Institute of Information Theory and Automation

Department of Decision-Making Theory

Head of the Department:
Martin Kružík

Deputy head of the Department:
František Matúš

Marie Kolářová

phone: +420 286 581 419
staff: people, Ph.D. students
List of publications, courses, projects, seminars

Most of the research activities of the department belong to the field of applied mathematics. The focus is on theoretical problems as well as problems connected with implementation of methods in the following areas:

  • mathematical optimization
  • nonsmooth analysis
  • differential equations
  • variational problems
  • probabilistic models of decision support systems
  • conditional independence structures
  • alternative calculi of uncertainty in artificial intelligence


Last events:

Mariánská - zimní pohled

Workshop on Variational Analysis and Optimization is an annual workshop organized by members of the Czech Academy of Sciences. It is an informal meeting of people interested in various topics of optimization theory. It combines a mathematical program in the afternoon/evening with a free program in the morning/early afternoon, when one can enjoy the beautiful scenery, go hiking, skiing or just discuss mathematics. Because of its location on the Czech-German border, it is suited mainly for Czech and German researchers.

Mariánská - zimní pohled

January 29 - February 2, Mariánská, Czech Republic

The Winter School of Department of Decision-Making Theory is a popular meeting point of students and researchers from the department and other colaborating researchers from several Czech institutions as well as guests from abroad. It is held in the UTIA's chalet.

The program of the 2017 edition of the MTR Winter School will consist mainly of tutorial talks given by participants.

The theory of belief functions, also referred to as evidence theory or Dempster-Shafer theory, is a well established general framework for reasoning with uncertainty, with well understood connections to other frameworks such as probability, possibility and imprecise probability theories. First introduced by Arthur P. Dempster in the context of statistical inference, the theory was later developed by Glenn Shafer into a general framework for modeling epistemic uncertainty.
Responsible for information: MTR
Last modification: 05.09.2012
Institute of Information Theory and Automation