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Complex optimization in answer set programming

  • Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.

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Author details:Martin GebserORCiD, Roland KaminskiORCiD, Torsten H. SchaubORCiDGND
DOI:https://doi.org/10.1017/S1471068411000329
ISSN:1471-0684
Title of parent work (English):Theory and practice of logic programming
Publisher:Cambridge Univ. Press
Place of publishing:New York
Publication type:Article
Language:English
Year of first publication:2011
Publication year:2011
Release date:2017/03/26
Tag:Answer Set Programming; Complex optimization; Meta-Programming; Preference Handling
Volume:11
Issue:3
Number of pages:19
First page:821
Last Page:839
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik und Computational Science
Peer review:Referiert
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Informatik
External remark:Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 554
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