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 an...

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Bibliographic Details
Published in:Abstract and Applied Analysis 2014-01, Vol.2014 (2014), p.11-16-901
Main Author: Yuan, Deming
Format: Article
Language:English
Subjects:
Algorithms
Colleges & universities
Communications networks
Convex analysis
Expected values
Mathematical optimization
Mathematical research
Methods
Multi-agent systems
Optimization
Random variables
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Summary: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.
ISSN:1085-3375
1687-0409
DOI:10.1155/2014/618641