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Optimized Bayesian Dynamic Advising

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Optimized Bayesian Dynamic Advising Synopsis

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 Kn arnn y October 2004 Josef B· ohm Tatiana V. Guy Ladislav Jirsa Ivan Nagy Petr Nedoma Ludvn ?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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

About This Edition

ISBN: 9781447156758
Publication date:
Author: Miroslav Karny
Publisher: Springer an imprint of Springer London
Format: Paperback
Pagination: 529 pages
Series: Advanced Information and Knowledge Processing
Genres: Mathematical theory of computation
Pattern recognition
Human–computer interaction
Computer modelling and simulation
Artificial intelligence
Probability and statistics
Mathematical and statistical software

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