Optimized Bayesian Dynamic Advising: Theory and Algorithms

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 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 and layout………………. 7 1. 5 Acknowledgements……………………………….. 10 2 Underlying theory………………………………….. 11 2. 1 General conventions………………………………. 11 2. 2 Basic notions and notations………………………….Optimized Bayesian Dynamic Advising: Theory and Algorithms 1st Edition is written by Miroslav Karny and published by Springer. ISBNs for Optimized Bayesian Dynamic Advising are 9781846282546, 1846282543 and the print ISBNs are 9781852339289, 1852339284.