From Declarative Set Constraint Models to “Good” SAT Instances - Université d'Angers Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

From Declarative Set Constraint Models to “Good” SAT Instances

Eric Monfroy

Résumé

On the one hand, Constraint Satisfaction Problems allow one to declaratively model problems. On the other hand, propositional satisfiability problem (SAT) solvers can handle huge SAT instances. We thus present a technique to declaratively model set constraint problems, to reduce them, and to encode them into ”good” SAT instances. We illustrate our technique on the well-known nqueens problem. Our technique is simpler, more expressive, and less error-prone than direct hand modeling. The SAT instances that we automatically generate are rather small w.r.t. hand-written instances.

Fichier principal
Vignette du fichier
aisc2014.pdf (307.44 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03352573 , version 1 (13-10-2021)

Identifiants

Citer

Frédéric Lardeux, Eric Monfroy. From Declarative Set Constraint Models to “Good” SAT Instances. Artificial Intelligence and Symbolic Computation, 2014, Séville, Spain. pp.76-87, ⟨10.1007/978-3-319-13770-4_8⟩. ⟨hal-03352573⟩

Collections

UNIV-ANGERS LERIA
30 Consultations
37 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More