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On Average Reward Semi-Markov Decision Processes with a General Multichain Structure

L. Jianyong and Z. Xiaobo
Mathematics of Operations Research
Vol. 29, No. 2 (May, 2004), pp. 339-352
Published by: INFORMS
Stable URL: http://www.jstor.org/stable/30035686
Page Count: 14
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On Average Reward Semi-Markov Decision Processes with a General Multichain Structure
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Abstract

In this paper we investigate average reward semi-Markov decision processes with a general multichain structure using a data-transformation method. By solving the transformed discrete-time average Markov decision processes, we can obtain significant and interesting information on the original average semi-Markov decision processes. If the original semi-Markov decision processes satisfy some appropriate conditions, then stationary optimal policies in the transformed discrete-time models are also optimal in the original semi-Markov decision processes.

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