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Model enumeration in propositional circumscription via unsatisfiable core analysis*

Published online by Cambridge University Press:  22 August 2017

MARIO ALVIANO
MARIO ALVIANO*
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: alviano@mat.unical.it)
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Abstract

Many practical problems are characterized by a preference relation over admissible solutions, where preferred solutions are minimal in some sense. For example, a preferred diagnosis usually comprises a minimal set of reasons that is sufficient to cause the observed anomaly. Alternatively, a minimal correction subset comprises a minimal set of reasons whose deletion is sufficient to eliminate the observed anomaly. Circumscription formalizes such preference relations by associating propositional theories with minimal models. The resulting enumeration problem is addressed here by means of a new algorithm taking advantage of unsatisfiable core analysis. Empirical evidence of the efficiency of the algorithm is given by comparing the performance of the resulting solver, circumscriptino, with hclasp, camus_mcs, lbx and mcsls on the enumeration of minimal models for problems originating from practical applications.

Keywords

Circumscriptionminimal model enumerationminimal correction subsetsminimal intervention strategiesunsatisfiable core analysis
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 17 , Special Issue 5-6: 33rd International Conference on Logic Programming , September 2017 , pp. 708 - 725
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

*

This research has been partially supported by the Italian Ministry for Economic Development (MISE) under project “PIUCultura – Paradigmi Innovativi per l'Utilizzo della Cultura” (no. F/020016/01-02/X27), and under project “Smarter Solutions in the Big Data World (S2BDW)” (no. F/050389/01-03/X32) funded within the call “HORIZON2020” PON I&C 2014-2020, and by Gruppo Nazionale per il Calcolo Scientifico (GNCS-INdAM).

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