Constrained Markov Decision Processes

🤖 Plain-English Summary

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.

🔑 Key Findings

• 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.
• It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives.
• This framework describes dynamic decision problems arising frequently in many engineering fields.

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