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Social welfare in one-sided matchings: random priority and beyond

Social welfare in one-sided matchings: random priority and beyond
Social welfare in one-sided matchings: random priority and beyond
We study the problem of approximate social welfare maximization (without money) in one-sided matching problems when agents have unrestricted cardinal preferences over a finite set of items. Random priority is a very well-known truthful-in-expectation mechanism for the problem. We prove that the approximation ratio of random priority is O(n -1/2) while no truthful-in-expectation mechanism can achieve an approximation ratio better than O(n -1/2), where n is the number of agents and items. Furthermore, we prove that the approximation ratio of all ordinal (not necessarily truthful-in-expectation) mechanisms is upper bounded by O(n -1/2), indicating that random priority is asymptotically the best truthful-in-expectation mechanism and the best ordinal mechanism for the problem.
1-12
Springer
Filos-Ratsikas, Aris
14e554b2-bc6b-4b2c-a84d-8650ad4bed14
Frederiksen, Soren Kristoffer Stiil
3e896a21-0be0-4102-895d-2370e32c28ae
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
Lavi, R
Filos-Ratsikas, Aris
14e554b2-bc6b-4b2c-a84d-8650ad4bed14
Frederiksen, Soren Kristoffer Stiil
3e896a21-0be0-4102-895d-2370e32c28ae
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
Lavi, R

Filos-Ratsikas, Aris, Frederiksen, Soren Kristoffer Stiil and Zhang, Jie (2014) Social welfare in one-sided matchings: random priority and beyond. Lavi, R (ed.) In Algorithmic Game Theory: SAGT 2014. vol. 8768, Springer. 297 pp, pp. 1-12. (doi:10.1007/978-3-662-44803-8_1).

Record type: Conference or Workshop Item (Paper)

Abstract

We study the problem of approximate social welfare maximization (without money) in one-sided matching problems when agents have unrestricted cardinal preferences over a finite set of items. Random priority is a very well-known truthful-in-expectation mechanism for the problem. We prove that the approximation ratio of random priority is O(n -1/2) while no truthful-in-expectation mechanism can achieve an approximation ratio better than O(n -1/2), where n is the number of agents and items. Furthermore, we prove that the approximation ratio of all ordinal (not necessarily truthful-in-expectation) mechanisms is upper bounded by O(n -1/2), indicating that random priority is asymptotically the best truthful-in-expectation mechanism and the best ordinal mechanism for the problem.

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e-pub ahead of print date: 2014
Published date: 2014
Organisations: Agents, Interactions & Complexity

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Local EPrints ID: 402584
URI: https://eprints.soton.ac.uk/id/eprint/402584
PURE UUID: 4a534793-493f-439d-912c-45c1266279a2
ORCID for Jie Zhang: ORCID iD orcid.org/0000-0003-1380-9952

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Date deposited: 29 Nov 2016 09:50
Last modified: 05 Jul 2018 00:24

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