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Team Formation in Partially Observable Multi-Agent SystemsSets of multi-agent teams often need to maximize a global utility rating the performance of the entire system where a team cannot fully observe other teams agents. Such limited observability hinders team-members trying to pursue their team utilities to take actions that also help maximize the global utility. In this article, we show how team utilities can be used in partially observable systems. Furthermore, we show how team sizes can be manipulated to provide the best compromise between having easy to learn team utilities and having them aligned with the global utility, The results show that optimally sized teams in a partially observable environments outperform one team in a fully observable environment, by up to 30%.
Document ID
20040070708
Acquisition Source
Ames Research Center
Document Type
Preprint (Draft being sent to journal)
Authors
Agogino, Adrian K.
(California Univ. Santa Cruz, CA, United States)
Tumer, Kagan
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 7, 2013
Publication Date
January 1, 2004
Subject Category
Mathematical And Computer Sciences (General)
Meeting Information
Meeting: International Joint Conference on Neural Networks
Location: Budapest
Country: Hungary
Start Date: July 1, 2004
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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