Distributed matching with mixed maximum-minimum utilities

Amos Azaria, David Sarner, Yonatan Aumann

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

1 Scopus citations

Abstract

In this paper we study distributed agent matching in environments characterized by costly exploration, where each agent's utility from forming a partnership is influenced by both the maximum and the minimum among the two agent's competence. This kind of utility function is somehow more applicable, compared to the one used in related work that takes the utility to be either the type of the agent partner or "standard" functions such as average or multiplication of the two types. The use of the hybrid min-max utility function is favorable whenever the performance of the agents forming a partnership is principally affected by the most (or least) competent among the two. This paper supplies a cohesive analysis for the min-max case, proving the equilibrium structure for the different min-max linear combination that may be used. We show that in any case that an agent sets its acceptance threshold below its own type it is guaranteed that any agent with a type between this threshold and its own will accept it (the agent) as a partner as well. This result substantially facilitates the calculation of equilibrium for such settings, e.g., when the set of types is finite.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Pages134-139
Number of pages6
DOIs
StatePublished - 2012
Event2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012 - Macau, China
Duration: 4 Dec 20127 Dec 2012

Publication series

NameProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Volume2

Conference

Conference2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Country/TerritoryChina
CityMacau
Period4/12/127/12/12

Keywords

  • Distributed matching
  • game theory
  • multi agent systems

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