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Theory and Practice of Logic Programming
Article . 2003 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2003
License: arXiv Non-Exclusive Distribution
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A semantic framework for preference handling in answer set programming

Authors: Schaub, T; Wang, KW;

A semantic framework for preference handling in answer set programming

Abstract

We provide a semantic framework for preference handling in answer set programming. To this end, we introduce preference preserving consequence operators. The resulting fixpoint characterizations provide us with a uniform semantic framework for characterizing preference handling in existing approaches. Although our approach is extensible to other semantics by means of an alternating fixpoint theory, we focus here on the elaboration of preferences under answer set semantics. Alternatively, we show how these approaches can be characterized by the concept of order preservation. These uniform semantic characterizations provide us with new insights about interrelationships and moreover about ways of implementation.

39 pages. To appear in Theory and Practice of Logic Programming

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Keywords

FOS: Computer and information sciences, Logic in artificial intelligence, I.2.3, Computer Science - Artificial Intelligence, D.1.6, Institut für Informatik und Computational Science, Semantics in the theory of computing, Symbolic computation and algebraic computation, Logic programming, priorities., I.2.3; D.1.6, Mechanization of proofs and logical operations, Artificial Intelligence (cs.AI), answer set programming, preferences, Theory of computation, Theorem proving (deduction, resolution, etc.)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
Green
bronze