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Using the relaxed plan heuristic to select goals in oversubscription planning problems

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Planificación y Aprendizajees
dc.contributor.authorGarcía Olaya, Ángel
dc.contributor.authorRosa Turbides, Tomás Eduardo de la
dc.contributor.authorBorrajo Millán, Daniel
dc.date.accessioned2012-01-16T13:17:09Z
dc.date.available2012-01-16T13:17:09Z
dc.date.issued2011
dc.description.abstractOversubscription planning (OSP) appears in many real problems where nding a plan achieving all goals is infeasi- ble. The objective is to nd a feasible plan reaching a goal sub- set while maximizing some measure of utility. In this paper, we present a new technique to select goals \a priori" for problems in which a cost bound prevents all the goals from being achieved. It uses estimations of distances between goals, which are com- puted using relaxed plans. Using these distances, a search in the space of subsets of goals is performed, yielding a new set of goals to plan for. A revised planning problem can be created and solved, taking into account only the selected goals. We present experiments in six di erent domains with good results.
dc.description.sponsorshipThis work has been partially supported by MICIIN TIN2008-06701-C03-03 and CCG10-UC3M/TIC-5597 projects.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationJose A. Lozano, José A. Gámez, José A. Moreno (eds.). Lectures Notes in Computer Science: vol. 7023. "Advances in Artificial Intelligencce: 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA, 2011, La Laguna, Spain, November 7-11, 2011. Proceedings" (pp. 183-192). Berlin: Springer.
dc.identifier.doi10.1007/978-3-642-25274-7_19
dc.identifier.isbn978-3-642-25273-7
dc.identifier.issn0302-9743 (Print)
dc.identifier.issn1611-3349 (Online)
dc.identifier.publicationfirstpage183
dc.identifier.publicationlastpage192
dc.identifier.publicationtitleAdvances in Artificial Intelligence
dc.identifier.publicationvolume7023
dc.identifier.urihttps://hdl.handle.net/10016/12968
dc.language.isoeng
dc.publisherSpringer
dc.relation.eventdateNovember 7-11, 2011
dc.relation.eventnumber14
dc.relation.eventplaceLa Laguna (Spain)
dc.relation.eventtitle14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA
dc.relation.projectIDGobierno de España. TIN2008-06701-C03-03
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-642-25274-7_19
dc.rights© Springer
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.titleUsing the relaxed plan heuristic to select goals in oversubscription planning problems
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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