Social decision with minimal efficiency loss: An automated mechanism design approach

Files

RA_hdl_108876.pdf (387.46 KB)
  (Restricted Access)

Date

2015

Authors

Guo, M.
Shen, H.
Todo, T.
Sakurai, Y.
Yokoo, M.

Editors

Advisors

Journal Title

Journal ISSN

Volume Title

Type:

Conference paper

Citation

Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2015, vol.1, pp.347-355

Statement of Responsibility

Mingyu Guo, Hong Shen, Taiki Todo, Yuko Sakurai, Makoto Yokoo

Conference Name

14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '15) (4 May 2015 - 8 May 2015 : Istanbul, Turkey)

Abstract

We study the problem where a group of agents need to choose from a finite set of social outcomes. We assume every agent's valuation for every outcome is bounded and the bounds are public information. For our model, no mechanism simultaneously satisfies strategy-proofness, individual rationality, non-deficit, and efficiency. In light of this, we aim to design mechanisms that are strategy-proof, individually rational, non-deficit, and minimize the worst-case efficiency loss. We propose a family of mechanisms called the shifted Groves mechanisms, which are generalizations of the Groves mechanisms. We first show that if there exist mechanisms that are strategy-proof, individually rational, and non-deficit, then there exist shifted Groves mechanisms with these properties. Our main result is an Automated Mechanism Design (AMD) approach for identifying the (unique) optimal shifted Groves mechanism, which minimizes the worst-case efficiency loss among all shifted Groves mechanisms. Finally, we prove that the optimal shifted Groves mechanism is globally optimal among all deterministic mechanisms that are strategy-proof, individually rational, and non-deficit.

School/Discipline

Dissertation Note

Provenance

Description

Access Status

Rights

Copyright © 2015, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

License

Grant ID

Call number

Persistent link to this record