This book presents the second part of a two-volume series devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes. As in Volume I (AM 30 Discrete-Time Markov Control Processes: Basic Optimality Criteria), interest is mainly confined to MCPs with Borel state and control spaces. However, an important feature of the present volume is that is it essentially self-contained and can be read independently of Volume I, because the assumptions on the control models are usually different.

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Devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes, the text is mainly confined to MCPs with Borel state and control spaces. Although the book follows on from the author's earlier work, an important feature of this volume is that it is self-contained and can thus be read independently of the first.
The control model studied is sufficiently general to include virtually all the usual discrete-time stochastic control models that appear in applications to engineering, economics, mathematical population processes, operations research, and management science.

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