^{1} Department of Computer Science, Science and Technology, Aarhus University^{2} Department of Computer Science, University of Oxford^{3} Department of Computer Science, Science and Technology, Aarhus University

DOI:

10.1007/978-3-662-44803-8_1

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 Theta(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.

ISBN:

9783662448021, 9783662448038

Type:

Conference paper

Language:

English

Published in:

Lecture Notes in Computer Science: 7th International Symposium, Sagt 2014, Proceedings, 2014, p. 1-12

Main Research Area:

Science/technology

Publication Status:

Published

Series:

Lecture Notes in Computer Science

Review type:

Peer Review

Conference:

Symposium on Algorithmic Game TheorySymposium on Algorithmic Game Theory, 2014