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Fitted Value Function Iteration With Probability One Contractions

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  • Jenö Pál
  • John Stachurski

Abstract

This paper studies a value function iteration algorithm that can be applied to almost all stationary dynamic programming problems. Using nonexpansive function approximation and Monte Carlo integration, we develop a randomized fitted Bellman operator and a corresponding algorithm that is globally convergent with probability one. When additional restrictions are imposed, an OP(n-1/2) rate of convergence for Monte Carlo error is obtained.

Suggested Citation

  • Jenö Pál & John Stachurski, 2011. "Fitted Value Function Iteration With Probability One Contractions," ANU Working Papers in Economics and Econometrics 2011-560, Australian National University, College of Business and Economics, School of Economics.
    • Handle: RePEc:acb:cbeeco:2011-560
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    File URL: https://www.cbe.anu.edu.au/researchpapers/econ/wp560.pdf
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    References listed on IDEAS

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