Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences

Brewka, Gerhard

doi:10.1613/jair.284

Cited by 90 publications

(74 citation statements)

References 17 publications

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“…Most of the approaches propose an extension of Gelfond and Lifschitz's extended logic programming by adding preference information (Delgrande et al, 2003;Wang et al, 2000;Zhang & Foo, 1997). Other proposals attempt to extend the well founded semantics to logic programs with preferences (Brewka, 1996;Schauba & Wang, 2001), and an extension of van-Gelder's alternating fixpoint theory for logic programs with priorities has been proposed by Wang et al (2000). Gelfond and Son (1997) have proposed a methodology of reasoning with prioritized default in the language of logic programming under answer set semantics.…”

Section: Other Approachesmentioning

confidence: 99%

“…they are "external" to the logic program, whereas dynamic preferences appear within the logic program and are determined "on the fly". The most common form of preference consists in specifying preference conditions among rules (Brewka, 1996;Brewka & Eiter, 1999Delgrande, Schaub, & Tompits, 2000a, 2000bGelfond & Son, 1997;Schauba & Wang, 2001;, 2004Wang, Zhou, & Lin, 2000;Zhang & Foo, 1997), whereas, some recent proposals admit the expression of preference relations among atoms (Brewka, Niemela, & Truszczynski, 2003;Brewka, 2004;Sakama & Inoue, 2000;Wakaki et al, 2003). More sophisticated forms of preferences also allow the specification of priorities between conjunctions (disjunctions) of literals (Brewka et al, 2003;Delgrande et al, 2000a;Sakama & Inoue, 2000) and numerical penalties for suboptimal options (Brewka, 2004).…”

Section: Introductionmentioning

confidence: 99%

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On the Semantics of Logic Programs with Preferences

Greco

Trubitsyna

Zumpano

2006

Logics in Artificial Intelligence

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This work is a contribution to prioritized reasoning in logic programming in the presence of preference relations involving atoms. The technique, providing a new interpretation for prioritized logic programs, is inspired by the semantics of Prioritized Logic Programming and enriched with the use of structural information of preference of Answer Set Optimization Programming. Specifically, the analysis of the logic program is carried out together with the analysis of preferences in order to determine the choice order and the sets of comparable models. The new semantics is compared with other approaches known in the literature and complexity analysis is also performed, showing that, with respect to other similar approaches previously proposed, the complexity of computing preferred stable models does not increase.

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Section: Other Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Semantics of Logic Programs with Preferences

Greco

Trubitsyna

Zumpano

2006

Logics in Artificial Intelligence

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“…In fact, every ordered logic program can be transformed into a OCLP such that the answer set semantics reflects the credulous semantics of the OCLP. Dynamic preference in extended logic programs was introduced in [8] in order to obtain a better suited well-founded semantics. Although preferences are called dynamic they are not dynamic in our sense.…”

Section: Relationship To Other Approachesmentioning

confidence: 99%

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Vos

2004

Lecture Notes in Computer Science

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Abstract. Ordered Choice Logic Programming (OCLP) allows for dynamic preference-based decision-making with multiple alternatives without the need for any form of negation. This complete absence of negation does not weaken the language as both forms (classical and as-failure) can be intuitively simulated in the language and eliminated using a simple pre-processor, making it also an easy language for users less familiar with logic programming. The semantics of the language is based on the preference between alternatives, yielding both a skeptical and a credulous approach. In this paper we demonstrate how OCLPs can be translated to semi-negative logic programs such that, depending on the transformation, the answer sets of the latter correspond with the skeptical/credulous answer sets of the former. By providing such a mapping, we have a mechanism for implementing OCLP using answer set solvers like Smodels or dlv. We end with a discussion of the complexity of our system and the reasoning tasks it can perform.

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“…Further semantics for priorities in extended logic programming, which are not based on answer sets, have been proposed in (Nute, 1994;Analyti & Pramanik, 1995;Brewka, 1996;Prakken & Sartor, 1997). They have quite different foundations such as logical entrenchment and specificity (Nute, 1994), reliability handling (Analyti & Pramanik, 1995), well-founded semantics (Brewka, 1996), or defeasible argumentation (Prakken & Sartor, 1997).…”

Section: Further Approachesmentioning

confidence: 99%

“…They have quite different foundations such as logical entrenchment and specificity (Nute, 1994), reliability handling (Analyti & Pramanik, 1995), well-founded semantics (Brewka, 1996), or defeasible argumentation (Prakken & Sartor, 1997).…”

Section: Further Approachesmentioning

confidence: 99%

Using methods of declarative logic programming for intelligent information agents

Eiter¹,

Fink²,

Sabbatini³

et al. 2002

Theory and Practice of Logic Programming

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At present, the search for specific information on the World Wide Web is faced with several problems, which arise on the one hand from the vast number of information sources available, and on the other hand from their intrinsic heterogeneity, since standards are missing. A promising approach for solving the complex problems emerging in this context is the use of multi-agent systems of information agents, which cooperatively solve advanced information-retrieval problems. This requires advanced capabilities to address complex tasks, such as search and assessment of information sources, query planning, information merging and fusion, dealing with incomplete information, and handling of inconsistency.In this paper, our interest lies in the role which some methods from the field of declarative logic programming can play in the realization of reasoning capabilities for information agents. In particular, we are interested to see in how they can be used, extended, and further developed for the specific needs of this application domain. We review some existing systems and current projects, which typically address information-integration problems. We then focus on declarative knowledge-representation methods, and review and evaluate approaches and methods from logic programming and nonmonotonic reasoning for information agents. We discuss advantages and drawbacks, and point out the possible extensions and open issues.

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Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences

Cited by 90 publications

References 17 publications

On the Semantics of Logic Programs with Preferences

On the Semantics of Logic Programs with Preferences

Implementing Ordered Choice Logic Programming Using Answer Set Solvers

Using methods of declarative logic programming for intelligent information agents

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