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Compact Preference Representation via Fuzzy Constraints in Stable Matching Problems: Theoretical and Experimental Studies

  • Maria Silvia PiniEmail author
  • Francesca Rossi
  • Kristen Brent Venable
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)

Abstract

The stable matching problem has many practical applications in two-sided markets, like those that assign doctors to hospitals or students to schools. Usually it is assumed that all agents in each side explicitly express a preference ordering over those in the other side. This can be unfeasible and impractical when the set of agents is very big. However, usually this set has a combinatorial structure, since each agent is often described by some features. To tackle these scenarios, we define a framework for stable matching problems where agents are allowed to express their preferences over those of the other group in a compact way, via soft constraints over the features describing these agents. We focus on a special kind of soft constraints, namely fuzzy constraints. We provide a solving engine for this new kind of stable matching problems that does not increase the time complexity of the classical Gale-Shapley algorithm, while maintaining stability of the matching returned. We then evaluate the approach experimentally.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Maria Silvia Pini
    • 1
  • Francesca Rossi
    • 1
    • 2
  • Kristen Brent Venable
    • 3
  1. 1.University of PadovaPaduaItaly
  2. 2.IBM T.J. Watson Research CenterYorktown HeightsUSA
  3. 3.Tulane University and IHMCNew OrleansUSA

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