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dc.contributor.convenorGabriella Pasien_AU
dc.contributor.authorKhanna, Sankalpen_US
dc.contributor.authorSattar, Abdulen_US
dc.contributor.authorHansen, Daviden_US
dc.contributor.authorStantic, Belaen_US
dc.contributor.editorRicardo Baeza-Yates, Jerome Lang, Sushmita Mitra, Simon Parsons, Gabriella Pasien_US
dc.date.accessioned2017-05-03T11:26:28Z
dc.date.available2017-05-03T11:26:28Z
dc.date.issued2009en_US
dc.date.modified2010-06-03T09:25:25Z
dc.identifier.refurihttp://www.wi-iat09.disco.unimib.it/IAT09/IAThome.htmen_AU
dc.identifier.doi10.1109/WI-IAT.2009.175en_AU
dc.identifier.urihttp://hdl.handle.net/10072/29999
dc.description.abstractMulti Agent Systems and the Distributed Constraint Optimization Problem (DCOP) formalism offer several asynchronous and optimal algorithms for solving naturally distributed optimization problems efficiently. There has been good application of this technology in addressing real world problems in areas like Sensor Networks and Meeting Scheduling. Most of these algorithms however exploit static tree structures and are thus not well suited to modeling and solving problems in rapidly changing domains. Also, while in theory most DCOP algorithms can be extended to handle complex local sub-problems, we argue that this generally results in making their performance sub-optimal, and thus their application less suitable. In this paper we present new measures that emphasize the interconnectedness between each agent's local and interagent sub-problems and use these measures to guide dynamic agent ordering during distributed constraint reasoning. The resulting algorithm, DCDCOP, offers a robust, flexible, and efficient mechanism for modeling and solving dynamic complex problems. Experimental evaluation of the algorithm shows that DCDCOP significantly outperforms ADOPT, the gold standard in search-based DCOP algorithms.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent757598 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherIEEE Computer Societyen_US
dc.publisher.placeLos Alamitos, CAen_US
dc.publisher.urihttp://portal.acm.org/citation.cfm?id=1632191.1632539en_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencename2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2009)en_US
dc.relation.ispartofconferencetitleProceedings. 2009 IEEE/WIC/ACM International Conference on Intelligent Agent Technologyen_US
dc.relation.ispartofdatefrom2009-09-15en_US
dc.relation.ispartofdateto2009-09-18en_US
dc.relation.ispartoflocationMilano, Italyen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchInformation Systems Development Methodologiesen_US
dc.subject.fieldofresearchcode080608en_US
dc.titleAn Efficient Algorithm For Solving Dynamic Complex DCOP Problemsen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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