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.
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