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Continuous State Dynamic Programming via Nonexpansive Approximation

  • John Stachurski

    ()

This paper studies fitted value iteration for continuous state dynamic programming using nonexpansive function approximators. A number of nonexpansive approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.

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File URL: http://hdl.handle.net/10.1007/s10614-007-9111-5
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Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 31 (2008)
Issue (Month): 2 (March)
Pages: 141-160

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Handle: RePEc:kap:compec:v:31:y:2008:i:2:p:141-160
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=100248

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