Ergodic control of Markov chains with constraints-The general case

Ergodic control of Markov chains with constraints-The general case

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Article ID: iaor19941567
Country: United States
Volume: 32
Issue: 1
Start Page Number: 176
End Page Number: 186
Publication Date: Jan 1994
Journal: SIAM Journal on Control and Optimization
Authors:
Abstract:

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 additinal 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.

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