Foundations Non Stationary Dynamic Programming by Hinderer (14 results)

Broschiert. Condition: Gut. VI, 160 Seiten : graph. Darst.; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); leichte altersbedingte Anbräunung des Papiers; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 320.

Softcover. Condition: Bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Légères traces d'usure sur la couverture. Couverture légèrement déchirée. Salissures sur la tranche. Pages cornées. Edition 1970. Tome 33. Ammareal reverse jusqu'à 15% du prix n ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Slightly creased cover. Slight signs of wear on the cover. Slightly torn cover. Stains on the edge. Dog-eared pages. Edition 1970. Volume 33. Ammareal gives back up to 15% of this item's net price to charity organizations.

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Gr.-8°, Softcover/Paperback. 1.Auflage,. 160 Seiten Einband etwas berieben, Bibl.Ex., sonst guter und sauberer Zustand Sprache: Englisch Gewicht in Gramm: 360.

Paperback/ broschiert. Condition: Gut. 160 S. Guter Zustand/ Good Ex-Library. Brownish paper. Stamped edges. Cover edges faded. Sprache: Englisch Gewicht in Gramm: 315.

Paperback. Condition: Brand New. 172 pages. 10.00x7.01x0.39 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results.

Taschenbuch. Condition: Neu. Foundations of Non-stationary Dynamic Programming with Discrete Time Parameter | K. Hinderer | Taschenbuch | vi | Englisch | Springer | EAN 9783540049562 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results. 172 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes th.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The present work is an extended version of a manuscript of a course which the author taught at the University of Hamburg during summer 1969. The main purpose has been to give a rigorous foundation of stochastic dynamic programming in a manner which makes the theory easily applicable to many different practical problems. We mention the following features which should serve our purpose. a) The theory is built up for non-stationary models, thus making it possible to treat e.g. dynamic programming under risk, dynamic programming under uncertainty, Markovian models, stationary models, and models with finite horizon from a unified point of view. b) We use that notion of optimality (p-optimality) which seems to be most appropriate for practical purposes. c) Since we restrict ourselves to the foundations, we did not include practical problems and ways to their numerical solution, but we give (cf.section 8) a number of problems which show the diversity of structures accessible to non stationary dynamic programming. The main sources were the papers of Blackwell (65), Strauch (66) and Maitra (68) on stationary models with general state and action spaces and the papers of Dynkin (65), Hinderer (67) and Sirjaev (67) on non-stationary models. A number of results should be new, whereas most theorems constitute extensions (usually from stationary models to non-stationary models) or analogues to known results.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 172 pp. Englisch.