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An algorithm for computing the stable model semantics of logic programs is developed. It is shown that one can extend the semantics and the algorithm to handle new and more expressive types of rules. Emphasis is placed on the use of…

Logic in Computer Science · Computer Science 2007-05-23 Patrik Simons

We present a method for computing stable models of normal logic programs, i.e., logic programs extended with negation, in the presence of predicates with arbitrary terms. Such programs need not have a finite grounding, so traditional…

Logic in Computer Science · Computer Science 2017-09-05 Kyle Marple , Elmer Salazar , Gopal Gupta

This paper studies the stable model semantics of logic programs with (abstract) constraint atoms and their properties. We introduce a succinct abstract representation of these constraint atoms in which a constraint atom is represented…

Artificial Intelligence · Computer Science 2009-05-01 Yi-Dong Shen , Jia-Huai You , Li-Yan Yuan

This paper introduces a fundamental result, which is relevant for Answer Set programming, and planning. For the first time since the definition of the stable model semantics, the class of logic programs for which a stable model exists is…

Artificial Intelligence · Computer Science 2007-05-23 Stefania Costantini

The Smodels system implements the stable model semantics for normal logic programs. It handles a subclass of programs which contain no function symbols and are domain-restricted but supports extensions including built-in functions as well…

Artificial Intelligence · Computer Science 2007-05-23 Ilkka Niemela , Patrik Simons , Tommi Syrjanen

The rules associated with propositional logic programs and the stable model semantics are not expressive enough to let one write concise programs. This problem is alleviated by introducing some new types of propositional rules. Together…

Logic in Computer Science · Computer Science 2007-05-23 Patrik Simons

A logic programming paradigm which expresses solutions to problems as stable models has recently been promoted as a declarative approach to solving various combinatorial and search problems, including planning problems. In this paradigm,…

Artificial Intelligence · Computer Science 2007-05-23 Maurice Bruynooghe

The stable model semantics had been recently generalized to non-Herbrand structures by several works, which provides a unified framework and solid logical foundations for answer set programming. This paper focuses on the expressiveness of…

Artificial Intelligence · Computer Science 2014-12-03 Heng Zhang , Yan Zhang

Stable Logic Programming (SLP) is an emergent, alternative style of logic programming: each solution to a problem is represented by a stable model of a deductive database/function-free logic program encoding the problem itself. Several…

Artificial Intelligence · Computer Science 2014-02-25 Gianpaolo Brignoli , Stefania Costantini , Ottavio D'Antona , Alessandro Provetti

We propose a stable model semantics for higher-order logic programs. Our semantics is developed using Approximation Fixpoint Theory (AFT), a powerful formalism that has successfully been used to give meaning to diverse non-monotonic…

Logic in Computer Science · Computer Science 2025-01-22 Bart Bogaerts , Angelos Charalambidis , Giannos Chatziagapis , Babis Kostopoulos , Samuele Pollaci , Panos Rondogiannis

Logic programming, as exemplified by datalog, defines the meaning of a program as its unique smallest model: the deductive closure of its inference rules. However, many problems call for an enumeration of models that vary along some set of…

Programming Languages · Computer Science 2024-11-22 Chris Martens , Robert J. Simmons , Michael Arntzenius

Answer set programming is one of the most praised frameworks for declarative programming in general and non-monotonic reasoning in particular. There has been many efforts to extend stable model semantics so that answer set programs can use…

Logic in Computer Science · Computer Science 2012-12-04 Shahab Tasharrofi

The logical semantics of normal logic programs has traditionally been based on the notions of Clark's completion and two-valued or three-valued canonical models, including supported, stable, regular, and well-founded models. Two-valued…

Logic in Computer Science · Computer Science 2026-01-08 Van-Giang Trinh , Sylvain Soliman , François Fages , Belaid Benhamou

The main contribution of the present paper is the introduction of a simple yet expressive hybrid-dynamic logic for describing quantum programs. This version of quantum logic can express quantum measurements and unitary evolutions of states…

Logic in Computer Science · Computer Science 2024-06-05 Daniel Gaina

Model counting is the problem of computing the number of models that satisfy a given propositional theory. It has recently been applied to solving inference tasks in probabilistic logic programming, where the goal is to compute the…

Artificial Intelligence · Computer Science 2014-11-21 Rehan Abdul Aziz , Geoffrey Chu , Christian Muise , Peter Stuckey

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modelling tools to…

Artificial Intelligence · Computer Science 2023-04-18 Pietro Totis , Angelika Kimmig , Luc De Raedt

It is widely acknowledged that function symbols are an important feature in answer set programming, as they make modeling easier, increase the expressive power, and allow us to deal with infinite domains. The main issue with their…

Artificial Intelligence · Computer Science 2020-02-19 Marco Calautti , Sergio Greco , Cristian Molinaro , Irina Trubitsyna

Part of the theory of logic programming and nonmonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more…

Artificial Intelligence · Computer Science 2007-05-23 Pascal Hitzler , Matthias Wendt

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there is constraint logic programming which computes a solution as an answer substitution to a query containing the…

Artificial Intelligence · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Marc Denecker

Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there are definite programs and constraint logic programs that compute a solution as an answer substitution to a query…

Logic in Computer Science · Computer Science 2007-05-23 Nikolay Pelov , Emmanuel De Mot , Maurice Bruynooghe
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