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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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Detalles Bibliográficos
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
Descripción
Sumario: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.