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    Analyzing feature generation for valuefunction approximation

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    We analyze a simple, Bellman-error-based approach to generating basis functions for valuefunction approximation. We show that it generates orthogonal basis functions that provably tighten approximation error bounds. We also illustrate the use of this approach in the presence of noise on some sample problems. 1.

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    Title : Analyzing feature generation for valuefunction approximation
    Abstract : We analyze a simple, Bellman-error-based approach to generating basis functions for valuefunction approximation. We show that it generates orthogonal basis functions that provably tighten approximation error bounds. We also illustrate the use of this approach in the presence of noise on some sample problems. 1.
    Subject : unspecified
    Area : Computer Science
    Language : English
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    Url : http://www.cs.duke.edu/~parr/icml07.pdf
    Doi : 10.1.1.151.5750

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