Fitted value function iteration with probability one contractions

Jen Pál; John Stachurski

doi:10.1016/j.jedc.2012.08.003

Fitted value function iteration with probability one contractions

Jen Pál, John Stachurski^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

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 O _P(n ^-1/2) rate of convergence for Monte Carlo error is obtained.

Original language	English
Pages (from-to)	251-264
Number of pages	14
Journal	Journal of Economic Dynamics and Control
Volume	37
Issue number	1
DOIs	https://doi.org/10.1016/j.jedc.2012.08.003
Publication status	Published - Jan 2013

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AB - 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 O P(n -1/2) rate of convergence for Monte Carlo error is obtained.

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KW - C63

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SP - 251

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JO - Journal of Economic Dynamics and Control

JF - Journal of Economic Dynamics and Control

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Fitted value function iteration with probability one contractions

Abstract

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