DocumentCode
2109848
Title
Distributed matching with mixed maximum-minimum utilities
Author
Azaria, Amos ; Sarne, David ; Aumann, Y.
Author_Institution
Dept. of Comput. Sci., Bar-Ilan Univ., Ramat Gan, Israel
Volume
2
fYear
2012
fDate
4-7 Dec. 2012
Firstpage
134
Lastpage
139
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.
Keywords
minimax techniques; pattern matching; search problems; utility theory; agent utility function; distributed agent matching; equilibrium structure; hybrid min-max utility function; min-max linear combination; mixed maximum-minimum utilities; Distributed matching; game theory; multi agent systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
Conference_Location
Macau
Print_ISBN
978-1-4673-6057-9
Type
conf
DOI
10.1109/WI-IAT.2012.119
Filename
6511562
Link To Document