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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationAAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages347-355
Number of pages9
Volume1
ISBN (Electronic)9781450337694
Publication statusPublished - 2015
Event14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 - Istanbul, Turkey
Duration: May 4 2015May 8 2015

Other

Other14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015
CountryTurkey
CityIstanbul
Period5/4/155/8/15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Guo, M., Shen, H., Todo, T., Sakurai, Y., & Yokoo, M. (2015). Social decision with minimal efficiency loss: An automated mechanism design approach. In AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (Vol. 1, pp. 347-355). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).

Social decision with minimal efficiency loss : An automated mechanism design approach. / Guo, Mingyu; Shen, Hong; Todo, Taiki; Sakurai, Yuko; Yokoo, Makoto.

AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 1 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2015. p. 347-355.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Guo, M, Shen, H, Todo, T, Sakurai, Y & Yokoo, M 2015, Social decision with minimal efficiency loss: An automated mechanism design approach. in AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. vol. 1, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), pp. 347-355, 14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, 5/4/15.
Guo M, Shen H, Todo T, Sakurai Y, Yokoo M. Social decision with minimal efficiency loss: An automated mechanism design approach. In AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 1. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). 2015. p. 347-355
Guo, Mingyu ; Shen, Hong ; Todo, Taiki ; Sakurai, Yuko ; Yokoo, Makoto. / Social decision with minimal efficiency loss : An automated mechanism design approach. AAMAS 2015 - Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems. Vol. 1 International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2015. pp. 347-355
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