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Group Decision Making: From Consistency to Consensus

  • Conference paper
Modeling Decisions for Artificial Intelligence (MDAI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4617))

Abstract

In group decision making (GDM) processes, prior to the selection of the best alternative(s), it would be desirable that experts achieve a high degree of consensus or agreement between them. Due to the complexity of most decision making problems, individuals’ preferences may not satisfy formal properties. Consistency is one of such properties, and it is associated with the transitivity property. Obviously, when carrying out a rational decision making, consistent information, i.e. information which does not imply any kind of contradiction, is more appropriate than information containing some contradictions. Therefore, in a GDM process, consistency should also be sought after.

In this paper we present a consensus model for GDM problems that proceeds from consistency to consensus. This model includes a novel consistency reaching module based on consistency measures. In particular, the model generates advice on how experts should change their preferences in order to reach a solution with high consistency and consensus degrees.

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Authors and Affiliations

  1. Centre for Computational Intelligence, De Montfort University, Leicester LE1 9BH, UK

    F. Chiclana

  2. Department of Computer Science, University of Jaén, 23700 Jaén, Spain

    F. Mata & L. Martínez

  3. Dept. of Computer Science and Artificial Intelligence, University of Granada, 18071 Granada, Spain

    S. Alonso & E. Herrera-Viedma

Authors
  1. F. Chiclana
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  2. F. Mata
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  3. S. Alonso
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  4. E. Herrera-Viedma
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  5. L. Martínez
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Vicenç Torra Yasuo Narukawa Yuji Yoshida

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© 2007 Springer-Verlag Berlin Heidelberg

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Chiclana, F., Mata, F., Alonso, S., Herrera-Viedma, E., Martínez, L. (2007). Group Decision Making: From Consistency to Consensus. In: Torra, V., Narukawa, Y., Yoshida, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2007. Lecture Notes in Computer Science(), vol 4617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73729-2_8

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  • DOI: https://doi.org/10.1007/978-3-540-73729-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73728-5

  • Online ISBN: 978-3-540-73729-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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