Reinforcement Learning-based control using Q-learning and gravitational search algorithm with experimental validation on a nonlinear servo system-Reference-Cited by-同舟云学术

Reinforcement Learning-based control using Q-learning and gravitational search algorithm with experimental validation on a nonlinear servo system

Published:2022-01 Issue: Volume:583 Page:99-120
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Zamfirache Iuliu Alexandru,Precup Radu-Emil,Roman Raul-Cristian,Petriu Emil M.

Funder

Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii

Ministry of Education and Research, Romania

Corporation for National and Community Service

Politehnica University of Timisoara

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. Reinforcement Learning: An Introduction;Sutton,2017

2. Reinforcement learning is direct adaptive optimal control;Sutton;IEEE Control Syst. Mag.,1992

3. Reinforcement learning and feedback control: using natural decision methods to design optimal adaptive controllers;Lewis;IEEE Control Syst. Mag.,2012

4. Reinforcement learning for control: performance, stability, and deep approximators;Buşoniu;Annu. Rev. Control,2018

5. Deep reinforcement learning: a brief survey;Arulkumaran;IEEE Signal Process Mag.,2017

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