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dc.contributor.convenorANU
dc.contributor.authorThornton, J
dc.contributor.authorPullan, W
dc.contributor.authorTerry, J
dc.contributor.editorBob McKay, John Slaney
dc.date.accessioned2017-05-03T13:58:14Z
dc.date.available2017-05-03T13:58:14Z
dc.date.issued2002
dc.date.modified2010-07-28T06:59:21Z
dc.identifier.isbn9783540001973
dc.identifier.issn0302-9743
dc.identifier.doi10.1007/3-540-36187-1_50
dc.identifier.urihttp://hdl.handle.net/10072/1466
dc.description.abstractConsiderable progress has recently been made in using clause weighting algorithms such as DLM and SDF to solve SAT benchmark problems. While these algorithms have outperformed earlier stochastic techniques on many larger problems, this improvement has been bought at the cost of extra parameters and the complexity of fine tuning these parameters to obtain optimal run-time performance. This paper examines the use of parameters, specifically in relation to DLM, to identify underlying features in clause weighting that can be used to eliminate or predict workable parameter settings. To this end we propose and empirically evaluate a simplified clause weighting algorithm that replaces the tabu list and flat moves parameter used in DLM. From this we show that our simplified clause weighting algorithm is competitive with DLM on the four categories of SAT problem for whichDLMhas already been optimised.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent56457 bytes
dc.format.extent25773 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofconferencename15th Australian Joint Conference on Artificial Intelligence
dc.relation.ispartofconferencetitleLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
dc.relation.ispartofdatefrom2002-12-02
dc.relation.ispartofdateto2002-12-06
dc.relation.ispartoflocationCanberra, Australia
dc.relation.ispartofpagefrom569
dc.relation.ispartofpageto578
dc.relation.ispartofvolume2557
dc.subject.fieldofresearchcode280213
dc.titleTowards Fewer Parameters for SAT Clause Weighting Algorithms
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2002 Springer-Verlag. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher.The original publication is available at www.springerlink.com
gro.date.issued2002
gro.hasfulltextFull Text
gro.griffith.authorPullan, Wayne J.


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

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