Justification and debugging of answer set programs in ASP

Elkhatib, Omar; Pontelli, Enrico; Son, Tran Cao

doi:10.1145/1085130.1085137

Cited by 8 publications

(7 citation statements)

References 18 publications

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“…This paper continues the work initiated in Elkhatib et al (2005), by proposing a more advanced and sound notion of offline justification, developing the concept of online justification and introducing these concepts in Smodels. The approach differs significantly from the recently introduced approach to debugging ASP programs in Brain et al (2007a).…”

Section: Debugging Logic Programs Under Answer Set Semanticsmentioning

confidence: 63%

“…2004;Anger et al . In this sense, this paper shares the spirit of other attempts in developing tools and methodologies for understanding and debugging of ASP programs 1 , as in (Elkhatib et al 2005;Brain et al 2007aBrain et al , 2007bPerri et al 2007). On the other hand, a source of difficulties in learning to use ASP lies in the lack of methodologies and tools which can assist users in understanding a program's behavior and debugging it.…”

Section: Examplementioning

confidence: 68%

“…This situation is especially difficult when the program execution produces unexpected outcomes, e.g., incorrect or missing answer sets. In this sense, this paper shares the spirit of other attempts in developing tools and methodologies for understanding and debugging of ASP programs 1 , as in (Elkhatib et al 2005;Brain et al 2007aBrain et al , 2007bPerri et al 2007).…”

Section: Examplementioning

confidence: 68%

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Justifications for logic programs under answer set semantics

Pontelli¹,

Son²,

Elkhatib³

2009

Theory and Practice of Logic Programming

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Link to this article: http://journals.cambridge.org/abstract_S1471068408003633How to cite this article: ENRICO PONTELLI, TRAN CAO SON and OMAR ELKHATIB (2009). Justications for logic programs under answer set semantics. AbstractThe paper introduces the notion of offline justification for answer set programming (ASP). Justifications provide a graph-based explanation of the truth value of an atom with respect to a given answer set. The paper extends also this notion to provide justification of atoms during the computation of an answer set (on-line justification) and presents an integration of online justifications within the computation model of Smodels. Offline and online justifications provide useful tools to enhance understanding of ASP, and they offer a basic data structure to support methodologies and tools for debugging answer set programs. A preliminary implementation has been developed in ASP − PROLOG.Proof. The result is obvious from the definition of offline e-graph and from the fact that J − ∩ TA P (M) ⊆ TA P (M). Proposition 4. Let M 0 , . . . , M k be a general complete computation and S(M 0 ), . . . , S(M k ) be an online justification of the computation. Then, for each atom a in M k , the egraph of a in S(M k ) is an offline justification of a w.r.t. M k and TA P (M k ).Proof. This follows immediately from Lemma 5.2, the construction of the snapshots S(M i ), the fact that M i M k for every k, and M k being an answer set of P .

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Section: Debugging Logic Programs Under Answer Set Semanticsmentioning

confidence: 63%

Section: Examplementioning

confidence: 68%

Section: Examplementioning

confidence: 68%

See 1 more Smart Citation

Justifications for logic programs under answer set semantics

Pontelli¹,

Son²,

Elkhatib³

2009

Theory and Practice of Logic Programming

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“…We review these approaches in Sections 4.1-4.3. Another approach makes use of the unsatisfiable core feature of the There used to be an implementation of off-line justifications (El-Khatib et al 2005). Unfortunately, this implementation is lost and it is not available anymore.…”

Section: Debugging Of Inconsistent Logic Programsmentioning

confidence: 99%

“…There also used to be an implementation of off-line justifications(El-Khatib et al 2005), but this is not available anymore. In this survey, we have limited ourselves to normal extended logic programs.…”

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confidence: 99%

Answering the “why” in answer set programming – A survey of explanation approaches

Fandinno¹,

Schulz²

2019

Theory and Practice of Logic Programming

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Artificial intelligence (AI) approaches to problem-solving and decision-making are becoming more and more complex, leading to a decrease in the understandability of solutions. The European Union’s new General Data Protection Regulation tries to tackle this problem by stipulating a “right to explanation” for decisions made by AI systems. One of the AI paradigms that may be affected by this new regulation is answer set programming (ASP). Thanks to the emergence of efficient solvers, ASP has recently been used for problem-solving in a variety of domains, including medicine, cryptography, and biology. To ensure the successful application of ASP as a problem-solving paradigm in the future, explanations of ASP solutions are crucial. In this survey, we give an overview of approaches that provide an answer to the question ofwhyan answer set is a solution to a given problem, notably off-line justifications, causal graphs, argumentative explanations, and why-not provenance, and highlight their similarities and differences. Moreover, we review methods explaining why a set of literals isnotan answer set or why no solution exists at all.

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Answer Set Programming

Faber

Leone

Ricca

2008

Wiley Encyclopedia of Computer Science and Engineering

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Answer set programming (ASP) evolved from logic programming, deductive databases, knowledge representation, and nonmonotonic reasoning, and it serves as a flexible language for solving problems in a declarative way. The user does not need to provide an algorithm for solving the problem; rather, it is sufficient that (s)he specifies the properties of the desired solution for its computation. ASP is highly expressive and allows us to solve problems even beyond the complexity class NP. The main representation feature of ASP are rules, which are interpreted according to common sense principles. In ASP, one writes a program, that is, a collection of rules, which represent a problem to be solved. This program, together with some input, usually expressed using factual rules, possesses a collection of models (possibly also no model), called answer sets, which correspond to the solutions of the modeled problem. Efficient systems for computing answer sets are available and have stimulated the development of applications relying on ASP, in both academia and, business. The field of ASP is growing, and several extensions of the basic language have been proposed and used in applications.

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Justification and debugging of answer set programs in ASP

Cited by 8 publications

References 18 publications

Justifications for logic programs under answer set semantics

Justifications for logic programs under answer set semantics

Answering the “why” in answer set programming – A survey of explanation approaches

Answer Set Programming

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