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Reducing fuzzy answer set programming to model finding in fuzzy logics

Published online by Cambridge University Press:  21 June 2011

JEROEN JANSSEN
Affiliation:
Department of Computer Science, Vrije Universiteit Brussel Pleinlaan 2, 1050 Brussels, Belgium (e-mail: jeroen.janssen@vub.ac.be, dirk.vermeir@vub.ac.be)
DIRK VERMEIR
Affiliation:
Department of Computer Science, Vrije Universiteit Brussel Pleinlaan 2, 1050 Brussels, Belgium (e-mail: jeroen.janssen@vub.ac.be, dirk.vermeir@vub.ac.be)
STEVEN SCHOCKAERT
Affiliation:
Department of Applied Mathematics and Computer Science, Universiteit Gent Krijgslaan 281, 9000 Ghent, Belgium (e-mail: steven.schockaert@ugent.be)
MARTINE DE COCK
Affiliation:
Institute of Technology, University of Washington 1900 Commerce Street, Tacoma, WA 98402, USA (e-mail: mdecock@u.washington.edu)

Abstract

In recent years, answer set programming (ASP) has been extended to deal with multivalued predicates. The resulting formalismsallow for the modeling of continuous problems as elegantly as ASP allows for the modeling of discrete problems, by combining thestable model semantics underlying ASP with fuzzy logics. However, contrary to the case of classical ASP where manyefficient solvers have been constructed, to date there is no efficient fuzzy ASP solver. A well-knowntechnique for classical ASP consists of translating an ASP program P to a propositional theory whose models exactlycorrespond to the answer sets of P. In this paper, we show how this idea can be extended to fuzzy ASP, paving the wayto implement efficient fuzzy ASP solvers that can take advantage of existing fuzzy logic reasoners.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2011

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