Join me with the weakest partner, please

Moshe Mash, Igor Rochlin, David Sarne

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

4 Scopus citations

Abstract

This paper considers the problem of self-interested agents engaged in costly exploration when individual findings benefit all agents. The purpose of the exploration is to reason about the nature and value of the different opportunities available to the agents whenever such information is a priori unknown. While the problem has been considered for the case where the goal is to maximize the overall expected benefit, the focus of this paper is on settings where the agents are self-interested, i.e, each agent's goal is to maximize its individual expected benefit. The paper presents an equilibrium analysis of the model, considering both mixed and pure equilibria. The analysis is used to demonstrate two somehow non-intuitive properties of the equilibrium cooperative exploration strategies used by the agents and their resulting expected payoffs: (a) when using mixed equilibrium strategies, the agents might lose due to having more potential opportunities available for them in their environment, and (b) if the agents can have additional agents join them in the exploration they might prefer the less competent ones to join the process.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Pages17-24
Number of pages8
DOIs
StatePublished - 1 Dec 2012
Externally publishedYes
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

  • Cooperation
  • Multi-Agent Exploration

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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