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Controlled Markov set-chains with discounting

Published online by Cambridge University Press:  14 July 2016

Masami Kurano ,
Jinjie Song ,
Masanori Hosaka  and
Youqiang Huang
Masami Kurano*
Affiliation:
Chiba University
Jinjie Song*
Affiliation:
Chiba University
Masanori Hosaka*
Affiliation:
Chiba University
Youqiang Huang*
Affiliation:
Chiba University
*
∗ Postal address: Faculty of Education, Chiba University, Yayoi-cho, Inage-ku, Chiba, Japan, 263.
∗ Postal address: Faculty of Education, Chiba University, Yayoi-cho, Inage-ku, Chiba, Japan, 263.
∗ Postal address: Faculty of Education, Chiba University, Yayoi-cho, Inage-ku, Chiba, Japan, 263.
∗ Postal address: Faculty of Education, Chiba University, Yayoi-cho, Inage-ku, Chiba, Japan, 263.
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Abstract

In the framework of discounted Markov decision processes, we consider the case that the transition probability varies in some given domain at each time and its variation is unknown or unobservable.

To this end we introduce a new model, named controlled Markov set-chains, based on Markov set-chains, and discuss its optimization under some partial order.

Also, a numerical example is given to explain the theoretical results and the computation.

Keywords

Controlled Markov set-chainsdiscounted return criterioninterval arithmetic

MSC classification

Primary: 90C40: Markov and semi-Markov decision processes
Secondary: 90C39: Dynamic programming

Information

Type
Research Papers
Information
Journal of Applied Probability , Volume 35 , Issue 2 , June 1998 , pp. 293 - 302
Copyright
Copyright © Applied Probability Trust 1998 

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