Preface.- Probability tools for stochastic modeling.- Renewal theory.- Markov Chains.- Markov renewal theory, Markov random walks and semi-Markov processes.- Functionals of (J-X) processes.- Non-homogeneous Markov and semi-Markov processes.- Markov and semi-Markov reward processes.- References.- Author index.- Subject index.
Aims to give to the reader the tools necessary to apply semi-Markov processes in real-life problems.
The book is self-contained and, starting from a low level of probability concepts, gradually brings the reader to a deep knowledge of semi-Markov processes.
Presents homogeneous and non-homogeneous semi-Markov processes, as well as Markov and semi-Markov rewards processes.
The concepts are fundamental for many applications, but they are not as thoroughly presented in other books on the subject as they are here.
First book to present the theory of semi-Markov processes in view of its applications to real-world problems