Optimized Bayesian Dynamic Advising: Theory and Algorithms

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 así 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 and layout................... 7 1. 5 Acknowledgements...................................... 10 2 Underlying theory......................................... 11 2. 1 General conventions..................................... 11 2.

Book Details

• Author: Miroslav Karny
• Publisher: Springer
• eBook ISBN: 9781846282546, 1846282543
• Print ISBN: 9781852339289, 1852339284