Seller: Lavendier Books, Foster, RI, U.S.A.
hardcover. Condition: As New. Springer Verlag; London, 2006. Hardcover. A Near Fine, binding firm, interior and extremities tidy, book appears unread, trace handling marks, mild crimping bottom spine edge, small and faint smudge mark on fore-edge, CD-ROM included in un-opened plastic pocket affirmed to rear pastedown, scratch mark mid rear board, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 529pp., references, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.
Published by Springer, 2005
Language: English
Seller: Antiquariat Thomas Haker GmbH & Co. KG, Berlin, Germany
Association Member: GIAQ
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Add to basketHardcover. Condition: Sehr gut. 546 S.; Ill. Very good. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 1080.
Condition: New. pp. 548.
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
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Add to basketCondition: New. 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. It is accompanied by a CD that contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the important areas. Editor(s): Karny, Miroslav (Academy of Sciences of the Czech Republic, Prague, Czech Republic). Series: Advanced Information and Knowledge Processing. Num Pages: 546 pages, 6 black & white tables, biography. BIC Classification: PBU; UMB. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 30. Weight in Grams: 2070. . 2005. 2006. Hardback. . . . .
Condition: New. 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. It is accompanied by a CD that contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the important areas. Editor(s): Karny, Miroslav (Academy of Sciences of the Czech Republic, Prague, Czech Republic). Series: Advanced Information and Knowledge Processing. Num Pages: 546 pages, 6 black & white tables, biography. BIC Classification: PBU; UMB. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 30. Weight in Grams: 2070. . 2005. 2006. Hardback. . . . . Books ship from the US and Ireland.
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Add to basketCondition: New. pp. 548 Illus.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
US$ 175.17
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Seller: Best Price, Torrance, CA, U.S.A.
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Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Published by Springer London Ltd, London, 2014
ISBN 10: 1447156757 ISBN 13: 9781447156758
Language: English
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Paperback. Condition: new. Paperback. 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . r Contents 1 Introduction . 1 Motivation . 2 State of the art . 1 Operator supports . 2 Mainstream multivariate techniques . 3 Developed advising and its role in computer support . 10 2 Underlying theory . 1 General conventions . 2 Basic notions and notations . Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Springer London Ltd, England, 2005
ISBN 10: 1852339284 ISBN 13: 9781852339289
Language: English
Seller: Grand Eagle Retail, Mason, OH, U.S.A.
Hardcover. Condition: new. Hardcover. 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, the book 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.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. A CD contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the most important and complex areas of the material presented. r Contents 1 Introduction . 1 Motivation . 2 State of the art . 1 Operator supports . 2 Mainstream multivariate techniques . 3 Developed advising and its role in computer support . 10 2 Underlying theory . 1 General conventions . 2 Basic notions and notations . Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
US$ 205.62
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Add to basketCondition: As New. Unread book in perfect condition.
Published by Springer, 2005
Language: English
Seller: Books in my Basket, New Delhi, India
US$ 185.91
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Add to basketHardcover. Condition: New. ISBN:9781852339289.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Seller: Books Puddle, New York, NY, U.S.A.
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketTaschenbuch. Condition: 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
US$ 215.13
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Add to basketGebunden. Condition: New. 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.
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
US$ 269.67
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Add to basketCondition: New. Editor(s): Karny, Miroslav (Academy of Sciences of the Czech Republic, Prague, Czech Republic). Series: Advanced Information and Knowledge Processing. Num Pages: 546 pages, 6 black & white tables, biography. BIC Classification: UFM; UGK; UYQ; UYQP; UYZG. Category: (G) General (US: Trade). Dimension: 235 x 155 x 28. Weight in Grams: 831. . 2014. Paperback. . . . .
Condition: New. Editor(s): Karny, Miroslav (Academy of Sciences of the Czech Republic, Prague, Czech Republic). Series: Advanced Information and Knowledge Processing. Num Pages: 546 pages, 6 black & white tables, biography. BIC Classification: UFM; UGK; UYQ; UYQP; UYZG. Category: (G) General (US: Trade). Dimension: 235 x 155 x 28. Weight in Grams: 831. . 2014. Paperback. . . . . Books ship from the US and Ireland.
Published by Springer London Okt 2005, 2005
ISBN 10: 1852339284 ISBN 13: 9781852339289
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
US$ 299.44
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Add to basketBuch. Condition: Neu. 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.
Published by Springer London Ltd, London, 2014
ISBN 10: 1447156757 ISBN 13: 9781447156758
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
US$ 339.02
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Add to basketPaperback. Condition: new. Paperback. 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . r Contents 1 Introduction . 1 Motivation . 2 State of the art . 1 Operator supports . 2 Mainstream multivariate techniques . 3 Developed advising and its role in computer support . 10 2 Underlying theory . 1 General conventions . 2 Basic notions and notations . Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Published by Springer London Ltd, England, 2005
ISBN 10: 1852339284 ISBN 13: 9781852339289
Language: English
Seller: AussieBookSeller, Truganina, VIC, Australia
US$ 372.85
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Add to basketHardcover. Condition: new. Hardcover. 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, the book 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.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. A CD contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the most important and complex areas of the material presented. r Contents 1 Introduction . 1 Motivation . 2 State of the art . 1 Operator supports . 2 Mainstream multivariate techniques . 3 Developed advising and its role in computer support . 10 2 Underlying theory . 1 General conventions . 2 Basic notions and notations . Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.