Adaptive control and optimization of multi-agent networks

Nasim Nezamoddini, Hiroki Sayama

研究成果: Conference contribution

抄録

This research proposes a novel technique for distributed control and optimization of the networked systems considering the uncertainties associated with internal complex dynamics and external interactions with the environment. The proposed technique applies a distributed multi-agent framework that minimizes the overall objective of the system subject to the limitations on the shared resources. In this framework, each agent tries to optimize its decisions and improve the learning strategy based on artificial neural networks (ANN) without having access to the statistical distributions of the involved parameters. Comprehensive experiments are implemented to investigate the effects of the learning mechanism and the level of uncertainties. The efficiency of the technique is tested by comparing the proposed technique with the existing traditional network optimization techniques. The proposed technique can be utilized in a variety of applications such as min cost flow problems, disease propagation models, and distributed controls over man-made networks such as supply chain and power grid.

本文言語English
ホスト出版物のタイトルProceedings of the 2020 IISE Annual Conference
編集者L. Cromarty, R. Shirwaiker, P. Wang
出版社Institute of Industrial and Systems Engineers, IISE
ページ1418-1423
ページ数6
ISBN(電子版)9781713827818
出版ステータスPublished - 2020
外部発表はい
イベント2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020 - Virtual, Online, United States
継続期間: 2020 11 12020 11 3

出版物シリーズ

名前Proceedings of the 2020 IISE Annual Conference

Conference

Conference2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020
国/地域United States
CityVirtual, Online
Period20/11/120/11/3

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 産業および生産工学

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