Vector-valued Markov decision processes and the systems of linear inequalities

Kazuyoshi Wakuta

Stochastic Processes and their Applications, 1995, vol. 56, issue 1, 159-169

Abstract: For a vector-valued Markov decision process, we characterize optimal (deterministic) stationary policies by systems of linear inequalities and present an algorithm for finding all optimal stationary policies from among all randomized, history-remembering ones. The algorithm consists of improving the policies and of checking the optimality of a policy by solving the associated system of linear inequalities via Fourier elimination.

Keywords: Dynamic; programming; Markov; decision; process; Multiobjective; Linear; inequalities; Fourier; elimination (search for similar items in EconPapers)
Date: 1995
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(94)00064-Z
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:56:y:1995:i:1:p:159-169

Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().