ATutorial Survey of Reinforcement Learn  ing

dc.contributor.author	S SATHIYA KEERTHI
dc.contributor.author	B RAVINDRAN
dc.date.accessioned	2012-11-22T14:34:15Z
dc.date.accessioned	2025-02-17T13:59:17Z
dc.date.available	2012-11-22T14:34:15Z
dc.date.issued	2012-11-22
dc.description	This paper gives a compact self contained tutorial survey of reinforcement learning a tool that is increasingly nding application in the development of intelligent dynamic systems Research on rein forcement learning during the past decade has led to the development of a variety of useful algorithms This paper surveys the literature and presents the algorithms in a cohesive framework	en_US
dc.description.abstract	This paper gives a compact self contained tutorial survey of reinforcement learning a tool that is increasingly nding application in the development of intelligent dynamic systems Research on rein forcement learning during the past decade has led to the development of a variety of useful algorithms This paper surveys the literature and presents the algorithms in a cohesive framework	en_US
dc.identifier.uri	https://dl.ftveti.edu.et/handle/123456789/3873
dc.language.iso	en	en_US
dc.subject	Reinforcement learning dynamic programming optimal control neural networks	en_US
dc.title	ATutorial Survey of Reinforcement Learn ing	en_US
dc.type	Article	en_US

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