Despite of huge progress in intelligent control, neural networks, fuzzy and nonlinear control, and other parts of control theory, the methods of linear control still remain a basis the other theories are compared with. Linear models have proved to be a relatively easy but powerful tool that has been successfully applied to many problems at work, and which has reached a high level of development during the last decades.

This research direction is concerned with identification and control of uncertain systems using Bayesian decision-making theory. The main advantage of this theory is consistency of the generated decision (i.e. estimates and control actions). However, solution of the implied recursive Bayesian relations is often available only approximately. 

Dynamic decision making (DM) maps knowledge into DM strategy, which ensures reaching DM aims under given constraints. Under general conditions, Bayesian DM, minimizing expected loss over admissible strategies, has to be used. Existing limitations of the paradigm impede its applicability to complex DM as:

Knowledge extraction maps extensive data sets on lower dimensional objects. Its results always serve to a subsequent, often dynamic, decision making. Decision-making quality is substantially influenced by the mapping used. This simple fact is relatively rarely respected by many elements in the overwhelming arsenal of existing mappings. A complete solution of decision making problems that includes explicitly the discussed mapping are severely limited by computational complexity (labelled as curse of dimensionality).  The project contributes to an improvement of this state via

The AS Department ensures, organizes and produces amount of lectures, educational materials, seminars, conferences and workshops within the domain of decision making, advanced control and related areas. The department produces a significant amount of educational material on Bayesian Decision Making. This page summarizes the information about the main educational activities held in the department.

Basic Publications

Development of software tools was never primary aim of our research, however development of methodologies and algorithms is impossible without proper software support. At present, we are dealing with increasingly more complex systems, hence requirement on reliability and flexiblity of software tools are growing. The following projects are actively developped and maintained:

Advisory System: Optimizing Support Tool for Decision Makers