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Introducing Incomparability in Modeling Qualitative Belief Functions

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Book cover Modeling Decisions for Artificial Intelligence (MDAI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7647))

Abstract

This paper investigates a new model for generating belief functions from qualitative preferences. Our approach consists in constructing appropriate quantitative information from incomplete preferences relations. It is able to combine preferences despite the presence of incompleteness and incomparability in their preference orderings. The originality of our model is to provide additional interpretation values to the existing methods based on strict preferences and indifferences only.

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References

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Author information

Authors and Affiliations

  1. LARODEC, University of Tunis, Institut Supérieur de Gestion, Tunisia

    Amel Ennaceur & Zied Elouedi

  2. Univ. Lille Nord of France, UArtois EA 3926, LGI2A, France

    Eric Lefevre

Authors
  1. Amel Ennaceur
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  2. Zied Elouedi
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  3. Eric Lefevre
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Editor information

Editors and Affiliations

  1. IIIA-CSIC, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

  2. Toho Gakuen, 3-1-10, Naka, 186-0004, Kunitachi, Tokyo, Japan

    Yasuo Narukawa

  3. Universitat de Girona, Campus Montilivi, building EPS-4, 17071, Girona, Spain

    Beatriz López  & Mateu Villaret  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Ennaceur, A., Elouedi, Z., Lefevre, E. (2012). Introducing Incomparability in Modeling Qualitative Belief Functions. In: Torra, V., Narukawa, Y., López, B., Villaret, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2012. Lecture Notes in Computer Science(), vol 7647. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34620-0_34

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  • DOI: https://doi.org/10.1007/978-3-642-34620-0_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34619-4

  • Online ISBN: 978-3-642-34620-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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