Implementing the maximum of monotone algorithms

Liad Blumrosen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Running several sub-optimal algorithms and choosing-the optimal one is a common procedure in computer science, most notably in the design of approximation algorithms. This paper deals with one significant flaw of this technique in environments where the inputs are provided by rational agents: such protocols are not necessarily incentive compatible even when the underlying algorithms are. We characterize sufficient and necessary conditions for such best-outcome protocols to be incentive compatible in a general model for agents with one-dimensional private data. We show how our techniques apply in several settings.

Original languageEnglish
Title of host publicationAAMAS'07 - Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems
Pages547-549
Number of pages3
DOIs
StatePublished - 2007
Externally publishedYes
Event6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07 - Honolulu, HI, United States
Duration: 14 May 200818 May 2008

Publication series

NameProceedings of the International Conference on Autonomous Agents

Conference

Conference6th International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS'07
Country/TerritoryUnited States
CityHonolulu, HI
Period14/05/0818/05/08

Keywords

  • Dominant strategies
  • Mechanism design
  • Single parameter

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