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dc.contributor.authorPham, Nghiaen_US
dc.contributor.authorThornton, Johnen_US
dc.contributor.authorSattar, Abdulen_US
dc.contributor.editorDieter Fox and Carla Gomesen_US
dc.date.accessioned2017-04-24T09:59:08Z
dc.date.available2017-04-24T09:59:08Z
dc.date.issued2008en_US
dc.date.modified2009-05-25T06:41:36Z
dc.identifier.refuriwww.aaai.org/Conferences/AAAI/aaai08.phpen_AU
dc.identifier.doihttp://www.aaai.org/Library/AAAI/aaai08contents.phpen_AU
dc.identifier.urihttp://hdl.handle.net/10072/23981
dc.description.abstractWe propose a new local search platform that splits a CNF formula into three sub-components: i) a minimal dependency lattice (representing the core connections between logic gates), ii) a conjunction of equivalence clauses, and iii) the remaining clauses. We also adopt a new hierarchical cost function that focuses on solving the core components of the problem first. We then show experimentally that our platform not only significantly outperforms existing local search approaches but is also competitive with modern systematic solvers on highly structured problems.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent136487 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherAAAI Pressen_US
dc.publisher.placeUSAen_US
dc.publisher.urihttp://www.aaai.org/Conferences/AAAI/aaai08.phpen_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencename23rd AAAI Conference on Artificial Intelligence (AAAI-08)en_US
dc.relation.ispartofconferencetitleProceedings of the 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conferenceen_US
dc.relation.ispartofdatefrom2008-07-13en_US
dc.relation.ispartofdateto2008-07-17en_US
dc.relation.ispartoflocationChicago, USAen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classifieden_US
dc.subject.fieldofresearchcode080199en_US
dc.titleEfficiently Exploiting Dependencies in Local Search for SATen_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 2008 AAAI Press. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Use hypertext link for access to conference website.en_AU
gro.date.issued2008
gro.hasfulltextFull Text


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    Contains papers delivered by Griffith authors at national and international conferences.

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