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dc.contributor.authorLin, Hanen_US
dc.contributor.authorSu, Kaileen_US
dc.contributor.authorLi, Chu-Minen_US
dc.contributor.editorDieter Fox, Carla P. Gomesen_US
dc.date.accessioned2017-05-03T16:57:05Z
dc.date.available2017-05-03T16:57:05Z
dc.date.issued2008en_US
dc.date.modified2009-07-02T06:45:00Z
dc.identifier.refurihttp://www.aaai.org/Conferences/AAAI/aaai08.phpen_AU
dc.identifier.urihttp://hdl.handle.net/10072/24593
dc.description.abstractThis paper focuses on improving branch-and-bound Max-SAT solvers by speeding up the lower bound computation. We notice that the existing propagation-based computing methods and the resolution-based computing methods, which have been studied intensively, both suffer from several drawbacks. In order to overcome these drawbacks, we propose a new method with a nice property that guarantees the increment of lower bounds. The new method exploits within-problem learning techniques. More specifically, at each branch point in the search-tree, the current node is enabled to inherit inconsistencies from its parent and learn information about effectiveness of the lower bound computing procedure from previous nodes. Furthermore, after branching on a new variable, the inconsistencies may shrink by applying unit propagation to them, and such process increases the probability of getting better lower bounds. We graft the new techniques into maxsatz and the experimental results demonstrate that the new solver outperforms the best state-of-the-art solvers on a wide range of instances including random and structured ones.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherAAAI Pressen_US
dc.publisher.placeCalifornia, United Statesen_US
dc.publisher.urihttp://www.aaai.org/Conferences/AAAI/aaai08.phpen_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencenameTwenty-Third AAAI Conference on Artificial Intelligence, AAAI-08en_US
dc.relation.ispartofconferencetitleProceedings of the Twenty-Third AAAI Conference on Artificial Intelligence and the Twentieth Innovativeen_US
dc.relation.ispartofdatefrom2008-07-13en_US
dc.relation.ispartofdateto2008-07-17en_US
dc.relation.ispartoflocationChicago, Illinois, USAen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchComputational Logic and Formal Languagesen_US
dc.subject.fieldofresearchcode080203en_US
dc.titleWithin-problem Learning for Efficient Lower Bound Computation in Max-SAT Solvingen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.rights.copyrightCopyright 2008 AAAI Press. Use hypertext link for access to conference website.en_AU
gro.date.issued2008
gro.hasfulltextNo Full Text


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