Approximating Extended Answer Sets

Authors:
Davy Van Nieuwenborgh;Stijn Heymans;Dirk Vermeir
Affiliations:
-;Digital Enterprise Research Institute (DERI), University of Innsbruck, Austria. Email: stijn.heymans@deri.org;Departement of Computer Science, Vrije Universiteit Brussel (VUB), Pleinlaan 2, B1050 Brussels, Belgium. Email: {dvnieuwe,dvermeir}@vub.ac.be
Venue:
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Year:
2006

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Abstract

We present an approximation theory for the extended answer set semantics, using the concept of an approximation constraint. Intuitively, an approximation constraint, while satisfied by a “perfect” solution, may be left unsatisfied in an approximate extended answer set. Approximations improve as the number of unsatisfied constraints decreases. We show how the framework can also capture the classical answer set semantics, thus providing an approximative version of the latter.