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Fitted Value Function Iteration with Probability One Contractions

Pal, Jeno; Stachurski, John


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

CollectionsANU Research Publications
Date published: 2013
Type: Journal article
Source: Journal of Economic Dynamics and Control
DOI: 10.1016/j.jedc.2012.08.003


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