Convergence analysis of the deep neural networks based globalized dual heuristic programming

Globalized dual heuristic programming (GDHP) algorithm is a special form of approximate dynamic programming (ADP) method that solves the Hamilton–Jacobi–Bellman (HJB) equation for the case where the system takes control-affine form subject to the quadratic cost function. This study incorporates the...

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Vydané v:	Automatica (Oxford) Ročník 122; s. 109222
Hlavní autori:	Kim, Jong Woo, Oh, Tae Hoon, Son, Sang Hwan, Jeong, Dong Hwi, Lee, Jong Min
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.12.2020
Predmet:	Approximate dynamic programming Deep neural networks Lyapunov stability Nonlinear control Reinforcement learning Lyapunov stability Approximate dynamic programming Deep neural networks Nonlinear control Reinforcement learning
ISSN:	0005-1098, 1873-2836
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