Extending Answer Set Programming using Generalized Possibilistic Logic

Didier Dubois (1, 2) , Henri Prade (1, 2) , Steven Schockaert (3)

1 IRIT-ADRIA - Argumentation, Décision, Raisonnement, Incertitude et Apprentissage
2 CNRS - Centre National de la Recherche Scientifique
3 Cardiff University

Answer set programming (ASP) is a form of logic programming in which negation-as-failure is defined in a purely declarative way, based on the notion of a stable model. This short paper briefly explains how a recent generalization of possibilistic logic (GPL) can be used to characterize the semantics of answer set programming. This characterization has several advantages over existing characterizations of the stable model semantics. First, unlike reduct-based approaches, it does not rely on a syntactic procedure: we can directly characterize answer sets based on the minimally specific models of a GPL theory. Second, GPL enables us to study extensions of ASP in an intuitive way: unlike in existing generalizations of ASP such as equilibrium logic and autoepistemic logic, all formulas in GPL have a meaning which is intuitively clear. Finally, being based on possibilistic logic, GPL offers a natural way of dealing with uncertainty in answer set programs.

Mots clés: Logic

Domaines: Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Logique en informatique [cs.LO]; Informatique et langage [cs.CL]

Didier Dubois, Henri Prade, Steven Schockaert. Extending Answer Set Programming using Generalized Possibilistic Logic. IJCAI Workshop 13 Ontologies and Logic Programming for Query Answering (ONTOLP 2015), Jul 2015, Buenos Aires, Argentina. pp. 8-12. ⟨hal-01287713⟩