IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v53y2001i2p279-295.html
   My bibliography  Save this article

Markov decision processes with a stopping time constraint

Author

Listed:
  • Masayuki Horiguchi

Abstract

In this paper, the optimization problem for a stopped Markov decision process with finite states and actions is considered over stopping times τ constrained so that ?τ≦α for some fixed α>0. The problem is solved through randomization of stopping times and mathematical programming formulation by occupation measures. Another representation, called F-representation, of randomized stopping times is given, by which the concept of Markov or stationary randomized stopping times is introduced. We treat two types of occupation measures, running and stopped, but stopped occupation measure is shown to be expressed by running one. We study the properties of the set of running occupation measures achieved by different classes of pairs of policies and randomized stopping times. Analyzing the equivalent mathematical programming problem formulated by running occupation measures corresponding with stationary policies and stationary randomized stopping times, we prove the existence of an optimal constrained pair of stationary policy and stopping time requiring randomization in at most one state. Copyright Springer-Verlag Berlin Heidelberg 2001

Suggested Citation

  • Masayuki Horiguchi, 2001. "Markov decision processes with a stopping time constraint," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 53(2), pages 279-295, June.
    • Handle: RePEc:spr:mathme:v:53:y:2001:i:2:p:279-295
    DOI: 10.1007/PL00003996
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/PL00003996
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/PL00003996?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christopher W. Miller, 2016. "A Duality Result for Robust Optimization with Expectation Constraints," Papers 1610.01227, arXiv.org.
    2. Lanlan Zhang & Xianping Guo, 2008. "Constrained continuous-time Markov decision processes with average criteria," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 67(2), pages 323-340, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:mathme:v:53:y:2001:i:2:p:279-295. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.