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Optimal Greedy Control in Reinforcement Learning

We consider the problem of dimensionality reduction of state space in the variational approach to the optimal control problem, in particular, in the reinforcement learning method. The control problem is described by differential algebraic equations consisting of nonlinear differential equations and...

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Autores principales: Gorobtsov, Alexander, Sychev, Oleg, Orlova, Yulia, Smirnov, Evgeniy, Grigoreva, Olga, Bochkin, Alexander, Andreeva, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698335/
https://www.ncbi.nlm.nih.gov/pubmed/36433518
http://dx.doi.org/10.3390/s22228920
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author Gorobtsov, Alexander
Sychev, Oleg
Orlova, Yulia
Smirnov, Evgeniy
Grigoreva, Olga
Bochkin, Alexander
Andreeva, Marina
author_facet Gorobtsov, Alexander
Sychev, Oleg
Orlova, Yulia
Smirnov, Evgeniy
Grigoreva, Olga
Bochkin, Alexander
Andreeva, Marina
author_sort Gorobtsov, Alexander
collection PubMed
description We consider the problem of dimensionality reduction of state space in the variational approach to the optimal control problem, in particular, in the reinforcement learning method. The control problem is described by differential algebraic equations consisting of nonlinear differential equations and algebraic constraint equations interconnected with Lagrange multipliers. The proposed method is based on changing the Lagrange multipliers of one subset based on the Lagrange multipliers of another subset. We present examples of the application of the proposed method in robotics and vibration isolation in transport vehicles. The method is implemented in FRUND—a multibody system dynamics software package.
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spelling pubmed-96983352022-11-26 Optimal Greedy Control in Reinforcement Learning Gorobtsov, Alexander Sychev, Oleg Orlova, Yulia Smirnov, Evgeniy Grigoreva, Olga Bochkin, Alexander Andreeva, Marina Sensors (Basel) Article We consider the problem of dimensionality reduction of state space in the variational approach to the optimal control problem, in particular, in the reinforcement learning method. The control problem is described by differential algebraic equations consisting of nonlinear differential equations and algebraic constraint equations interconnected with Lagrange multipliers. The proposed method is based on changing the Lagrange multipliers of one subset based on the Lagrange multipliers of another subset. We present examples of the application of the proposed method in robotics and vibration isolation in transport vehicles. The method is implemented in FRUND—a multibody system dynamics software package. MDPI 2022-11-18 /pmc/articles/PMC9698335/ /pubmed/36433518 http://dx.doi.org/10.3390/s22228920 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gorobtsov, Alexander
Sychev, Oleg
Orlova, Yulia
Smirnov, Evgeniy
Grigoreva, Olga
Bochkin, Alexander
Andreeva, Marina
Optimal Greedy Control in Reinforcement Learning
title Optimal Greedy Control in Reinforcement Learning
title_full Optimal Greedy Control in Reinforcement Learning
title_fullStr Optimal Greedy Control in Reinforcement Learning
title_full_unstemmed Optimal Greedy Control in Reinforcement Learning
title_short Optimal Greedy Control in Reinforcement Learning
title_sort optimal greedy control in reinforcement learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698335/
https://www.ncbi.nlm.nih.gov/pubmed/36433518
http://dx.doi.org/10.3390/s22228920
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