Hostname: page-component-74656f9884-54qdv Total loading time: 0 Render date: 2026-11-10T09:37:09.357Z Has data issue: false hasContentIssue false

Extreme-point solutions in Markov decision processes

Published online by Cambridge University Press:  14 July 2016

David Assaf*
Affiliation:
The Hebrew University of Jerusalem
*
∗ Postal address: Department of Statistics, Faculty of Social Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.

Abstract

The paper presents sufficient conditions for certain functions to be convex. Functions of this type often appear in Markov decision processes, where their maximum is the solution of the problem. Since a convex function takes its maximum at an extreme point, the conditions may greatly simplify a problem. In some cases a full solution may be obtained after the reduction is made. Some illustrative examples are discussed.

Information

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1983 

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.)

Article purchase

Temporarily unavailable