[PDF.20gh] Learning Representation and Control in Markov Decision Processes (Foundations and Trends(r) in Machine Learning)

Learning Representation and Control in Markov Decision Processes (Foundations and Trends(r) in Machine Learning)

[PDF.lb16] Learning Representation and Control in Markov Decision Processes (Foundations and Trends(r) in Machine Learning)

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 | #9567416 in Books |  2009-06-02 | Original language:English | PDF # 1 |  9.21 x.39 x6.14l,.59 | File type: PDF | 184 pages

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||About the Author|University of Massachusetts, Amherst

Learning Representation and Control in Markov Decision Processes describes methods for automatically compressing Markov decision processes (MDPs) by learning a low-dimensional linear approximation defined by an orthogonal set of basis functions. A unique feature of the text is the use of Laplacian operators, whose matrix representations have non-positive off-diagonal elements and zero row sums. The generalized inverses of Laplacian operators, in particular the Drazin inv...

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