Optimized Bayesian Dynamic Advising Theory and Algorithms [Paperback]

A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the worlds leading groups in the area of Bayesian identification, control, and decision making.

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 layoul³2