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Robustness of policies in constrained Markov decision processes

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2 Author(s)
Zadorojniy, A. ; Intel Israel Ltd., Haifa, Israel ; Shwartz, A.

We consider the optimization of finite-state, finite-action Markov decision processes (MDPs), under constraints. Cost and constraints are discounted. We introduce a new method for investigating the continuity, and a certain type of robustness, of the optimal cost and the optimal policy under changes in the constraints. This method is also applicable for other cost criteria such as finite horizon and infinite horizon average cost.

Published in:

Automatic Control, IEEE Transactions on  (Volume:51 ,  Issue: 4 )