Continuous-Time Markov Decision Processes
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 populations (such as fisheries and epidemics), and management science, among many other fields. This volume provides a unified, systematic, self-contained presentation of recent developments on the theory and applications of continuous-time MDPs. The MDPs in this volume include most of the cases that arise in applications, because they allow unbounded transition and reward/cost rates. Much of the material appears for the first time in book form.
To the best of our knowledge, it is the first book completely devoted to continuous-time Markov Decision ProcessesIt studies continuous-time MDPs allowing unbounded transition rates, which is the case in most applicationsIt is thus distinguished from other books that contain chapters on the continuous-time case