Optimized Bayesian Dynamic Advising: Theory and Algorithms (Advanced Information and Knowledge Processing) - Softcover

9781447156758: Optimized Bayesian Dynamic Advising: Theory and Algorithms (Advanced Information and Knowledge Processing)

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ISBN 10: 1447156757 ISBN 13: 9781447156758

Verlag: Springer, 2014

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A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world's leading groups in the area of Bayesian identification, control, and decision making.

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Written by one of the world s leading groups in the area of Bayesian identification, control and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising.
Starting from abstract ideas and formulations, and culminating in detailed algorithms, Optimized Bayesian Dynamic Advising comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modeling by dynamic mixture models and fully probabilistic dynamic optimization. The proposed non-standard problem formulation and its solution mark a significant contribution to the design of anthropocentric automation systems.
Written for a broad audience, including developers of algorithms and application engineers, researchers, lecturers and postgraduates, this book can be used as a reference tool, and an advanced text on Bayesian dynamic decision making.

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Verlag: Springer
Erscheinungsdatum: 2014
Sprache: Englisch
ISBN 10: 1447156757
ISBN 13: 9781447156758
Einband: Tapa blanda
Anzahl der Seiten: 548
Herausgeber: Karny Miroslav
Kontakt zum Hersteller: Nicht verf�gbar
Verantwortliche Person: CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Deutschland

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Verlag: Springer, 2005
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Optimized Bayesian Dynamic Advising

Karny, Miroslav

Verlag: Springer London, 2014

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a generic methodology with elaborated algorithmic image of probabilistic, possibly adaptive, optimised advisory system supporting dynamic decision making under uncertainty in a complex environmentDynamic, adaptive, mixture modelling of no. Bestandsnummer des Verk�ufers 4185330

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Miroslav Karny

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ISBN 10: 1447156757 ISBN 13: 9781447156758

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world's leading groups in the area of Bayesian identification, control, and decision making. 548 pp. Englisch. Bestandsnummer des Verk�ufers 9781447156758

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Optimized Bayesian Dynamic Advising

Miroslav Karny

Verlag: Springer London, Springer London Okt 2014, 2014

ISBN 10: 1447156757 ISBN 13: 9781447156758

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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This work summarizes the theoretical and algorithmic basis of optimized pr- abilistic advising. It developed from a series of targeted research projects s- ported both by the European Commission and Czech grant bodies. The source text has served as a common basis of communication for the research team. When accumulating and re ning the material we found that the text could also serve as � a grand example of the strength of dynamic Bayesian decision making, � a practical demonstration that computational aspects do matter, � a reference to ready particular solutions in learning and optimization of decision-making strategies, � a source of open and challenging problems for postgraduate students, young as well as experienced researchers, � a departure point for a further systematic development of advanced op- mized advisory systems, for instance, in multiple participant setting. These observations have inspired us to prepare this book. Prague, Czech Republic Miroslav K� arn� y October 2004 Josef B� ohm Tatiana V. Guy Ladislav Jirsa Ivan Nagy Petr Nedoma Ludv� k Tesa r Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 2 State of the art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 1 Operator supports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 2 Mainstream multivariate techniques . . . . . . . . . . . . . . . . . 4 1. 2. 3 Probabilistic dynamic optimized decision-making . . . . . . 6 1. 3 Developed advising and its role in computer support . . . . . . . . . 6 1. 4 Presentation style, readership andlayout . . . . . . . . . . . . . . . . . . . 7 1. 5 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Underlying theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 1 General conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 2 Basic notions and notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 548 pp. Englisch. Bestandsnummer des Verk�ufers 9781447156758

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Optimized Bayesian Dynamic Advising : Theory and Algorithms

Miroslav Karny

Verlag: Springer London, 2014

ISBN 10: 1447156757 ISBN 13: 9781447156758

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This work summarizes the theoretical and algorithmic basis of optimized pr- abilistic advising. It developed from a series of targeted research projects s- ported both by the European Commission and Czech grant bodies. The source text has served as a common basis of communication for the research team. When accumulating and re ning the material we found that the text could also serve as - a grand example of the strength of dynamic Bayesian decision making, - a practical demonstration that computational aspects do matter, - a reference to ready particular solutions in learning and optimization of decision-making strategies, - a source of open and challenging problems for postgraduate students, young as well as experienced researchers, - a departure point for a further systematic development of advanced op- mized advisory systems, for instance, in multiple participant setting. These observations have inspired us to prepare this book. Prague, Czech Republic Miroslav K arn y October 2004 Josef B ohm Tatiana V. Guy Ladislav Jirsa Ivan Nagy Petr Nedoma Ludv k Tesa r Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 2 State of the art . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 1 Operator supports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 2. 2 Mainstream multivariate techniques . . . . . . . . . . . . . . . . . 4 1. 2. 3 Probabilistic dynamic optimized decision-making . . . . . . 6 1. 3 Developed advising and its role in computer support . . . . . . . . . 6 1. 4 Presentation style, readership andlayout . . . . . . . . . . . . . . . . . . . 7 1. 5 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2 Underlying theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 1 General conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. 2 Basic notions and notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bestandsnummer des Verk�ufers 9781447156758

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