Block-successive approximation for a discounted Markov decision model

Moshe Haviv

Stochastic Processes and their Applications, 1985, vol. 19, issue 1, 151-160

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.

Keywords: optimal; reward; Markov; decision; model; partitioning; transition; matrices; successive; approximation; stationary; policies (search for similar items in EconPapers)
Date: 1985
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