Input-Output Data-Based Output Antisynchronization Control of Multiagent Systems Using Reinforcement Learning Approach

This article investigates an output antisynchronization problem of multiagent systems by using an input-output data-based reinforcement learning approach. Till now, most of the existing results on antisynchronization problems required full-state information and exact system dynamics in the controlle...

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Bibliographic Details
Published in:	IEEE transactions on industrial informatics Vol. 17; no. 11; pp. 7359 - 7367
Main Authors:	Peng, Zhinan, Zhao, Yiyi, Hu, Jiangping, Luo, Rui, Ghosh, Bijoy Kumar, Nguang, Sing Kiong
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.11.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Control systems design Control theory Heuristic algorithms Incremental actor–critic (AC) network Informatics input–output data Iterative algorithms Iterative methods Learning Multi-agent systems Multiagent systems Network topology optimal antisynchronization Optimal control partially observable multiagent systems reinforcement learning (RL) Synchronization System dynamics
ISSN:	1551-3203, 1941-0050
Online Access:	Get full text
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