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Compact Preference Representation via Fuzzy Constraints in Stable Matching Problems

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Algorithmic Decision Theory (ADT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10576))

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Abstract

We define a framework for stable matching problems where agents are allowed to express their preferences in a compact way, via fuzzy constraints over the features describing the agents of the other group. We provide a solving engine for this new kind of stable matching problems that does not increase the time complexity of the classical GS algorithm, while maintaining stability of the matching returned. We then evaluate the approach experimentally.

Francesca Rossi—(on leave from University of Padova, Italy).

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References

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Author information

Authors and Affiliations

  1. University of Padova, Padua, Italy

    Maria Silvia Pini

  2. IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

    Francesca Rossi

  3. IHMC, Tulane University, New Orleans, USA

    Kristen Brent Venable

Authors
  1. Maria Silvia Pini
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  2. Francesca Rossi
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  3. Kristen Brent Venable
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Corresponding author

Correspondence to Maria Silvia Pini .

Editor information

Editors and Affiliations

  1. Heinrich Heine University, Düsseldorf, Germany

    Jörg Rothe

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Pini, M.S., Rossi, F., Venable, K.B. (2017). Compact Preference Representation via Fuzzy Constraints in Stable Matching Problems. In: Rothe, J. (eds) Algorithmic Decision Theory. ADT 2017. Lecture Notes in Computer Science(), vol 10576. Springer, Cham. https://doi.org/10.1007/978-3-319-67504-6_23

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  • DOI: https://doi.org/10.1007/978-3-319-67504-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67503-9

  • Online ISBN: 978-3-319-67504-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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