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Clingcon: The next generation*

Published online by Cambridge University Press:  28 June 2017

MUTSUNORI BANBARA ,
BENJAMIN KAUFMANN ,
MAX OSTROWSKI  and
TORSTEN SCHAUB
MUTSUNORI BANBARA
Affiliation:
Kobe University, Kobe, Japan (e-mail: banbara@kobe-u.ac.jp)
BENJAMIN KAUFMANN
Affiliation:
University of Potsdam, Potsdam, Germany (e-mails: kaufmann@cs.uni-potsdam.de, ostrowsk@cs.uni-potsdam.de)
MAX OSTROWSKI
Affiliation:
University of Potsdam, Potsdam, Germany (e-mails: kaufmann@cs.uni-potsdam.de, ostrowsk@cs.uni-potsdam.de)
TORSTEN SCHAUB
Affiliation:
University of Potsdam, Germany and INRIA Rennes, Rennes, France (e-mail: torsten@cs.uni-potsdam.de)
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Abstract

We present the third generation of the constraint answer set system clingcon, combining Answer Set Programming (ASP) with finite domain constraint processing (CP). While its predecessors rely on a black-box approach to hybrid solving by integrating the CP solver gecode, the new clingcon system pursues a lazy approach using dedicated constraint propagators to extend propagation in the underlying ASP solver clasp. No extension is needed for parsing and grounding clingcon's hybrid modeling language since both can be accommodated by the new generic theory handling capabilities of the ASP grounder gringo. As a whole, clingcon 3 is thus an extension of the ASP system clingo 5, which itself relies on the grounder gringo and the solver clasp. The new approach of clingcon offers a seamless integration of CP propagation into ASP solving that benefits from the whole spectrum of clasp's reasoning modes, including, for instance, multi-shot solving and advanced optimization techniques. This is accomplished by a lazy approach that unfolds the representation of constraints and adds it to that of the logic program only when needed. Although the unfolding is usually dictated by the constraint propagators during solving, it can already be partially (or even totally) done during preprocessing. Moreover, clingcon's constraint preprocessing and propagation incorporate several well-established CP techniques that greatly improve its performance. We demonstrate this via an extensive empirical evaluation contrasting, first, the various techniques in the context of CSP solving and, second, the new clingcon system with other hybrid ASP systems.

Keywords

Constraint Answer Set Programming (CASP)Answer Set Programming (ASP)Sat Modulo Theories (SMT)Constraint Programming (CP)
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 17 , Issue 4 , July 2017 , pp. 408 - 461
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

†

The author is currently affiliated with the Simon Fraser University, Canada, and Griffith University, Australia.

*

This work was partially funded by JSPS (KAKENHI 15K00099) and DFG (SCHA 550/9).

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