Smodels with CLP and Its Applications: A Simple and Effective Approach to Aggregates in ASP

Elkabani, Islam; Pontelli, Enrico; Son, Tran Cao

doi:10.1007/978-3-540-27775-0_6

Cited by 26 publications

(29 citation statements)

References 9 publications

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“…The motivation for this investigation arises from the successful use of both paradigms in dealing with various classes of combinatorial problems, and the need to better understand their respective strengths and weaknesses. Ultimately, we hope this work will provide indication for integration and cooperation between the two paradigms (e.g., along the lines of [6]). …”

Section: Introductionmentioning

confidence: 91%

A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems

2005

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Abstract. This paper presents experimental comparisons between declarative encodings of various computationally hard problems in both Answer Set Programming (ASP) and Constraint Logic Programming (CLP) over finite domains. The objective is to identify how the solvers in the two domains respond to different problems, highlighting strengths and weaknesses of their implementations and suggesting criteria for choosing one approach versus the other. Ultimately, the work in this paper is expected to lay the ground for transfer of concepts between the two domains (e.g., suggesting ways to use CLP in the execution of ASP).

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Section: Introductionmentioning

confidence: 91%

A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems

2005

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“…(9) nth(IdfA,Nodes,A),nth(IdfA,Vars,ColA), (10) nth(IdfB,Nodes,B),nth(IdfB,Vars,ColB), (11) ColA #\= ColB, (12) constraints(R, Nodes, Vars). (9)- (10)).…”

Section: Clp(fd) Encodingmentioning

confidence: 99%

“…The motivation for this investigation arises from the successful use of both paradigms in dealing with various classes of combinatorial problems, and the need to better understand their respective strengths and weaknesses. Ultimately, we hope this work will indicate methods for integration and cooperation between the two paradigms (e.g., along the lines of [10,11]). …”

Section: Introductionmentioning

confidence: 99%

An empirical study of constraint logic programming and answer set programming solutions of combinatorial problems

Dovier

Formisano

Pontelli

2009

Journal of Experimental & Theoretical Artificial Intelligen

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This paper presents experimental comparisons between the declarative encodings of various computationally hard problems in both Answer Set Programming (ASP) and Constraint Logic Programming over finite domains (CLP(FD)). The objective is to investigate how the solvers in the two domains respond to different problems, highlighting strengths and weaknesses of their implementations and suggesting criteria for choosing one approach versus the other. Ultimately, the work in this paper is expected to lay the foundations for transfer of technology between the two domains, e.g., suggesting ways to use CLP(FD) in the execution of ASP.

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“…In recent years, researchers have paid particular attention to extensions of ASP with means to model aggregate constraints in particular, and constraints on sets in general (Calimeri et al 2005;Denecker et al 2001;Elkabani et al 2004;Elkabani et al 2005;Faber et al 2004;Ferraris 2005;Liu et al 2007;Liu and Truszczynski 2005;Liu and Truszczynski 2006;Marek et al 2008; element (set inclusive) in 2 D \ {∅} is a singleton in 2 D . In this case, any minimal element B in 2 D and D form a pair with B being the bottom element and D being the top.…”

Section: Introductionmentioning

confidence: 99%

Characterizations of stable model semantics for logic programs with arbitrary constraint atoms

Shen¹,

You²,

Yuan³

2009

Theory and Practice of Logic Programming

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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 compactly. We show two applications. First, under this representation of constraint atoms, we generalize the Gelfond-Lifschitz transformation and apply it to define stable models (also called answer sets) for logic programs with arbitrary constraint atoms. The resulting semantics turns out to coincide with the one defined by Son et al., which is based on a fixpoint approach. One advantage of our approach is that it can be applied, in a natural way, to define stable models for disjunctive logic programs with constraint atoms, which may appear in the disjunctive head as well as in the body of a rule. As a result, our approach to the stable model semantics for logic programs with constraint atoms generalizes a number of previous approaches. Second, we show that our abstract representation of constraint atoms provides a means to characterize dependencies of atoms in a program with constraint atoms, so that some standard characterizations and properties relying on these dependencies in the past for logic programs with ordinary atoms can be extended to logic programs with constraint atoms.

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Smodels with CLP and Its Applications: A Simple and Effective Approach to Aggregates in ASP

Cited by 26 publications

References 9 publications

A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems

A Comparison of CLP(FD) and ASP Solutions to NP-Complete Problems

An empirical study of constraint logic programming and answer set programming solutions of combinatorial problems

Characterizations of stable model semantics for logic programs with arbitrary constraint atoms

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