DocumentCode
2826235
Title
On the rate of convergence of distributed subgradient methods for multi-agent optimization
Author
Nedic, Angelia ; Ozdaglar, Asuman
Author_Institution
Univ. of Illinois Urbana-Champaign, Urbana
fYear
2007
fDate
12-14 Dec. 2007
Firstpage
4711
Lastpage
4716
Abstract
We study a distributed computation model for optimizing the sum of convex (nonsmooth) objective functions of multiple agents. We provide convergence results and estimates for convergence rate. Our analysis explicitly characterizes the tradeoff between the accuracy of the approximate optimal solutions generated and the number of iterations needed to achieve the given accuracy.
Keywords
control system analysis; control system synthesis; convergence; decentralised control; multi-robot systems; convergence rate; distributed subgradient methods; multi-agent optimization; Algorithm design and analysis; Computational modeling; Computer industry; Convergence; Distributed computing; Electrical equipment industry; Industrial control; Optimization methods; Resource management; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 2007 46th IEEE Conference on
Conference_Location
New Orleans, LA
ISSN
0191-2216
Print_ISBN
978-1-4244-1497-0
Electronic_ISBN
0191-2216
Type
conf
DOI
10.1109/CDC.2007.4434693
Filename
4434693
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