9783030296919 - Neural Approximations for Optimal Control and Decision (Communications and Control Engineering) de Zoppoli, Riccardo; Sanguineti, Marcello; Gnecco, Giorgio; Parisin... (10 resultados)

Hardcover. Condición: Very Good. 1. Auflage. unread, with a mimimum of shelfwear.

Condición: New. pp. XVIII, 517 99 illus., 8 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural Approximations for Optimal Control and Decisionprovides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.Features of the text include:- a general functional optimization framework;- thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;- comparison of classical and neural-network based methods of approximate solution;- bounds to the errors of approximate solutions;- solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with onedecision maker or several;- applications of current interest: routing in communications networks, traffic control, water resource management, etc.;and- numerous, numerically detailed examples.The authors' diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.

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

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Material is an up-to-date treatment of optimal control problems which have thus far been difficult to solve Applications selected have major current interest: routing in communications networks, freeway traffic control, water resources managem.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Neural Approximations for Optimal Control and Decisionprovides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.Features of the text include:- a general functional optimization framework;- thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;- comparison of classical and neural-network based methods of approximate solution;- bounds to the errors of approximate solutions;- solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several;- applications of current interest: routing in communications networks, traffic control, water resource management, etc.;and- numerous, numerically detailed examples.The authors' diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering. 536 pp. Englisch.

Buch. Condición: Neu. Neural Approximations for Optimal Control and Decision | Riccardo Zoppoli (u. a.) | Buch | Communications and Control Engineering | xviii | Englisch | 2019 | Springer | EAN 9783030296919 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.Features of the text include:¿ a general functional optimization framework;¿ thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;¿ comparison of classical and neural-network based methods of approximate solution;¿ bounds to the errors of approximate solutions;¿ solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with onedecision maker or several;¿ applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and¿ numerous, numerically detailed examples.The authors¿ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 536 pp. Englisch.

Condición: New. Print on Demand pp. XVIII, 517 99 illus., 8 illus. in color.

Condición: New. PRINT ON DEMAND pp. XVIII, 517 99 illus., 8 illus. in color.