Preference Elicitation in Matching Markets Via Interviews: A Study of Offline Benchmarks

Rastegari, B., Goldberg, P. and Manlove, D. (2016) Preference Elicitation in Matching Markets Via Interviews: A Study of Offline Benchmarks. In: EXPLORE 2016: 3rd Workshop on Exploring Beyond the Worst Case in Computational Social Choice, Singapore, 10 May 2016,

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The stable marriage problem and its extensions have been extensively studied, with much of the work in the literature assuming that agents fully know their own preferences over alternatives. This assumption however is not always practical (especially in large markets) and agents usually need to go through some costly deliberation process in order to learn their preferences. In this paper we assume that such deliberations are carried out via interviews, where an interview involves a man and a woman, each of whom learns information about the other as a consequence. If everybody interviews everyone else, then clearly agents can fully learn their preferences. But interviews are costly, and we may wish to minimize their use. It is often the case, especially in practical settings, that due to correlation between agents’ preferences, it is unnecessary for all potential interviews to be carried out in order to obtain a stable matching. Thus the problem is to find a good strategy for interviews to be carried out in order to minimize their use, whilst leading to a stable matching. One way to evaluate the performance of an interview strategy is to compare it against a na¨ıve algorithm that conducts all interviews. We argue however that a more meaningful comparison would be against an optimal offline algorithm that has access to agents’ preference orderings under complete information. We show that, unless P=NP, no offline algorithm can compute the optimal interview strategy in polynomial time. If we are additionally aiming for a particular stable matching (perhaps one with certain desirable properties), we provide restricted settings under which efficient optimal offline algorithms exist.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Manlove, Dr David and Rastegari, Dr Baharak
Authors: Rastegari, B., Goldberg, P., and Manlove, D.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2016 The Authors
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
607071Efficient Algorithms for Mechanism Design Without Monetary Transfer.David ManloveEngineering & Physical Sciences Research Council (EPSRC)EP/K010042/1COM - COMPUTING SCIENCE