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A Multi-perceptual-Based Approach for Group Decision Aiding

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Modeling Decisions for Artificial Intelligence (MDAI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13408))

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Abstract

This paper presents a multi-perceptual framework for multi-criteria group decision aiding based on unbalanced hesitant linguistic information. The concept of a perceptual map is introduced to break the uniformity among the set of basic labels considered in linguistic term sets. Projected perceptual maps are considered to provide multi-perceptual frameworks for group decision aiding. This approach enables decision-makers to use sets of labels or different meanings for the same set of labels (since not all decision-makers feel comfortable using the same linguistic term set when expressing their judgements). Distances and measures of centrality and agreement or consensus are revised based on the concept of a perceptual map and a projected perceptual map that enables us to merge information from decision makers.

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Acknowledgements

This research has been partially supported by the PERCEPTIONS Research Project (PID2020-114247GB-I00), funded by the Spanish Ministry of Science and Information Technology.

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Authors and Affiliations

  1. Esade, Barcelona, Spain

    Olga Porro & Núria Agell

  2. BarcelonaTech, Barcelona, Spain

    Mónica Sánchez & Francisco J. Ruiz

Authors
  1. Olga Porro
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  2. Núria Agell
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  3. Mónica Sánchez
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  4. Francisco J. Ruiz
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Corresponding author

Correspondence to Francisco J. Ruiz .

Editor information

Editors and Affiliations

  1. Umeå University, Umeå, Sweden

    Vicenç Torra

  2. Tamagawa University, Tokyo, Japan

    Yasuo Narukawa

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Porro, O., Agell, N., Sánchez, M., Ruiz, F.J. (2022). A Multi-perceptual-Based Approach for Group Decision Aiding. In: Torra, V., Narukawa, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2022. Lecture Notes in Computer Science(), vol 13408. Springer, Cham. https://doi.org/10.1007/978-3-031-13448-7_2

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  • DOI: https://doi.org/10.1007/978-3-031-13448-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13447-0

  • Online ISBN: 978-3-031-13448-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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