Block-successive approximation for a discounted Markov decision model

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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Year of publication:	1985
Authors:	Haviv, Moshe
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 19.1985, 1, p. 151-160
Publisher:	Elsevier
Keywords:	optimal reward Markov decision model partitioning transition matrices successive approximation stationary policies

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008873101