Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization
This paper considers the constrained multiagent optimization problem. The objective function of the problem is a sum of convex functions, each of which is known by a specific agent only. For solving this problem, we propose an asynchronous distributed method that is based on gradient-free oracles...
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Format: | Article |
Language: | English |
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Wiley
2014-01-01
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Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2014/618641 |
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author | Deming Yuan |
author_facet | Deming Yuan |
author_sort | Deming Yuan |
collection | DOAJ |
description | This paper considers the constrained multiagent optimization problem.
The objective function of the problem is a sum of convex functions,
each of which is known by a specific agent only.
For solving this problem, we propose an asynchronous distributed method
that is based on gradient-free oracles and gossip algorithm.
In contrast to the existing work, we do not require that agents be capable of
computing the subgradients of their objective functions and coordinating their step size values as well.
We prove that with probability 1 the iterates of all agents converge to the
same optimal point of the problem, for a diminishing step size. |
format | Article |
id | doaj-art-f02e8f6c122d4515afe3131f19d44069 |
institution | Kabale University |
issn | 1085-3375 1687-0409 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
series | Abstract and Applied Analysis |
spelling | doaj-art-f02e8f6c122d4515afe3131f19d440692025-02-03T01:23:05ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/618641618641Asynchronous Gossip-Based Gradient-Free Method for Multiagent OptimizationDeming Yuan0College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, ChinaThis paper considers the constrained multiagent optimization problem. The objective function of the problem is a sum of convex functions, each of which is known by a specific agent only. For solving this problem, we propose an asynchronous distributed method that is based on gradient-free oracles and gossip algorithm. In contrast to the existing work, we do not require that agents be capable of computing the subgradients of their objective functions and coordinating their step size values as well. We prove that with probability 1 the iterates of all agents converge to the same optimal point of the problem, for a diminishing step size.http://dx.doi.org/10.1155/2014/618641 |
spellingShingle | Deming Yuan Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization Abstract and Applied Analysis |
title | Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization |
title_full | Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization |
title_fullStr | Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization |
title_full_unstemmed | Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization |
title_short | Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization |
title_sort | asynchronous gossip based gradient free method for multiagent optimization |
url | http://dx.doi.org/10.1155/2014/618641 |
work_keys_str_mv | AT demingyuan asynchronousgossipbasedgradientfreemethodformultiagentoptimization |