Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems

This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The ﬁrst part undertakes systematic review of consensus problems....

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Main Authors:	Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Turaev, Sherzod, Zeki, Akram M., Adamu, Abubakar Ibrahim
Format:	Article
Language:	English English English
Published:	De Gruyter 2018
Subjects:	QA Mathematics QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/1/jaiscr-2018-0003.pdf http://irep.iium.edu.my/59266/7/59266_Nonlinear%20convergence%20algorithm_scopus.pdf http://irep.iium.edu.my/59266/13/59266_Nonlinear%20convergence%20algorithm_WoS.pdf

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spelling	iium-592662019-05-06T02:50:28Z http://irep.iium.edu.my/59266/ Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems Abdulghafor, Rawad Abdulkhaleq Abdulmolla Turaev, Sherzod Zeki, Akram M. Adamu, Abubakar Ibrahim QA Mathematics QA75 Electronic computers. Computer science This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The ﬁrst part undertakes systematic review of consensus problems. Convergence was generated via extreme doubly stochastic quadratic operators (EDSQOs) in the other part. However, this work was able to formulate convergence algorithms from doubly stochastic matrices, majorization theory, graph theory and stochastic analysis. We develop two algorithms: 1) the nonlinear algorithm of extreme doubly stochastic quadratic operator (NLAEDSQO) to generate all the convergent EDSQOs and 2) the nonlinear convergence algorithm (NLCA) of EDSQOs to investigate the optimal consensus for MAS. Experimental evaluation on convergent of EDSQOs yielded an optimal consensus for MAS. Comparative analysis with the convergence of EDSQOs and DeGroot model were carried out. The comparison was based on the complexity of operators, number of iterations to converge and the time required for convergences. This research proposed algorithm on convergence which is faster than the DeGroot linear model. De Gruyter 2018-11-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/59266/1/jaiscr-2018-0003.pdf application/pdf en http://irep.iium.edu.my/59266/7/59266_Nonlinear%20convergence%20algorithm_scopus.pdf application/pdf en http://irep.iium.edu.my/59266/13/59266_Nonlinear%20convergence%20algorithm_WoS.pdf Abdulghafor, Rawad Abdulkhaleq Abdulmolla and Turaev, Sherzod and Zeki, Akram M. and Adamu, Abubakar Ibrahim (2018) Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems. Journal of Artificial Intelligence and Soft Computing Research, 8 (1). pp. 49-61. ISSN 2083-2567 E-ISSN 2449-6499 https://www.degruyter.com/downloadpdf/j/jaiscr.2018.8.issue-1/jaiscr-2018-0003/jaiscr-2018-0003.pdf 10.1515/jaiscr-2018-0003
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	QA Mathematics QA75 Electronic computers. Computer science
spellingShingle	QA Mathematics QA75 Electronic computers. Computer science Abdulghafor, Rawad Abdulkhaleq Abdulmolla Turaev, Sherzod Zeki, Akram M. Adamu, Abubakar Ibrahim Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
description	This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The ﬁrst part undertakes systematic review of consensus problems. Convergence was generated via extreme doubly stochastic quadratic operators (EDSQOs) in the other part. However, this work was able to formulate convergence algorithms from doubly stochastic matrices, majorization theory, graph theory and stochastic analysis. We develop two algorithms: 1) the nonlinear algorithm of extreme doubly stochastic quadratic operator (NLAEDSQO) to generate all the convergent EDSQOs and 2) the nonlinear convergence algorithm (NLCA) of EDSQOs to investigate the optimal consensus for MAS. Experimental evaluation on convergent of EDSQOs yielded an optimal consensus for MAS. Comparative analysis with the convergence of EDSQOs and DeGroot model were carried out. The comparison was based on the complexity of operators, number of iterations to converge and the time required for convergences. This research proposed algorithm on convergence which is faster than the DeGroot linear model.
format	Article
author	Abdulghafor, Rawad Abdulkhaleq Abdulmolla Turaev, Sherzod Zeki, Akram M. Adamu, Abubakar Ibrahim
author_facet	Abdulghafor, Rawad Abdulkhaleq Abdulmolla Turaev, Sherzod Zeki, Akram M. Adamu, Abubakar Ibrahim
author_sort	Abdulghafor, Rawad Abdulkhaleq Abdulmolla
title	Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
title_short	Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
title_full	Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
title_fullStr	Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
title_full_unstemmed	Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
title_sort	nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
publisher	De Gruyter
publishDate	2018
url	http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/ http://irep.iium.edu.my/59266/1/jaiscr-2018-0003.pdf http://irep.iium.edu.my/59266/7/59266_Nonlinear%20convergence%20algorithm_scopus.pdf http://irep.iium.edu.my/59266/13/59266_Nonlinear%20convergence%20algorithm_WoS.pdf
first_indexed	2023-09-18T21:23:56Z
last_indexed	2023-09-18T21:23:56Z
_version_	1777412065848197120

Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems

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