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A Random Set Model for Fuzzy Labels

  • Conference paper
Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2711))

Abstract

A random set semantics for fuzzy labels is proposed in which we model the vagueness of fuzzy concepts in terms of their level of appropriateness as descriptions for values. This random set model is then shown to be characterised by a certain axiom system for appropriateness measures. It is then shown how some t-norms can generate appropriateness measures and an attempt is made to identify a family of t-norms that can be used consistently for this purpose. The calculus that is introduced is functional but not truth-functional.

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Author information

Authors and Affiliations

  1. Department of Engineering Mathematics, University of Bristol, Bristol, UK

    Jonathan Lawry

  2. Secció Matemàtiques i Informàtica – ETSAV, Univ. Politècnica de Catalunya, Pere Serra 1-15, Sant Cugat del Vallès, Barcelona, Spain

    Jordi Recasens

Authors
  1. Jonathan Lawry
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  2. Jordi Recasens
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Aalborg University, Fredrik Bajersvej 7E, 9220, Aalborg, Denmark

    Thomas Dyhre Nielsen

  2. Department of Computer Science, Hong Kong University of Science and Technology, ClearWater Bay Road, Kowloon, Hong Kong, China,

    Nevin Lianwen Zhang

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© 2003 Springer-Verlag Berlin Heidelberg

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Lawry, J., Recasens, J. (2003). A Random Set Model for Fuzzy Labels. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45062-7_29

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  • DOI: https://doi.org/10.1007/978-3-540-45062-7_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40494-1

  • Online ISBN: 978-3-540-45062-7

  • eBook Packages: Springer Book Archive

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