Continuous average control of piecewise deterministic Markov processes

Resource Information

The work Continuous average control of piecewise deterministic Markov processes represents a distinct intellectual or artistic creation found in University of Missouri Libraries. This resource is a combination of several types including: Work, Language Material, Books.

Label

Continuous average control of piecewise deterministic Markov processes

Statement of responsibility

Oswaldo Luiz do Valle Costa, Francois Dufour

Creator

• Costa, Oswaldo Luiz do Valle

Contributor

• Dufour, François, (Mathematician)

Subject

• Complex Systems.
• Continuous Optimization
• Continuous Optimization.
• Control theory -- Mathematical models
• Control theory -- Mathematical models
• Control theory -- Mathematical models
• Distribution (Probability theory)
• Electronic books
• Electronic bookss
• MATHEMATICS -- Calculus
• MATHEMATICS -- Mathematical Analysis
• Markov processes
• Markov processes
• Markov processes
• Mathematics
• Mathematics.
• Operations Research, Management Science
• Operations Research, Management Science.
• Probability Theory and Stochastic Processes
• Probability Theory and Stochastic Processes.
• Systems Theory, Control
• Systems Theory, Control.
• Complex Systems

Language

eng

Summary

"The intent of this book is to present recent results in the control theory for the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs). The book focuses mainly on the long run average cost criteria and extends to the PDMPs some well-known techniques related to discrete-time and continuous-time Markov decision processes, including the so-called "average inequality approach'', "vanishing discount technique'' and "policy iteration algorithm''. We believe that what is unique about our approach is that, by using the special features of the PDMPs, we trace a parallel with the general theory for discrete-time Markov Decision Processes rather than the continuous-time case. The two main reasons for doing that is to use the powerful tools developed in the discrete-time framework and to avoid working with the infinitesimal generator associated to a PDMP, which in most cases has its domain of definition difficult to be characterized. Although the book is mainly intended to be a theoretically oriented text, it also contains some motivational examples. The book is targeted primarily for advanced students and practitioners of control theory. The book will be a valuable source for experts in the field of Markov decision processes. Moreover, the book should be suitable for certain advanced courses or seminars. As background, one needs an acquaintance with the theory of Markov decision processes and some knowledge of stochastic processes and modern analysis."--Publisher's website

Member of

• SpringerBriefs in mathematics

Cataloging source

GW5XE

Dewey number

515/.642

Illustrations

illustrations

Index

index present

LC call number

QA402.3

LC item number

.C67 2013

Literary form

non fiction

Nature of contents

• dictionaries
• bibliography

Series statement

SpringerBriefs in mathematics,