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Convergent reinforcement learning control with neural ...
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由 M Lee 著作2014被引用 11 次 — We combine a convergent TD-learning method and direct continuous action search with neural networks for function approximation to obtain both stability and ...
Convergent reinforcement learning control with neural ...
ResearchGate
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We combine a convergent TD-learning method and direct continuous action search with neural networks for function approximation to obtain both stability and ...
Convergent Reinforcement Learning Control with Neural ...
The University of North Carolina at Charlotte
https://webpages.charlotte.edu › pdfs › adprl14
The University of North Carolina at Charlotte
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由 M Lee 著作被引用 11 次 — Abstract—We combine a convergent TD-learning method and direct continuous action search with neural networks for function.
Convergent reinforcement learning control with neural networks ...
Semantic Scholar
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A convergent TD-learning method and direct continuous action search with neural networks for function approximation to obtain both stability and ...
Convergent reinforcement learning control with neural networks ...
DBLP
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Minwoo Lee, Charles W. Anderson : Convergent reinforcement learning control with neural networks and continuous action search. ADPRL 2014: 1-8.
Minwoo Lee - Google 學術搜尋
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Computer Networks 219, 109396, 2022. 11, 2022. Convergent reinforcement learning control with neural networks and continuous action search. M Lee, CW Anderson.
Applying Neural Network to Reinforcement Learning in ...
Springer
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由 D Wang 著作2005被引用 3 次 — This paper is concerned with the problem of Reinforcement Learning (RL) in large or continuous spaces. Function approximation is the main method to solve ...
SBEED: Convergent Reinforcement Learning with Nonlinear ...
Proceedings of Machine Learning Research
https://proceedings.mlr.press › ...
Proceedings of Machine Learning Research
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由 B Dai 著作被引用 320 次 — Furthermore, the algorithm handles both the optimal value function estimation and policy optimization in a unified way, and readily applies to both continuous ...
10 頁
Deep Reinforcement Learning in Parameterized Action ...
arXiv
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arXiv
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2024年5月3日 — This paper represents a successful extension of deep reinforcement learning to the class of parameterized action space MDPs.
Combining neural networks and control
ScienceDirect.com
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由 S Cerf 著作2023被引用 1 次 — Abstract: Machine learning tools are widely used for knowledge extraction, modeling, and decision tasks; a range of problems that Control Theory also ...