Infinite horizon Markov decision processes with unknown or variable discount factors
type: Item
instance of: scholarly article
title: Infinite horizon Markov decision processes with unknown or variable discount factors
zbMATH Open document ID: 0616.90095
DOI: 10.1016/0377-2217(87)90174-3
published in: European Journal of Operational Research
publication date: 1987-01-01T00:00:00Z
review text: The standard approach to discounted Markov decision processes is to assume a fixed discount factor, and, perhaps, apply a sensitivity analysis if the estimate is subject to error. In this paper the discount factor is assumed to be endowed with certain stochastic properties, and the Markov decision problem is then reformulated. Bounds for loss of optimality are calculated if an estimate of the discount factor is used in a standard model.
Mathematics Subject Classification ID: 90C40
zbMATH DE Number: 3999705
zbMATH Keywords: stochastic discount factors
zbMATH Keywords: discounted Markov decision processes
zbMATH Keywords: Bounds for loss of optimality
author: D. J. White
MaRDI profile type: Publication
full work available at URL: 0377-2217(87)90174-3
OpenAlex ID: W1970641913
cites work: Optimum Policy Regions for Markov Processes with Discounting
cites work: Q4190426
cites work: Q3266141
cites work: Q4739658
cites work: Q3867541
description: scientific article; zbMATH DE number 3999705