MDPs have been applied in many areas, such as communications, signal processing, artificial intelligence, stochastic scheduling and manufacturing systems, discrete event systems, management and economies. This book examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents three main topics: a new methodology for MDPs with discounted total reward criterion; transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; application of MDPs in stochastic environments, which greatly extends the area where MDPs can be applied. Each topic is used to study optimal control problems or other types of problems.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
<p>Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters. </p><p></p><p><em>Markov Decision Processes With Their Applications</em> examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents four main topics that are used to study optimal control problems:</p><p></p><p>*a new methodology for MDPs with discounted total reward criterion;</p><p></p><p>*transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs;</p><p></p><p>*MDPs in stochastic environments, which greatly extends the area where MDPs can be applied;</p><p></p><p>*applications of MDPs in optimal control of discrete event systems, optimal replacement, and optimal allocation in sequential online auctions. </p><p></p><p>This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce.</p>
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 17,09 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiEUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costiDa: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents new branches for Markov Decision Processes (MDP)Applies new methodology for MDPs with discounted total reward criterionOffers new applications of MDPs in areas such as the control of discrete event systems and the optimal allocatio. Codice articolo 4174591
Quantità: Più di 20 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters.Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents four main topics that are used to study optimal control problems: a new methodology for MDPs with discounted total reward criterion; transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; MDPs in stochastic environments, which greatly extends the area where MDPs can be applied; applications of MDPs in optimal control of discrete event systems, optimal replacement, and optimal allocation in sequential online auctions.This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 316 pp. Englisch. Codice articolo 9781441942388
Quantità: 1 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters.Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents four main topics that are used to study optimal control problems: a new methodology for MDPs with discounted total reward criterion; transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; MDPs in stochastic environments, which greatly extends the area where MDPs can be applied; applications of MDPs in optimal control of discrete event systems, optimal replacement, and optimal allocation in sequential online auctions.This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce. Codice articolo 9781441942388
Quantità: 1 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 12688011-n
Quantità: Più di 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 12688011
Quantità: Più di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 12688011
Quantità: Più di 20 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 316. Codice articolo 263075684
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 316 6 Illus. Codice articolo 5853627
Quantità: 4 disponibili
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 537. Codice articolo C9781441942388
Quantità: Più di 20 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 298 pages. 9.00x6.00x0.72 inches. In Stock. Codice articolo x-1441942386
Quantità: 2 disponibili