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

Abstract

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.

Type
Research Article
Copyright
© 2000 Cambridge University Press

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