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VECTOR-VALUED MARKOV DECISION PROCESSES WITH AVERAGE REWARD CRITERION: THE MULTICHAIN CASE

Published online by Cambridge University Press:  31 October 2000

Kazuyoshi Wakuta
Kazuyoshi Wakuta
Affiliation:
Nagaoka Technical College, Nagaoka, Niigata 940-8532, Japan, E-mail: wakuta@nagaoka-ct.ac.jp
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Abstract

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We study the multichain case of a vector-valued Markov decision process with average reward criterion. We characterize optimal deterministic stationary policies via systems of linear inequalities and discuss a policy iteration algorithm for finding all optimal deterministic stationary policies.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 14 , Issue 4 , October 2000 , pp. 533 - 548
Copyright
© 2000 Cambridge University Press