Optimized Bayesian Dynamic Advising : Theory and Algorithms
Language: English
Published by Springer, 2014
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . …
Seller Inventory # 9781447156758
- Title
- Optimized Bayesian Dynamic Advising : Theory and Algorithms
- Author
- Miroslav Karny
- Publisher
- Springer
- Publication year
- 2014
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1447156757
- ISBN 13
- 9781447156758
- Item weight
- 820 grams
- Dimensions
- 235x155x30 mm
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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