Hostname: page-component-6dbcb7884d-g628x Total loading time: 0 Render date: 2025-02-14T07:53:32.993Z Has data issue: false hasContentIssue false
  • English
  • Français

On a class of non-Markov decision processes

Published online by Cambridge University Press:  14 July 2016

K. D. Glazebrook
K. D. Glazebrook*
Affiliation:
University of Newcastle upon Tyne
Get access Rights & Permissions [Opens in a new window]

Abstract

The optimal strategy for a class of non-Markov decision processes is characterised and has the property that changes of action may occur between successive transitions of the process. Results are given which enable the optimal strategy to be computed iteratively.

Keywords

BANDIT PROCESSESDYNAMIC ALLOCATION INDEXDYNAMIC PROGRAMMINGMARKOV AND SEMI-MARKOV DECISION PROCESSES
Type
Research Papers
Information
Journal of Applied Probability , Volume 15 , Issue 4 , December 1978 , pp. 689 - 698
Copyright
Copyright © Applied Probability Trust 1978 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Gittins, J. C. and Glazebrook, K. D. (1977) On Bayesian models in stochastic scheduling. J. Appl. Prob. 14, 556–565.Google Scholar
Gittins, J. C. and Jones, D. M. (1972) A dynamic allocation index for the sequential design of experiments. In Progress in Statistics: Proc. 9th European Meeting of Statisticians , ed. Gani, J. et al. North Holland, Amsterdam.Google Scholar
Lippman, S. A. (1971) Maximal average-reward policies for semi-Markov decision processes with arbitrary state and action space. Ann. Math. Statist. 42, 1717–1726.CrossRefGoogle Scholar
Miller, B. L. (1968) Finite state continuous time Markov decision processes with an infinite planning horizon. J. Math. Anal. Appl. 22, 552–569.Google Scholar
Ross, S. M. (1968) Arbitrary state Markovian decision processes. Ann. Math. Statist. 39, 2118–2122.CrossRefGoogle Scholar
Ross, S. M. (1970) Applied Probability Models with Optimization Applications. Holden-Day, San Francisco.Google Scholar