Dynamic Optimization Deterministic and Stochastic Models /

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Hinderer, Karl (Autor), Rieder, Ulrich (Autor), Stieglitz, Michael (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Universitext,
Temas:
Operations research.
Management science.
System theory.
Control theory.
Mathematical optimization.
Probabilities.
Operations Research, Management Science .
Systems Theory, Control .
Discrete Optimization.
Probability Theory.
Acceso en línea:Texto Completo

MARC

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100 1 |a Hinderer, Karl.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Dynamic Optimization  |h [electronic resource] :  |b Deterministic and Stochastic Models /  |c by Karl Hinderer, Ulrich Rieder, Michael Stieglitz. 
250 |a 1st ed. 2016. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2016. 
300 |a XXII, 530 p. 22 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Universitext,  |x 2191-6675 
505 0 |a Introduction and Organization of the Book -- Part I Deterministic Models -- Part II Markovian Decision Processes -- Part III Generalizations of Markovian Decision Processes -- Part IV Appendix. 
520 |a This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained. 
650 0 |a Operations research. 
650 0 |a Management science. 
650 0 |a System theory. 
650 0 |a Control theory. 
650 0 |a Mathematical optimization. 
650 0 |a Probabilities. 
650 1 4 |a Operations Research, Management Science . 
650 2 4 |a Systems Theory, Control . 
650 2 4 |a Discrete Optimization. 
650 2 4 |a Probability Theory. 
700 1 |a Rieder, Ulrich.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Stieglitz, Michael.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783319488134 
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950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713) 

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