Publication:
The IBaCoP planning system: instance-based configured portfolios

Simple item page
dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Planificación y Aprendizajees
dc.contributor.authorCenamor Guijarro, Isabel Rosario
dc.contributor.authorRosa Turbides, Tomás Eduardo de la
dc.contributor.authorFernández Rebollo, Fernando
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2020-03-02T10:30:32Z
dc.date.available2020-03-02T10:30:32Z
dc.date.issued2016-08-01
dc.description.abstractSequential planning portfolios are very powerful in exploiting the complementary strength of different automated planners. The main challenge of a portfolio planner is to define which base planners to run, to assign the running time for each planner and to decide in what order they should be carried out to optimize a planning metric. Portfolio configurations are usually derived empirically from training benchmarks and remain fixed for an evaluation phase. In this work, we create a per-instance configurable portfolio, which is able to adapt itself to every planning task. The proposed system pre-selects a group of candidate planners using a Pareto-dominance filtering approach and then it decides which planners to include and the time assigned according to predictive models. These models estimate whether a base planner will be able to solve the given problem and, if so, how long it will take. We define different portfolio strategies to combine the knowledge generated by the models. The experimental evaluation shows that the resulting portfolios provide an improvement when compared with non-informed strategies. One of the proposed portfolios was the winner of the Sequential Satisficing Track of the International Planning Competition held in 2014.en
dc.description.sponsorshipWe thank the authors of the base planners because our work is based largely on their previous effort. This work has been partially supported by the Spanish projects TIN2011-27652-C03-02, TIN2012-38079-C03-02 and TIN2014-55637-C2-1-R.en
dc.format.extent34
dc.identifier.bibliographicCitationCenamor, I., Rosa, T. de la, Fernández, F. (2016). The IBaCoP Planning System: Instance-Based Configured Portfolios, Journal of Artificial Intelligence Research, 56, pp. 657-691en
dc.identifier.doihttps://doi.org/10.1613/jair.5080
dc.identifier.issn1076-9757
dc.identifier.publicationfirstpage657
dc.identifier.publicationlastpage691
dc.identifier.publicationtitleJournal of artificial intelligence Researchen
dc.identifier.publicationvolume56
dc.identifier.urihttps://hdl.handle.net/10016/29809
dc.identifier.uxxiAR/0000019626
dc.language.isoenges
dc.publisherAI Access Foundationen
dc.relation.projectIDGobierno de España. TIN2011-27652-C03-02es
dc.relation.projectIDGobierno de España. TIN2012- 38079-C03-02es
dc.relation.projectIDGobierno de España. TIN2014-55637-C2-1-Res
dc.rights© 2016 AI Access Foundationes
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherAlgorithmen
dc.subject.otherSelectionen
dc.subject.otherDomainsen
dc.subject.otherDeterministic parten
dc.titleThe IBaCoP planning system: instance-based configured portfoliosen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ibacop_JAIR_2016.pdf
Size:
678.19 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
DI - PLG - Artículos de Revistas