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Aggregating Preferences Represented by Conditional Preference Networks

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Algorithmic Decision Theory (ADT 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13023))

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Abstract

This paper focuses on the task of aggregating preference orders over combinatorial domains, where both the individual and the aggregate preference orders are represented as Conditional Preference Networks (CP-nets). We propose intuitive objective functions for finding an optimal aggregate CP-net, as well as corresponding optimal efficient aggregation algorithms for inputs with certain structural properties.

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).

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Notes

  1. 1.

    Completeness is a limiting condition to be defined in Sect. 3.

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Authors and Affiliations

  1. University of Regina, Regina, SK, Canada

    Abu Mohammad Hammad Ali, Howard J. Hamilton, Elizabeth Rayner, Boting Yang & Sandra Zilles

Authors
  1. Abu Mohammad Hammad Ali
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  2. Howard J. Hamilton
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  3. Elizabeth Rayner
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  4. Boting Yang
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  5. Sandra Zilles
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Editor information

Editors and Affiliations

  1. National Technical University of Athens, Athens, Greece

    Dimitris Fotakis

  2. Consejo Superior de Investigaciones Cientificas, Madrid, Madrid, Spain

    David Ríos Insua

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Ali, A.M.H., Hamilton, H.J., Rayner, E., Yang, B., Zilles, S. (2021). Aggregating Preferences Represented by Conditional Preference Networks. In: Fotakis, D., Ríos Insua, D. (eds) Algorithmic Decision Theory. ADT 2021. Lecture Notes in Computer Science(), vol 13023. Springer, Cham. https://doi.org/10.1007/978-3-030-87756-9_1

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  • DOI: https://doi.org/10.1007/978-3-030-87756-9_1

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