ISBN: 9781447142843 - stochastic recursive algorithms for optimization: simultaneous perturbation methods: 434 (11 risultati)

Condizione: New.

Condizione: New. In English.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms:- are easily implemented;- do not require an explicit system model; and- work with real or simulated data.Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix.The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.…

Paperback. Condizione: Brand New. 322 pages. 9.00x6.00x0.75 inches. In Stock.

Taschenbuch. Condizione: Neu. Stochastic Recursive Algorithms for Optimization | Simultaneous Perturbation Methods | S. Bhatnagar (u. a.) | Taschenbuch | Lecture Notes in Control and Information Sciences | xvii | Englisch | 2012 | Springer | EAN 9781447142843 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condizione: As New. Unread book in perfect condition.

Condizione: gut. Stochastic Recursive Algorithms for Optimization In englischer Sprache. pages.

Condizione: new. Questo è un articolo print on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms:- are easily implemented;- do not require an explicit system model; and- work with real or simulated data.Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix.The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value. 320 pp. Englisch.…

Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Algorithms described perform better in real-life settings than many previously described in the literature Detailed mathematical treatment of the algorithms proposed is provided using both gradient- and Hessian-based methods Both constraine.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms:¿ are easily implemented;¿ do not require an explicit system model; and¿ work with real or simulated data.Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix.The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.…