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Finding a Collection of MUSes Incrementally

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Integration of AI and OR Techniques in Constraint Programming (CPAIOR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9676))

Abstract

Minimal Unsatisfiable Sets (MUSes) are useful in a number of applications. However, in general there are many different MUSes, and each application might have different preferences over these MUSes. Typical Muser systems produce a single MUS without much control over which MUS is generated. In this paper we describe an algorithm that can efficiently compute a collection of MUSes, thus presenting an application with a range of choices. Our algorithm improves over previous methods for finding multiple MUSes by computing its MUSes incrementally. This allows it to generate multiple MUSes more efficiently; making it more feasible to supply applications with a collection of MUSes rather than just one.

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Notes

  1. 1.

    Version 1.1, downloaded from https://sun.iwu.edu/~mliffito/marco/.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Toronto, Toronto, ON, Canada

    Fahiem Bacchus

  2. MIAT, INRA, Toulouse, France

    George Katsirelos

Authors
  1. Fahiem Bacchus
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  2. George Katsirelos
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Correspondence to George Katsirelos .

Editor information

Editors and Affiliations

  1. Université Laval, Quebec, Québec, Canada

    Claude-Guy Quimper

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Bacchus, F., Katsirelos, G. (2016). Finding a Collection of MUSes Incrementally. In: Quimper, CG. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2016. Lecture Notes in Computer Science(), vol 9676. Springer, Cham. https://doi.org/10.1007/978-3-319-33954-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-33954-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33953-5

  • Online ISBN: 978-3-319-33954-2

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