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Preservation of Distinguished Fuzzy Measure Classes by Distortion

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Modeling Decisions for Artificial Intelligence (MDAI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3131))

Abstract

Distortion of fuzzy measures is discussed. A special attention is paid to the preservation of submodularity and supermodularity, belief and plausibility.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering, Slovak University of Technology, SK-813 68, Bratislava, Slovakia

    Lubica Valásková & Peter Struk

Authors
  1. Lubica Valásková
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  2. Peter Struk
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Editor information

Editors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute CSIC, Spanish National Research Council, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

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

    Yasuo Narukawa

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Valásková, L., Struk, P. (2004). Preservation of Distinguished Fuzzy Measure Classes by Distortion. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2004. Lecture Notes in Computer Science(), vol 3131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27774-3_17

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  • DOI: https://doi.org/10.1007/978-3-540-27774-3_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22555-3

  • Online ISBN: 978-3-540-27774-3

  • eBook Packages: Springer Book Archive

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