Aggregated Fuzzy Answer Set Programming

  • Authors:

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

  • Affiliations:

  • Department of Computer Science, Vrije Universiteit Brussel, VUB, Brussel, Belgium 1050;Department of Applied Mathematics and Computer Science, Universiteit Gent, UGent, Gent, Belgium 9000;Department of Computer Science, Vrije Universiteit Brussel, VUB, Brussel, Belgium 1050;Department of Applied Mathematics and Computer Science, Universiteit Gent, UGent, Gent, Belgium 9000

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Fuzzy Answer Set Programming (FASP) is an extension of answer set programming (ASP), based on fuzzy logic. It allows to encode continuous optimization problems in the same concise manner as ASP allows to model combinatorial problems. As a result of its inherent continuity, rules in FASP may be satisfied or violated to certain degrees. Rather than insisting that all rules are fully satisfied, we may only require that they are satisfied partially, to the best extent possible. However, most approaches that feature partial rule satisfaction limit themselves to attaching predefined weights to rules, which is not sufficiently flexible for most real-life applications. In this paper, we develop an alternative, based on aggregator functions that specify which (combination of) rules are most important to satisfy. We extend upon previous work by allowing aggregator expressions to define partially ordered preferences, and by the use of a fixpoint semantics.