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Controlled Markov set-chains under average criteria
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DOI：10.1016/S0096-3003(99)00241-6.png)
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In this payer, applying an interval arithmetic analysis, we consider the average case of controlled Markov set-chains, whose process allows for fluctuating transition matrices at each step in time. We introduce a a-step contractive property for the average case, under which a Pareto optimal periodic policy is characterized as a maximal solution of optimality equation. Also, in the class of stationary policies, the behavior of the expected reward over T-horizon as T approaches infinity is investigated and the left- and right-hand side optimality equations are given, by which a Pareto optimal stationary policy is found. As a numerical example, the Taxicab problem is considered. (C) 2001 Elsevier Science Inc. All rights reserved.
Keyword:
controlled Markov set-chains
average reward criterion
Pareto optimal
minorization condition
interval arithmetic
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3.4
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2.3W
被引数:
3.3W
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