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Preference elicitation in matching markets via interviews: a study of offline benchmarks

Preference elicitation in matching markets via interviews: a study of offline benchmarks
Preference elicitation in matching markets via interviews: a study of offline benchmarks
In this paper we study two-sided matching markets in which the participants do not fully know their preferences and need to go through some costly deliberation process in order to learn their preferences. We assume that such deliberations are carried out via interviews, 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 nave ïalgorithm 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, we provide restricted settings …
1393-1394
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Goldberg, Paul W.
46b110bb-a7df-406d-babc-291a17fff863
Manlove, David
a4321a32-3611-4a9f-9dfe-c595dc7a5a38
Rastegari, Baharak
6ba9e93c-53ba-4090-8f77-c1cb1568d7d1
Goldberg, Paul W.
46b110bb-a7df-406d-babc-291a17fff863
Manlove, David
a4321a32-3611-4a9f-9dfe-c595dc7a5a38

Rastegari, Baharak, Goldberg, Paul W. and Manlove, David (2016) Preference elicitation in matching markets via interviews: a study of offline benchmarks. In, Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. 2016 International Conference on Autonomous Agents & Multiagent Systems (AAMAS '16) (09/05/16 - 13/05/16) Richland. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 1393-1394.

Record type: Book Section

Abstract

In this paper we study two-sided matching markets in which the participants do not fully know their preferences and need to go through some costly deliberation process in order to learn their preferences. We assume that such deliberations are carried out via interviews, 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 nave ïalgorithm 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, we provide restricted settings …

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More information

Published date: 9 May 2016
Venue - Dates: 2016 International Conference on Autonomous Agents & Multiagent Systems (AAMAS '16), , Singapore, Singapore, 2016-05-09 - 2016-05-13

Identifiers

Local EPrints ID: 426213
URI: http://eprints.soton.ac.uk/id/eprint/426213
PURE UUID: 28597fe3-786b-4681-8a93-6907e3d2ff86
ORCID for Baharak Rastegari: ORCID iD orcid.org/0000-0002-0985-573X

Catalogue record

Date deposited: 19 Nov 2018 17:30
Last modified: 20 Jul 2024 01:58

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Contributors

Author: Baharak Rastegari ORCID iD
Author: Paul W. Goldberg
Author: David Manlove

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