Institute of Information Theory and Automation

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Ing. Miroslav Kárný, DrSc.

deputy head of the department
Research interests: 
adaptive system, decision making under uncertainty, Bayesian identification, merging prior information, multiple-participant decision making
Publications ÚTIA: 

Research interests: They cover conceptual, theoretical and algorithmic aspects of adaptive systems. Bayesian dynamic decision making (DM) and its extension, fully probabilistic design (FPD) of decision strategies, form its theoretical background. Conversion of the Bayesian decision paradigm into a generic, widely applicable, tool is his long-term aim sometimes hidden behind particular activities

Projects: Principal investigator about 20 projects,

Publications: 1 monograph, 6 edited books, about 400 works (about 100 journal papers); the list since 1989

Education: Ing. (MSc) Faculty of Nuclear Sciences and Physical Engineering (FJFI), Czech Technical University (CTU), 1973; CSc. (PhD) Institute of Information Theory and Automation (ÚTIA), Czechoslovak Academy of Sciences (ČSAV), 1978; DrSc. (DSc) ÚTIA ČSAV, 1990

Employment: ÚTIA since 1973

Teaching: Advanced course on Probabilistic Dynamic DM (1992-, FJFI CTU); 14 successfully concluded PhD supervision; now 1 PhD students at Faculty of Mathematics and Physics, Charles University; supervisor of many Bc and MS theses and of undergraduate research projects.

Awards: 2011 Frank Wilcoxon Prize; 2011 Outstanding Statistical Application Award of American Statistical Association; 2003, 2006 Best UTIA paper awards; 2003 Prize of the Ministry of Education, Youth and Sports of the Czech Republic for theoretical outcomes achieved within the IST Project ProDaCTool 12058; 1992 Award of Academy of Sciences of the Czech Republic for Nonlinear Estimation Theory; 1981 Award of Academy of Sciences of the Czech Republic for Bayesian Identification Theory

Others: Associate editor of KES journal; member of editorial boards in International Journal of Computational Intelligence Studies, Czech mutation of Control Engineering, International Journal of Hybrid Intelligent Systems and Springer Series on Advanced Intelligence, co-organiser of a range of international workshops, see, (notably, DM with multiple imperfect decision makers - in conjunction with 24th, 25th NIPS Conference, Whistler Canada 2010, Sierra Nevada Spain 2011, ECML/PKDD, Prague, CR, 2013, 30th NIPS Conference, Barcelona, Spain 2016).

admin: 2018-03-27 17:55

Person detail

Duration: 2016 - 2018
Rapid development of information and computer technology as well as availability of multiple, very frequently incompatible, informational sources have caused that decision makers (both humans and devices) are overloaded with information. Their imperfectness (i.e.
Duration: 2013 - 2016
Decision making (DM) is a targeted choice of actions based on given knowledge and preferences. Normatively, Bayesian DM, maximising expected utility, should be used under uncertainty but this happens less than desirable. Often, imperfection of the DM participant can be blamed as it limits the deliberation effort spent.
Duration: 2008 - 2011
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.
Duration: 2006 - 2009
Knowledge elicitation from extensive data files inevitably reduces the extracted information content. Results always serve to a subsequent, often dynamic, decision making. Its quality depends critically on the reduction made.
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.



Dr. Ing. Jan Schier
Ing. Josef Andrýsek Ph.D.
Ing. Pavel Ettler Ph.D.
Ing. Hong Gao Ph.D.
Ing. Petr Gebouský Ph.D.
Ing. Tatiana Valentine Guy Ph.D.
Ing. Li He Ph.D.
Ing. Nathalia Khailova Ph.D.
Ing. Jan Kracík Ph.D.
RNDr. Vladimíra Sečkárová Ph.D.
Ing. Jan Schier Ph.D.
Mgr. Jan Šindelář Ph.D.
Doc. Ing. Václav Šmídl Ph.D.
Fakulta jaderná a fyzikálně-inženýrská ČVUT