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Modeling and Language Extensions

  • Answer set programming (ASP) has emerged as an approach to declarative problem solving based on the stable model semantics for logic programs. The basic idea is to represent a computational problem by a logic program, formulating constraints in terms of rules, such that its answer sets correspond to problem solutions. To this end, ASP combines an expressive language for high-level modeling with powerful low-level reasoning capacities, provided by off-the-shelf tools. Compact problem representations take advantage of genuine modeling features of ASP, including (first-order) variables, negation by default, and recursion. In this article, we demonstrate the ASP methodology on two example scenarios, illustrating basic as well as advanced modeling and solving concepts. We also discuss mechanisms to represent and implement extended kinds of preferences and optimization. An overview of further available extensions concludes the article.

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Author details:Martin GebserORCiD, Torsten H. SchaubORCiDGND
ISSN:0738-4602
Title of parent work (English):AI magazine
Publisher:Association for the Advancement of Artificial Intelligence
Place of publishing:Menlo Park
Publication type:Article
Language:English
Year of first publication:2016
Publication year:2016
Release date:2020/03/22
Volume:37
Number of pages:12
First page:33
Last Page:44
Funding institution:DFG [SCHA 550/8, SCHA 550/9]
Peer review:Referiert
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik
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