Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators

This paper investigates the problem of finding a fixed point for a global nonexpansive operator under time-varying communication graphs in real Hilbert spaces, where the global operator is separable and composed of an aggregate sum of local nonexpansive operators. Each local operator is only private...

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Main Authors: Li, Xiuxian, Xie, Lihua
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/152143
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1521432021-09-13T07:57:28Z Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators Li, Xiuxian Xie, Lihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Distributed Algorithms Multi-agent Networks This paper investigates the problem of finding a fixed point for a global nonexpansive operator under time-varying communication graphs in real Hilbert spaces, where the global operator is separable and composed of an aggregate sum of local nonexpansive operators. Each local operator is only privately accessible to each agent, and all agents constitute a network. To seek a fixed point of the global operator, it is indispensable for agents to exchange local information and update their solution cooperatively. To solve the problem, two algorithms are developed, called distributed Krasnosel'skiĭ–Mann (D-KM) and distributed block-coordinate Krasnosel'skiĭ–Mann (D-BKM) iterations, for which D-BKM is a block-coordinate version of D-KM in the sense of randomly choosing and computing only one block-coordinate of local operators at each time for each agent. It is shown that the proposed two algorithms can both converge weakly to a fixed point of the global operator. Meanwhile, the designed algorithms are applied to recover the classical distributed gradient descent (DGD) algorithm, devise a new block-coordinate DGD algorithm, handle a distributed shortest distance problem in the Hilbert space for the first time, and solve linear algebraic equations in a novel distributed approach. Finally, the theoretical results are corroborated by a few numerical examples. Ministry of Education (MOE) This work was supported by the Ministry of Education of Singapore under MoE Tier 1 Research Grant RG72. 2021-09-13T07:57:28Z 2021-09-13T07:57:28Z 2020 Journal Article Li, X. & Xie, L. (2020). Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators. Automatica, 122, 109286-. https://dx.doi.org/10.1016/j.automatica.2020.109286 0005-1098 https://hdl.handle.net/10356/152143 10.1016/j.automatica.2020.109286 2-s2.0-85091988922 122 109286 en RG72 Automatica © 2020 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Distributed Algorithms
Multi-agent Networks
spellingShingle Engineering::Electrical and electronic engineering
Distributed Algorithms
Multi-agent Networks
Li, Xiuxian
Xie, Lihua
Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
description This paper investigates the problem of finding a fixed point for a global nonexpansive operator under time-varying communication graphs in real Hilbert spaces, where the global operator is separable and composed of an aggregate sum of local nonexpansive operators. Each local operator is only privately accessible to each agent, and all agents constitute a network. To seek a fixed point of the global operator, it is indispensable for agents to exchange local information and update their solution cooperatively. To solve the problem, two algorithms are developed, called distributed Krasnosel'skiĭ–Mann (D-KM) and distributed block-coordinate Krasnosel'skiĭ–Mann (D-BKM) iterations, for which D-BKM is a block-coordinate version of D-KM in the sense of randomly choosing and computing only one block-coordinate of local operators at each time for each agent. It is shown that the proposed two algorithms can both converge weakly to a fixed point of the global operator. Meanwhile, the designed algorithms are applied to recover the classical distributed gradient descent (DGD) algorithm, devise a new block-coordinate DGD algorithm, handle a distributed shortest distance problem in the Hilbert space for the first time, and solve linear algebraic equations in a novel distributed approach. Finally, the theoretical results are corroborated by a few numerical examples.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Li, Xiuxian
Xie, Lihua
format Article
author Li, Xiuxian
Xie, Lihua
author_sort Li, Xiuxian
title Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
title_short Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
title_full Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
title_fullStr Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
title_full_unstemmed Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
title_sort distributed algorithms for computing a fixed point of multi-agent nonexpansive operators
publishDate 2021
url https://hdl.handle.net/10356/152143
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