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Mathematical optimization / Dynamic programming / Stochastic control / Equations / Numerical analysis / Automatic basis function construction / Reinforcement learning / Proto-value functions / Bellman equation / Statistics / Mathematics / Mathematical analysis


Analyzing Feature Generation for Value-Function Approximation Ronald Parr Christopher Painter-Wakefield Department of Computer Science, Duke University, Durham, NC[removed]USA Lihong Li
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Document Date: 2007-04-23 20:09:21


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File Size: 266,77 KB

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City

Piscataway / Cambridge / /

Company

Neural Information Processing Systems / MIT Press / Markov / /

Facility

Duke University / Rutgers University / University of Massachusetts / Massachusetts Institute of Technology / /

IndustryTerm

inner product / value-iteration algorithm / positive dot product / approximate solution / on-line learning / dot product / Linear least-squares algorithms / to uncontrolled systems / signal processing / off-policy algorithm / linear fixed point solution / approximate policy-iteration algorithm / /

MarketIndex

SET 50 / /

Organization

BEBFs LSPI / National Science Foundation / MIT / Rutgers University / USA Lihong Li Michael Littman Department of Computer Science / University of Massachusetts / Amherst / Massachusetts Institute of Technology / Value-Function Approximation Ronald Parr Christopher Painter-Wakefield Department of Computer Science / Laboratory for Information and Decision Systems / Duke University / Durham / /

Person

Van Roy / Ronald Parr Christopher / Morgan Kaufmann / Christopher Painter-Wakefield / /

Position

author / MP / /

Product

Pentax K-x Digital Camera / Bellman / /

ProgrammingLanguage

V / /

ProvinceOrState

New Jersey / North Carolina / Massachusetts / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

Linear least-squares algorithms / frustrating algorithm / artificial intelligence / off-policy algorithm / machine learning / value-iteration algorithm / approximate policy-iteration algorithm / /

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