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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 2-3/2018

01-08-2018 | Editorial

Special Issue on Answer Set Programming

Authors: Torsten Schaub, Stefan Woltran

Published in: KI - Künstliche Intelligenz | Issue 2-3/2018

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Excerpt

“What is Answer Set Programming? And what can it do for me?” might have been the questions you had in mind when taking up this special issue. Let’s start with your first question. Answer Set Programming, or ASP for short, is a rule-based formalism for modeling and solving knowledge-intense combinatorial (optimization) problems. What makes ASP attractive is its combination of a declarative modeling language with highly effective solving engines. This allows you to concentrate on specifying—rather than programming the algorithm for solving—a problem at hand. Historically, ASP has its roots in deductive databases, logic programming, and non-monotonic reasoning; its solving engines draw on the same technology as solvers for satisfiability testing. Given this origin, ASP is tailored to support closed as well as open world reasoning, which makes it predestined for knowledge representation and reasoning tasks. …
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Metadata
Title
Special Issue on Answer Set Programming
Authors
Torsten Schaub
Stefan Woltran
Publication date
01-08-2018
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2-3/2018
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-018-0554-8

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