two- and three-dimensional self-reconfiguration problem over discrete grids as a constrained potential game. We develop a game-theoretic learning algorithm based on the Metropolis-Hastings algorithm that solves the self-reconfiguration problem in a globally optimal fashion. Both a centralized and a fully decentralized algorithm are presented and we show that the only stochastically stable state is the potential function maximizer, i.e. the desired target configuration. These algorithms compute transition probabilities in such a way that even though each agent acts in a self-interested way, the overall collective goal of self-reconfiguration is achieved. Simulation results confirm the feasibility of our approach and show convergence to desired target configurations.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 54th IEEE Conference on Decision and Control (CDC)
Conference/Event name:
2015 54th IEEE Conference on Decision and Control (CDC)
Issue Date:
15-Dec-2015
DOI:
10.1109/CDC.2015.7402645
Type:
Conference Paper
Sponsors:
This research was sponsored by AFOSR/MURI Project #FA9550-09-1- 0538 and ONR Project #N00014-09-1-0751.
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7402645
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorPickem, Danielen
dc.contributor.authorEgerstedt, Magnusen
dc.contributor.authorShamma, Jeff S.en
dc.date.accessioned2016-04-24T12:57:34Zen
dc.date.available2016-04-24T12:57:34Zen
dc.date.issued2015-12-15en
dc.identifier.doi10.1109/CDC.2015.7402645en
dc.identifier.urihttp://hdl.handle.net/10754/606858en
dc.description.abstractIn this paper we formulate the homogeneous two- and three-dimensional self-reconfiguration problem over discrete grids as a constrained potential game. We develop a game-theoretic learning algorithm based on the Metropolis-Hastings algorithm that solves the self-reconfiguration problem in a globally optimal fashion. Both a centralized and a fully decentralized algorithm are presented and we show that the only stochastically stable state is the potential function maximizer, i.e. the desired target configuration. These algorithms compute transition probabilities in such a way that even though each agent acts in a self-interested way, the overall collective goal of self-reconfiguration is achieved. Simulation results confirm the feasibility of our approach and show convergence to desired target configurations.en
dc.description.sponsorshipThis research was sponsored by AFOSR/MURI Project #FA9550-09-1- 0538 and ONR Project #N00014-09-1-0751.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7402645en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.en
dc.titleA game-theoretic formulation of the homogeneous self-reconfiguration problemen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2015 54th IEEE Conference on Decision and Control (CDC)en
dc.conference.date15-18 Dec. 2015en
dc.conference.name2015 54th IEEE Conference on Decision and Control (CDC)en
dc.conference.locationOsakaen
dc.eprint.versionPost-printen
dc.contributor.institutionRobotics, Georgia Institute of Technology, Atlanta, USAen
dc.contributor.institutionElectrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USAen
dc.contributor.institutionSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USAen
kaust.authorShamma, Jeff S.en
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