Block-successive approximation for a discounted Markov decision model

Moshe Haviv

doi:10.1016/0304-4149(85)90046-8

Block-successive approximation for a discounted Markov decision model

Moshe Haviv^*

^*Corresponding author for this work

Department of Statistics

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

3 Scopus citations

Abstract

In this paper we suggest a new successive approximation method to compute the optimal discounted reward for finite state and action, discrete time, discounted Markov decision chains. The method is based on a block partitioning of the (stochastic) matrices corresponding to the stationary policies. The method is particularly attractive when the transition matrices are jointly nearly decomposable or nearly completely decomposable.

Original language	English
Pages (from-to)	151-160
Number of pages	10
Journal	Stochastic Processes and their Applications
Volume	19
Issue number	1
DOIs	https://doi.org/10.1016/0304-4149(85)90046-8
State	Published - Feb 1985

Keywords

Markov decision model
optimal reward
partitioning transition matrices
stationary policies
successive approximation

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10.1016/0304-4149(85)90046-8

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abstract = "In this paper we suggest a new successive approximation method to compute the optimal discounted reward for finite state and action, discrete time, discounted Markov decision chains. The method is based on a block partitioning of the (stochastic) matrices corresponding to the stationary policies. The method is particularly attractive when the transition matrices are jointly nearly decomposable or nearly completely decomposable.",

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AB - In this paper we suggest a new successive approximation method to compute the optimal discounted reward for finite state and action, discrete time, discounted Markov decision chains. The method is based on a block partitioning of the (stochastic) matrices corresponding to the stationary policies. The method is particularly attractive when the transition matrices are jointly nearly decomposable or nearly completely decomposable.

KW - Markov decision model

KW - optimal reward

KW - partitioning transition matrices

KW - stationary policies

KW - successive approximation

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Block-successive approximation for a discounted Markov decision model

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Keywords

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