Continuous-Time Markov Decision Processes Theory and Applications /

• Main Authors: Guo, Xianping (Author), Hernández-Lerma, Onésimo (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
• Series: Stochastic Modelling and Applied Probability, 62
• Subjects: Mathematics.; Mathematical optimization.; Operations research.; Management science.; Probabilities.; Optimization.; Probability Theory and Stochastic Processes.; Operations Research, Management Science.

Continuous-time Markov decision processes (MDPs), also known as controlled Markov chains, are used for modeling decision-making problems that arise in operations research (for instance, inventory, manufacturing, and queueing systems), computer science, communications engineering, control of populati...

Table of Contents:

• and Summary
• Continuous-Time Markov Decision Processes
• Average Optimality for Finite Models
• Discount Optimality for Nonnegative Costs
• Average Optimality for Nonnegative Costs
• Discount Optimality for Unbounded Rewards
• Average Optimality for Unbounded Rewards
• Average Optimality for Pathwise Rewards
• Advanced Optimality Criteria
• Variance Minimization
• Constrained Optimality for Discount Criteria
• Constrained Optimality for Average Criteria.