Institute of Information Theory and Automation

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Clusters of Research Oriented Activities

Bayesian Dynamic Decision Making

Dynamic decision making (DM) maps knowledge into DM strategy, which ensures reaching DM aims. Under general conditions, Bayesian DM, minimizing expected loss over admissible strategies, has to be used. Long-term research covers: i) theoretical support whole design leading to fully probabilistic design generalising Bayesian DM; ii) support of particular steps of DM, like structure estimation; iii) formulation and solutions specific tasks as like probabilistic support of operators or trading with futures; iv) algorithmisation facing, for instance, poorly informative data, local nature of models, approximate estimation of dynamic mixtures; v)  distributed DM, especially, performed by decision makers with limited cognitive abilities.      

Advanced Control

The inspected problems ranges from extansions of  linear control theories, over adaptive, numerically robust, linear-quadratic control, its extension to predictive controllers oriented towards mechatronic systems. The progress is driven by advanced applications oriented, for instance, towards rolling mills or electrical motors. They call for ellaborating various technigues like: i) non-linear filtering based on marginalised particle filtering or design of soft sensors; ii)  control design for specific, say, mechatronic systems or universal controlled high-dimensional dynamic mixture models; iii) inspecting dual and distributed variants of control desing.

Traffic Control

Strong research group oriented on traffic-control domain covers theoretical, algorithmic and application-specific aspects like: i) traffic-lights based adaptive hierarchical control of town traffic; ii) estimation of an exact position of vehicle facing GPS inaccessability; iii) personal advanced system supporting economical driving style.  

Nuclear Safety

Advanced physical modelling, custemisation of general techniques to Czech teritory, tailoring of advanced Bayesian technique for data asimilation, specific algorithms fighting with problem dimensionality are key techniques developed and used for solving nuclear safety problems, especially, for advising to authorities in case of nuclear (possibly chemical or even terroristic) threats.      

Medical applications

Bayesian techniques have been traditionally developed, refined and applied in variaty of medical, predominantly dignostics, problems.  Beign improtant on their own, they have served as test field with a a alck of universal (physical-like) models, very limited amount of very uncertain measured data of mixed nature and significant consequences for patients with dangerous diseases like thyroid gland cancer or lymphedema. 

Accumulation of Acquired Knowledge 

Complexity of the targeted research makes care about knowledge accumulation in software and educational material its indispenseable part.  

smidl: 2011-02-15 19:16