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Markov processes / Applied mathematics / Markov models / Dynamic programming / Stochastic control / Reinforcement learning / Partially observable Markov decision process / Mathematical optimization / Markov chain / Statistics / Operations research / Control theory


Policy search by dynamic programming J. Andrew Bagnell Carnegie Mellon University Pittsburgh, PA[removed]Andrew Y. Ng
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Document Date: 2004-03-05 16:57:09

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PSDP / /

Facility

Sham Kakade University of Pennsylvania Philadelphia / J. Andrew Bagnell Carnegie Mellon University / Jeff Schneider Carnegie Mellon University / University College London / /

IndustryTerm

statistical gradient-following algorithms / then computing / supervised learning algorithm / http /

Organization

University College London / Jeff Schneider Carnegie Mellon University Pittsburgh / J. Andrew Bagnell Carnegie Mellon University Pittsburgh / Sham Kakade University of Pennsylvania Philadelphia / Stanford University Stanford / /

Person

Andrew Y. Ng / Michael I. Jordan / John Langford / Ronald J. Williams / Michael Kearns / Yishay Mansour / Sham Kakade / /

Position

learned open-loop controller / open-loop learned controller / /

ProvinceOrState

South Dakota / Pennsylvania / North Dakota / Nova Scotia / California / /

PublishedMedium

Machine Learning / /

Technology

following algorithm / polynomial time algorithm / supervised learning algorithm / regression algorithms / iteration style algorithms / Machine Learning / Simulation / statistical gradient-following algorithms / policy search algorithm / /

URL

http /

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