IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4613-0265-0_12.html
   My bibliography  Save this book chapter

Interval Methods for Uncertain Markov Decision Processes

In: Markov Processes and Controlled Markov Chains

Author

Listed:
  • Masami Kurano

    (Chiba University)

  • Masami Yasuda

    (Chiba University)

  • Jun-ichi Nakagami

    (Chiba University)

Abstract

In this paper, interval methods for uncertain Markov decision processes are considered. That is, a controlled Markov set-chain model with a finite state is developed by an interval arithmetic analysis, and we will find Pareto optimal policies which maximize the discounted or average expected rewards over all stationary policies under some partial order. The optimal policies are characterized by a maximal solution of an optimality equation including efficient set function.

Suggested Citation

  • Masami Kurano & Masami Yasuda & Jun-ichi Nakagami, 2002. "Interval Methods for Uncertain Markov Decision Processes," Springer Books, in: Zhenting Hou & Jerzy A. Filar & Anyue Chen (ed.), Markov Processes and Controlled Markov Chains, chapter 0, pages 223-232, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-0265-0_12
    DOI: 10.1007/978-1-4613-0265-0_12
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:sprchp:978-1-4613-0265-0_12. 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.