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Ergodic control of Markov Chains with Constraints – The General Case

Borkar, VS (1994) Ergodic control of Markov Chains with Constraints – The General Case. In: SIAM Journal on Control and Optimization, 32 (1). pp. 176-186.

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The problem of controlling a Markov chain on a countable state space with ergodic or ’long run average’ cost is studied in the presence of additional constraints, requiring finitely many (say, m) other ergodic costs to satisfy prescribed bounds. Under extremely general conditions, it is proved that an optimal stationary randomized strategy can be found that requires at most m randomizations. This generalizes a result of Ross.

Item Type: Journal Article
Publication: SIAM Journal on Control and Optimization
Publisher: Society for Industrial & Applied Mathematics
Additional Information: The copyright of this article belongs to Society for Industrial & Applied Mathematics.
Keywords: Controlled Markov chains;Control under constraintsErgodic control;Randomized strategy;Ergodic occupation measures
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 06 Jul 2006
Last Modified: 27 Feb 2019 10:26
URI: http://eprints.iisc.ac.in/id/eprint/7889

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