Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Partial Weighted MaxSAT for Optimal Planning

Simple item page
dc.contributor.authorRobinson, Nathan
dc.contributor.authorGretton, Charles
dc.contributor.authorPham, Duc Nghia
dc.contributor.authorSattar, Abdul
dc.contributor.editorByoung-Tak Zhang
dc.contributor.editorMehmet A. Orgun
dc.coverage.spatialDaegu, Korea
dc.date.accessioned2022-01-18T03:07:00Z
dc.date.createdAugust 30-September 2
dc.date.issued2010
dc.date.updated2020-12-06T07:20:00Z
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.en_AU
dc.description.sponsorshipNICTA is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Centre of Excellence program. This work was also supported by EC FP7-IST grant 215181-CogX.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.isbn978-3-642-15245-0en_AU
dc.identifier.urihttp://hdl.handle.net/1885/258474
dc.language.isoen_AUen_AU
dc.provenancehttps://www.springernature.com/gp/open-research/policies/book-policies..."Authors whose work is accepted for publication in a non-open access Springer or Palgrave Macmillan book are permitted to self-archive the accepted manuscript (AM), on their own personal website and/or in their funder or institutional repositories, for public release after 12 months embargo " From the publishers site as at 25/01/2022
dc.publisherSpringeren_AU
dc.relationhttp://purl.org/au-research/grants/arc/DP140102596en_AU
dc.relation.ispartofseries11th Pacific Rim International Conference on Artificial Intelligenceen_AU
dc.sourcePRICAI 2010 : trends in artificial intelligence : 11th Pacific Rim International Conference on Artificial Intelligence, Daegu, Korea, August 30-September 2, 2010 : proceedingsen_AU
dc.titlePartial Weighted MaxSAT for Optimal Planningen_AU
dc.typeConference paperen_AU
dcterms.accessRightsOpen Access
local.bibliographicCitation.lastpage243en_AU
local.bibliographicCitation.startpage231en_AU
local.contributor.affiliationRobinson, Nathan, Griffith Universityen_AU
local.contributor.affiliationGretton, Charles, College of Engineering and Computer Science, ANUen_AU
local.contributor.affiliationPham, Duc Nghia, Griffith Universityen_AU
local.contributor.affiliationSattar, Abdul, Griffith Universityen_AU
local.contributor.authoruidGretton, Charles, u3223587en_AU
local.description.notesImported from ARIESen_AU
local.description.refereedYes
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classifieden_AU
local.identifier.ariespublicationu3223587xPUB5en_AU
local.identifier.doi10.1007/978-3-642-15246-7_23en_AU
local.identifier.scopusID2-s2.0-78049277916
local.publisher.urlhttps://link.springer.com/en_AU
local.type.statusAccepted Versionen_AU

Downloads

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
costop_sp.pdf
Size:
341.54 KB
Format:
Adobe Portable Document Format
Download

Collections

ANU Research Publications

DSpace software copyright © 2002-2026 LYRASIS