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Measuring Dissimilarity between Judgment Sets

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Logics in Artificial Intelligence (JELIA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8761))

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Abstract

Distances and scores are widely used to measure (dis)similarity between objects of information such as preferences, belief sets, judgment sets, etc. Typically, measures are directly imported from information theory or topology, with little consideration for adequacy in the context of comparing logically related information. We propose a set of desirable properties for measures used to aggregate (logically related) judgments, and show which of the measures used for this purpose satisfy them.

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Author information

Authors and Affiliations

  1. University of Bergen, PB. 7802, 5020, Bergen, Norway

    Marija Slavkovik & Thomas Ågotnes

Authors
  1. Marija Slavkovik
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  2. Thomas Ågotnes
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Editor information

Editors and Affiliations

  1. University of Madeira, Funchal, Madeira, Portugal

    Eduardo Fermé

  2. CENTRIA, Universidade Nova de Lisboa, Caparica, Portugal

    João Leite

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© 2014 Springer International Publishing Switzerland

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Slavkovik, M., Ågotnes, T. (2014). Measuring Dissimilarity between Judgment Sets. In: Fermé, E., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2014. Lecture Notes in Computer Science(), vol 8761. Springer, Cham. https://doi.org/10.1007/978-3-319-11558-0_44

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  • DOI: https://doi.org/10.1007/978-3-319-11558-0_44

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11557-3

  • Online ISBN: 978-3-319-11558-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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