Constrained Markov Decision Processes

This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs. A thorough overview of these applications is presented in the introduction.

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• 1 Unlike the single controller case considered in many other books, the author considers a single controller with several objectives, such as minimizing delays and loss, probabilities, and maximization of throughputs.
• 2 It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives.
• 3 This framework describes dynamic decision problems arising frequently in many engineering fields.

Mathematical breakthroughs form the theoretical backbone of science, cryptography, data analysis, and engineering.

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