Reducing fuzzy answer set programming to model finding in fuzzy logics

@article{Janssen2011ReducingFA,
  title={Reducing fuzzy answer set programming to model finding in fuzzy logics},
  author={Jeroen Janssen and Dirk Vermeir and Steven Schockaert and Martine De Cock},
  journal={Theory and Practice of Logic Programming},
  year={2011},
  volume={12},
  pages={811 - 842}
}
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… 
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17 Citations
Highly Influential Citations
3
Background Citations
8
Methods Citations
4

17 Citations

Foundations of a DPLL-Based Solver for Fuzzy Answer Set Programs

The inner works of a DPLL-based fuzzy SAT solver for propositional product logic should provide foundations for the technical implementation of the solver, utilizing the fuzzy generalization of the DPLL algorithm.

A finite-valued solver for disjunctive fuzzy answer set programs

This paper proposes an implementation of FASP based on a reduction to classical ASP, and develops a prototype implementation of this method, believed to be the first solver for disjunctive FASp programs.

Solving Fuzzy Answer Set Programs in Product Logic

This work investigates the methods used in state-of-the-art classical ASP solvers with the aim of designing a FASP solver for product propositional logic and bases its approach on the conversion into fuzzy SAT (satisfiability problem) and the fuzzy generalization of the DPLL algorithm.

Fuzzy answer set computation via satisfiability modulo theories

A translation of FASP programs into satisfiability modulo theories (SMT), which in general produces quantified formulas because of the minimality of the semantics, is analyzed.

Aggregated Fuzzy Answer Set Programming

This paper develops an alternative, based on aggregator functions that specify which (combination of) rules are most important to satisfy, that extends upon previous work by allowing aggregator expressions to define partially ordered preferences, and by the use of a fixpoint semantics.

Solving satisfiability in fuzzy logics with evolution strategies

This paper proposes a new incomplete solver, based on a class of continuous optimization algorithms called evolution strategies, and shows experimentally that this method is an important contribution to the state of the art in incomplete fuzzy-SAT solvers.

Solving satisfiability in fuzzy logics by mixing CMA-ES

This paper proposes new benchmark problems and analyzes the function landscape of different problem classes, focussing on plateaus, and develops Mixing CMA-ES (M-CMA- ES), an extension to C MA-ES that is well suited to solving problems with many large plateaus.

Minimal Undefinedness for Fuzzy Answer Sets

This paper presents algorithms that minimize undefinedness of fuzzy answer sets, and implements them through the minimization of a measure of undefinedness.

On the Computation of Paracoherent Answer Sets

Several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework and an empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given.

A core language for fuzzy answer set programming

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