Fitted Value Function Iteration With Probability One Contractions
AbstractThis 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.
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Bibliographic InfoPaper provided by Australian National University, College of Business and Economics, School of Economics in its series ANU Working Papers in Economics and Econometrics with number 2011-560.
Length: 22 Pages
Date of creation: Oct 2011
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-10-22 (All new papers)
- NEP-CIS-2011-10-22 (Confederation of Independent States)
- NEP-CMP-2011-10-22 (Computational Economics)
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