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dc.contributor.convenorManuela M. Velosoen_AU
dc.contributor.authorPham, Nghiaen_US
dc.contributor.authorThornton, Johnen_US
dc.contributor.authorSattar, Abdulen_US
dc.contributor.editorManuela Velosaen_US
dc.date.accessioned2017-05-03T12:54:31Z
dc.date.available2017-05-03T12:54:31Z
dc.date.issued2007en_US
dc.date.modified2009-05-29T07:10:01Z
dc.identifier.refurihttp://www.ijcai-07.org/en_AU
dc.identifier.urihttp://hdl.handle.net/10072/18331
dc.description.abstractLocal search procedures for solving satisfiability problems have attracted considerable attention since the development of GSAT in 1992. However, recent work indicates that for many real-world problems, complete search methods have the advantage, because modern heuristics are able to effectively exploit problem structure. Indeed, to develop a local search technique that can effectively deal with variable dependencies has been an open challenge since 1997. In this paper we show that local search techniques can effectively exploit information about problem structure producing significant improvements in performance on structured problem instances. Building on the earlier work of Ostrowski et al. we describe how information about variable dependencies can be built into a local search, so that only independent variables are considered for flipping. The cost effect of a flip is then dynamically calculated using a dependency lattice that models dependent variables using gates (specifically and, or and equivalence gates). The experimental study on hard structured benchmark problems demonstrates that our new approach significantly outperforms the previously reported best local search techniques.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherSpringeren_US
dc.publisher.placeMenlo Park, Californiaen_US
dc.publisher.urihttp://www.ijcai.org/en_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencenameInternational Joint Conference on Artificial Intelligence, IJCAI-07en_US
dc.relation.ispartofconferencetitleIJCAI-07, Proceedings of the 20th International Joint Conference on Artificial Intelligenceen_US
dc.relation.ispartofdatefrom2007-01-06en_US
dc.relation.ispartofdateto2007-01-12en_US
dc.relation.ispartoflocationHyderabad, Indiaen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode280213en_US
dc.titleBuilding Structure into 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.date.issued2007
gro.hasfulltextNo Full Text


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

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