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On Measuring Inconsistency Using Maximal Consistent Sets

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9161))

Abstract

An important problem in knowledge-based systems is inconsistency handling. This problem has recently been attracting a lot of attention in AI community. In this paper, we tackle the problem of evaluating the amount of conflicts in knowledge bases, and provide a new fine grained inconsistency measure, denoted MCSC, based on maximal consistent sets. In particular, it is suitable in systems where inconsistency results from multiple consistent sources. We show that our measure satisfies several rational postulates proposed in the literature. Moreover, we provide an encoding in integer linear programming for computing MCSC.

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Notes

  1. 1.

    In the original paper, this property is called enhanced additivity.

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Author information

Authors and Affiliations

  1. CRIL - CNRS UMR 8188, University Artois, 62307, Lens Cedex, France

    Meriem Ammoura, Badran Raddaoui & Yakoub Salhi

  2. LAROMAD - University Mouloud Mammeri, Tizi Ouzou, Algeria

    Meriem Ammoura & Brahim Oukacha

Authors
  1. Meriem Ammoura
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  2. Badran Raddaoui
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  3. Yakoub Salhi
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  4. Brahim Oukacha
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Corresponding author

Correspondence to Yakoub Salhi .

Editor information

Editors and Affiliations

  1. Université de Technologie de Compiègne, Compiègne, France

    Sébastien Destercke

  2. Centre de Recherches de Royallieu, Université de Technologie de Compiègne, Compiègne, France

    Thierry Denoeux

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Ammoura, M., Raddaoui, B., Salhi, Y., Oukacha, B. (2015). On Measuring Inconsistency Using Maximal Consistent Sets. In: Destercke, S., Denoeux, T. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2015. Lecture Notes in Computer Science(), vol 9161. Springer, Cham. https://doi.org/10.1007/978-3-319-20807-7_24

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  • DOI: https://doi.org/10.1007/978-3-319-20807-7_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20806-0

  • Online ISBN: 978-3-319-20807-7

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