Introducing Constraint Well-Founded Semantics for Constraint Logic Programming Through Rewriting Transformations

Constraint Answer Set Programming (CASP) combines Answer Set Programming (ASP) and Constraint Programming (CP) to offer a powerful framework for solving complex problems. While there exists various ways to represent CASP problems, fusing both in a way that benefits both communities remains difficult to this day. To address this, we propose to extend the Well Founded Semantics (WFS) to propositional constraint logic programs. To this end, we present an iterative process involving elementary rewriting transformations to simplify the program iteratively. Our method aims to give a better description of the interactions between ASP and CP inside of a constraint logic program.

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Published
2024-10-28
DOI
https://doi.org/10.1109/ictai62512.2024.00062
Primary Topic
Semantic Web and Ontologies
Type
article
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article

Introducing Constraint Well-Founded Semantics for Constraint Logic Programming Through Rewriting Transformations

Eric Monfroy, Bryan Garreau, Igor Stéphan, Martin Dieguez Lodeiro
Semantic Web and Ontologies
article

Introducing Constraint Well-Founded Semantics for Constraint Logic Programming Through Rewriting Transformations

Eric Monfroy, Bryan Garreau, Igor Stéphan, Martin Dieguez Lodeiro
article en

Abstract

Constraint Answer Set Programming (CASP) combines Answer Set Programming (ASP) and Constraint Programming (CP) to offer a powerful framework for solving complex problems. While there exists various ways to represent CASP problems, fusing both in a way that benefits both communities remains difficult to this day. To address this, we propose to extend the Well Founded Semantics (WFS) to propositional constraint logic programs. To this end, we present an iterative process involving elementary rewriting transformations to simplify the program iteratively. Our method aims to give a better description of the interactions between ASP and CP inside of a constraint logic program.

Université d'Angers (FR)
Openalex Percentile: Top 76%
Semantic Web and Ontologies
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