Optimal Tracking Control of a Nonlinear Multiagent System Using Q-Learning via Event-Triggered Reinforcement Learning

This article offers an optimal control tracking method using an event-triggered technique and the internal reinforcement Q-learning (IrQL) algorithm to address the tracking control issue of unknown nonlinear systems with multiple agents (MASs). Relying on the internal reinforcement reward (IRR) form...

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Detalles Bibliográficos
Autores principales: Wang, Ziwei, Wang, Xin, Tang, Yijie, Liu, Ying, Hu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955809/
https://www.ncbi.nlm.nih.gov/pubmed/36832665
http://dx.doi.org/10.3390/e25020299

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955809/
https://www.ncbi.nlm.nih.gov/pubmed/36832665
http://dx.doi.org/10.3390/e25020299

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