Model-Free Dual Heuristic Dynamic Programming

Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires offline training for the model network, and thus resulting in extra computational cost. In this brief, we propose a model-free DHP (MF-DHP) d...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 26; H. 8; S. 1834 - 1839
Hauptverfasser:	Zhen Ni, Haibo He, Xiangnan Zhong, Prokhorov, Danil V.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.08.2015
Schlagworte:	Action-dependent dual heuristic dynamic programming (DHP) adaptive critic designs (ACDs) adaptive dynamic programming (ADP) Approximation methods Computational modeling Convergence Dynamic programming Learning systems Linear programming Mathematical model online learning reinforcement learning adaptive critic designs (ACDs) Action-dependent dual heuristic dynamic programming (DHP) adaptive dynamic programming (ADP) online learning reinforcement learning
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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