Reducing fuzzy answer set programming to model finding in fuzzy logics

  • Authors:

  • Jeroen Janssen;Dirk Vermeir;Steven Schockaert;Martine De cock

  • Affiliations:

  • Department of computer science, vrije universiteit brussel pleinlaan 2, 1050 brussels, belgium (e-mail: jeroen.janssen@vub.ac.be, dirk.vermeir@vub.ac.be);Department of computer science, vrije universiteit brussel pleinlaan 2, 1050 brussels, belgium (e-mail: jeroen.janssen@vub.ac.be, dirk.vermeir@vub.ac.be);Department of applied mathematics and computer science, universiteit gent krijgslaan 281, 9000 ghent, belgium (e-mail: steven.schockaert@ugent.be);Institute of technology, university of washington 1900 commerce street, tacoma, wa 98402, usa (e-mail: mdecock@u.washington.edu)

  • Venue:
  • Theory and Practice of Logic Programming
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

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.