An enhanced features extractor for a portfolio of constraint solvers - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

An enhanced features extractor for a portfolio of constraint solvers

Résumé

Recent research has shown that a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers. The solver selection is usually done by means of (un)supervised learning techniques which exploit features extracted from the problem specifica-tion. In this paper we present an useful and flexible framework that is able to extract an extensive set of features from a Constraint (Satisfaction/Optimization) Problem defined in possibly different modeling languages: MiniZinc, FlatZinc or XCSP.
Fichier principal
Vignette du fichier
sac_2014.pdf (184.82 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01089183 , version 1 (01-12-2014)

Identifiants

Citer

Roberto Amadini, Maurizio Gabbrielli, Jacopo Mauro. An enhanced features extractor for a portfolio of constraint solvers. SAC 2014, Mar 2014, Gyeongju, South Korea. pp.1357 - 1359, ⟨10.1145/2554850.2555114⟩. ⟨hal-01089183⟩

Collections

INRIA INRIA2
244 Consultations
149 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More