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An Ordered Family of Consistency Measures of Belief Functions

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Belief Functions: Theory and Applications (BELIEF 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11069))

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Abstract

We propose a family of measures of consistency (and induced conflict) derived from a definition of consistent belief functions introduced previously. Besides satisfying the desired properties of monotonicity, boundedness, and extreme values, the novel family encompasses the existing probabilistic and logical consistency measures which are shown to correspond to two extremes of the family (lower sharp bound and upper asymptotic limit respectively). We illustrate the definitions and measures of consistency within an example of vessel destination estimation with inconsistent sources.

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Acknowledgements

This research was supported by NATO Allied Command Transformation (ACT).

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Authors and Affiliations

  1. NATO STO Centre for Maritime Research and Experimentation, Viale San Bartolomeo, 400, La Spezia, Italy

    Nadia Ben Abdallah & Anne-Laure Jousselme

  2. Université d’Artois, EA 3926, Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A), 62400, Béthune, France

    Frédéric Pichon

Authors
  1. Nadia Ben Abdallah
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  2. Anne-Laure Jousselme
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  3. Frédéric Pichon
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Corresponding author

Correspondence to Nadia Ben Abdallah .

Editor information

Editors and Affiliations

  1. University of Technology of Compiègne, Compiègne Cedex, France

    Sébastien Destercke

  2. UMR CNRS 7253 Heudiasyc, Université de Technologie de Compiègne, Compiègne Cedex, France

    Thierry Denoeux

  3. Department of Computing and Communication, Oxford Brookes University, Oxford, United Kingdom

    Fabio Cuzzolin

  4. Université de Rennes 1, Lannion Cedex, France

    Arnaud Martin

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Ben Abdallah, N., Jousselme, AL., Pichon, F. (2018). An Ordered Family of Consistency Measures of Belief Functions. In: Destercke, S., Denoeux, T., Cuzzolin, F., Martin, A. (eds) Belief Functions: Theory and Applications. BELIEF 2018. Lecture Notes in Computer Science(), vol 11069. Springer, Cham. https://doi.org/10.1007/978-3-319-99383-6_25

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  • DOI: https://doi.org/10.1007/978-3-319-99383-6_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99382-9

  • Online ISBN: 978-3-319-99383-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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