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dc.contributor.authorHatanaka, Takeshi-
dc.contributor.authorWasa, Yasuaki-
dc.contributor.authorFunada, Riku-
dc.contributor.authorCharalambides, Alexandros G.-
dc.contributor.authorFujita, Masayuki-
dc.contributor.otherΧαραλαμπίδης, Αλέξανδρος-
dc.date.accessioned2017-01-12T11:53:08Z-
dc.date.available2017-01-12T11:53:08Z-
dc.date.issued2016-03-01-
dc.identifier.citationIEEE Transactions on Automatic Control, 2016, vol. 61, no. 3,pp. 709-724en_US
dc.identifier.issn15582523-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/9014-
dc.description.abstractThis paper addresses cooperative environmental monitoring for Pan-Tilt-Zoom (PTZ) visual sensor networks. In particular, we investigate the optimal monitoring problem whose objective function value is intertwined with the uncertain state of the physical world. In addition, due to the large volume of vision data, it is desired for each sensor to execute processing through local computation and communication. To address these issues, we present a distributed solution to the problem based on game theoretic cooperative control and payoff-based learning. At the first stage, a utility function is designed so that the resulting game constitutes a potential game with potential function equal to the group objective function, where the designed utility is shown to be computable through local image processing and communication. Then, we present a payoff-based learning algorithm so that the sensors are led to the global objective function maximizers without using any prior information on the environmental state. Finally, we run experiments to demonstrate the effectiveness of the present approach.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Automatic Controlen_US
dc.rights© IEEEen_US
dc.subjectCyber-physical systemsen_US
dc.subjectEnvironmental monitoringen_US
dc.subjectGame theoretic cooperative controlen_US
dc.subjectPayoff-based learningen_US
dc.subjectVisual sensor networksen_US
dc.titleA Payoff-Based Learning Approach to Cooperative Environmental Monitoring for PTZ Visual Sensor Networksen_US
dc.typeArticleen_US
dc.collaborationTokyo Institute of Technologyen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryEarth and Related Environmental Sciencesen_US
dc.journalsSubscriptionen_US
dc.countryJapanen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/TAC.2015.2450611en_US
dc.relation.issue3en_US
dc.relation.volume61en_US
cut.common.academicyear2015-2016en_US
dc.identifier.spage709en_US
dc.identifier.epage724en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn00189286-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.orcid0000-0002-0374-2128-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
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