Institute of Information Theory and Automation

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Department of Adaptive Systems

Secretary: 
Phone: 
266052061
286890420
Publications ÚTIA: 
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The Department of Adaptive Systems focuses predominantly on the design of decision-making systems, which modify their behavior according to the changing properties of their environment. This essential ability – adaptivity – enhances their efficiency. Decades of research have brought a number of conceptual, theoretical, algorithmic, software and application results. The applicability of adaptive systems is currently being extended toward complex scenarios by improving the classical adaptive systems and by developing their new versions.

The departmental “know-how” serves to resolve national as well as international research projects, running in collaboration with industry and government agencies. The interplay between theory and limited computing power is the common issue linking the various project domains. They include traffic control, management and control of technological systems, radiation protection, nuclear medicine, analysis of financial data, electronic democracy, etc. The increasing complexity of the problems addressed directs the main stream of the research toward decentralized control of large-scale systems and normative decision-making with multiple participants.

admin: 2018-06-04 14:32

Department detail

Ing. Lubomír Bakule CSc.
Ing. Alkomiet Belal
Ing. Květoslav Belda Ph.D.
Ing. Milan Berka
Ing. Josef Böhm CSc.
Ing. Jindřich Bůcha CSc.
Ing. Kamil Dedecius Ph.D.
Dr. Siavash Fakhimi Derakhshan Ph.D.
Ing. Tatiana Valentine Guy Ph.D.
Mgr. Kateřina Henclová (Márová)
Ing. Jitka Homolová Ph.D.
RNDr. Ladislav Jirsa Ph.D.
Ing. Miroslav Kárný DrSc.
Ing. Václav Kůs Ph.D.
Ing. Petr Nedoma CSc.
Ing. Milan Papež
Ing. Lenka Pavelková Ph.D.
Ing. Petr Pecha CSc.
Anthony Paul Quinn
Prof. Oleksandr Rezunenko Ph.D.
RNDr. Vladimíra Sečkárová Ph.D.
Dominika Smolková
Ing. Vít Škvára
Doc. Ing. Václav Šmídl Ph.D.
Ing. Jakub Štěch
Ing. Ondřej Tichý Ph.D.
Ing. Lukáš Ulrych
Ing. Petr Zagalak CSc.
Duration: 2004 - 2007
First version of a decision support system using biophysical and radiological data was practically tested. Some of its insufficiencies indicate improvement of the methodology of mixture analysis and extension of the data set by biochemical, histological and other medical quantities. The aims: 1.
Duration: 2004 - 2007
Aim 1 Development of implementable theory of Bayesian adaptive distributed decision making (DM) with multiple participants and multiple-criteria. It will provide: Fully probabilistic design (FPD) of adaptive strategies respecting changing environment and group aims.