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Lattice-Theoretic Approach to Version Spaces in Qualitative Decision Making

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Statistical Learning and Data Sciences (SLDS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9047))

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Abstract

We present a lattice-theoretic approach to version spaces in multicriteria preference learning and discuss some complexity aspects. In particular, we show that the description of version spaces in the preference model based on the Sugeno integral is an NP-hard problem, even for simple instances.

T. Waldhauser—This research is supported by the Hungarian National Foundation for Scientific Research under grant no. K104251 and by the János Bolyai Research Scholarship.

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Author information

Authors and Affiliations

  1. LORIA (CNRS - Inria Nancy Grand Est - Université de Lorraine), Equipe Orpailleur – Bâtiment B, Campus Scientifique, B.P. 239, 54506, Vandœuvre-ĺes-Nancy Cedex, France

    Miguel Couceiro

  2. Bolyai Institute, University of Szeged, Aradi vértanúk tere 1, Szeged, H-6720, Hungary

    Tamás Waldhauser

Authors
  1. Miguel Couceiro
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  2. Tamás Waldhauser
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Corresponding author

Correspondence to Miguel Couceiro .

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Editors and Affiliations

  1. University of London, Egham, Surrey, United Kingdom

    Alexander Gammerman

  2. University of London, Egham, Surrey, United Kingdom

    Vladimir Vovk

  3. Frederick University, Nicosia, Cyprus

    Harris Papadopoulos

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Couceiro, M., Waldhauser, T. (2015). Lattice-Theoretic Approach to Version Spaces in Qualitative Decision Making. In: Gammerman, A., Vovk, V., Papadopoulos, H. (eds) Statistical Learning and Data Sciences. SLDS 2015. Lecture Notes in Computer Science(), vol 9047. Springer, Cham. https://doi.org/10.1007/978-3-319-17091-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-17091-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17090-9

  • Online ISBN: 978-3-319-17091-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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