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Measures of Disagreement and Aggregation of Preferences Based on Multidistances

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Advances in Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 300))

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Abstract

This paper deals with measures of disagreement and aggregation of preferences. Multidistances are used as measures of disagreement and also as a key element in the definition of aggregation of preferences. After introducing contractive multidistances, they are shown to be particularly suitable for our purpose. Two families of multidistances are studied, and, in particular, those satisfying contractivity, homogeneity and generalized maximum dissension properties.

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Author information

Authors and Affiliations

  1. University of Alcalá, Pza. San Diego, 28801, Alcalá de Henares, Madrid, Spain

    Tomasa Calvo

  2. University of the Balearic Islands, Cra. Valldemossa km 7.5, 07122, Palma, Spain

    Javier Martín & Gaspar Mayor

Authors
  1. Tomasa Calvo
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  2. Javier Martín
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  3. Gaspar Mayor
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. CNRS UMR 7606, DAPA, LIP6 8, Université Pierre et Marie Curie - Paris6, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute — IONA College,, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Calvo, T., Martín, J., Mayor, G. (2012). Measures of Disagreement and Aggregation of Preferences Based on Multidistances. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_58

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  • DOI: https://doi.org/10.1007/978-3-642-31724-8_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31723-1

  • Online ISBN: 978-3-642-31724-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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