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dc.contributor.authorRobinson, Nathan
dc.contributor.authorGretton, Charles
dc.contributor.authorPham, Duc Nghia
dc.contributor.authorSattar, Abdul
dc.contributor.editorZhang, BT
dc.contributor.editorOrgun, MA
dc.date.accessioned2017-05-03T13:11:09Z
dc.date.available2017-05-03T13:11:09Z
dc.date.issued2010
dc.date.modified2011-03-03T07:09:58Z
dc.identifier.isbn978-3-642-15245-0
dc.identifier.issn0302-9743
dc.identifier.refurihttp://www.ourglocal.com/url/?url=http%3A%2F%2Fwww.pricai2010.org%2F
dc.identifier.doi10.1007/978-3-642-15246-7_23
dc.identifier.urihttp://hdl.handle.net/10072/36746
dc.description.abstractWe consider the problem of computing optimal plans for propositional planning problems with action costs. In the spirit of leveraging advances in general-purpose automated reasoning for that setting, we develop an approach that operates by solving a sequence of partial weighted MaxSAT problems, each of which corresponds to a step-bounded variant of the problem at hand. Our approach is the first SAT-based system in which a proof of cost-optimality is obtained using a MaxSAT procedure. It is also the first system of this kind to incorporate an admissible planning heuristic. We perform a detailed empirical evaluation of our work using benchmarks from a number of International Planning Competitions.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofconferencename11th Pacific Rim International Conference on Artificial Intelligence
dc.relation.ispartofconferencetitlePRICAI 2010: TRENDS IN ARTIFICIAL INTELLIGENCE
dc.relation.ispartofdatefrom2010-08-30
dc.relation.ispartofdateto2010-09-02
dc.relation.ispartoflocationKorean Inst Informat Sci & Engn, Daegu, SOUTH KOREA
dc.relation.ispartofpagefrom231
dc.relation.ispartofpagefrom2 pages
dc.relation.ispartofpageto+
dc.relation.ispartofpageto2 pages
dc.relation.ispartofvolume6230
dc.rights.retentionY
dc.subject.fieldofresearchArtificial intelligence not elsewhere classified
dc.subject.fieldofresearchcode460299
dc.titlePartial Weighted MaxSAT for Optimal Planning
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.date.issued2010
gro.hasfulltextNo Full Text
gro.griffith.authorSattar, Abdul


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

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