Continuous average control of piecewise deterministic Markov processes

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 relat...

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Huvudupphovsmän: Costa, Oswaldo Luiz do Valle, Dufour, François, 1965-...., chercheur en mathématiques appliquées (Författare, medförfattare)
Materialtyp: Livre numérique
Språk:Anglais
Publicerad: New York, NY : Springer New York [20..].
Cham : Springer Nature
Upplaga:1st ed. 2013.
Serie:SpringerBriefs in Mathematics
Länkar:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Anmärkning: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Continuous Average Control of Piecewise Deterministic Markov Processes, Texte imprimé, 9781461469841
• Continuous Average Control of piecewise deterministic Markov processes, Oswaldo Luiz do Valle Costa, François Dufour, 2013, New York[etc.], Springer, 1 vol. (XII-116 p.), Springer briefs in mathematics, 978-1-4614-6982-7
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245 1 0 |a Continuous average control of piecewise deterministic Markov processes   |c by Oswaldo Luiz do Valle Costa, François Dufour. 
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520 |a 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.  
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