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Conflict-driven ASP solving with external sources

Published online by Cambridge University Press:  05 September 2012

THOMAS EITER ,
MICHAEL FINK ,
THOMAS KRENNWALLNER  and
CHRISTOPH REDL
THOMAS EITER
Affiliation:
Institut für Informationssysteme, Technische Universität WienFavoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: [email protected], [email protected], [email protected], [email protected])
MICHAEL FINK
Affiliation:
Institut für Informationssysteme, Technische Universität WienFavoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: [email protected], [email protected], [email protected], [email protected])
THOMAS KRENNWALLNER
Affiliation:
Institut für Informationssysteme, Technische Universität WienFavoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: [email protected], [email protected], [email protected], [email protected])
CHRISTOPH REDL
Affiliation:
Institut für Informationssysteme, Technische Universität WienFavoritenstraße 9-11, A-1040 Vienna, Austria (e-mail: [email protected], [email protected], [email protected], [email protected])
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Abstract

Answer Set Programming (ASP) is a well-known problem solving approach based on nonmonotonic logic programs and efficient solvers. To enable access to external information, hex-programs extend programs with external atoms, which allow for a bidirectional communication between the logic program and external sources of computation (e.g., description logic reasoners and Web resources). Current solvers evaluate hex-programs by a translation to ASP itself, in which values of external atoms are guessed and verified after the ordinary answer set computation. This elegant approach does not scale with the number of external accesses in general, in particular in presence of nondeterminism (which is instrumental for ASP). In this paper, we present a novel, native algorithm for evaluating hex-programs which uses learning techniques. In particular, we extend conflict-driven ASP solving techniques, which prevent the solver from running into the same conflict again, from ordinary to hex-programs. We show how to gain additional knowledge from external source evaluations and how to use it in a conflict-driven algorithm. We first target the uninformed case, i.e., when we have no extra information on external sources, and then extend our approach to the case where additional meta-information is available. Experiments show that learning from external sources can significantly decrease both the runtime and the number of considered candidate compatible sets.

Keywords

Answer set programmingnonmonotonic reasoningconflict-driven clause learning
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 12 , Issue 4-5: 28th International Conference on Logic Programming , July 2012 , pp. 659 - 679
Copyright
Copyright © Cambridge University Press 2012

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