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Bayesian Decision Making Library BDM

The library is designed using object oriented approach where decision-making is implemneted as a method of dedicated object: decision-maker. The library contains many commonly known decision-makers such as estimators and Bayesian filters. Support for control-oriented decision-makers (LQG control) is under development.

Design philosophy of the toolbox is tocreate a close image of the underlying theory. The library is build from objects representing random variables, probability density functions (pdfs) and Bayesian models. Calculus with probability density functions is implemented eiter as:

  • methods of classes representing pdfs: marginalization and conditioning
  • special types of pdf classes: the chain rule
  • and operation of class Bayesian model: the Bayes rule.

The library also contain supporting classes for running experiments with Bayesian decision makers, such as:

  • loggers: classes for recording results and intermediate results of the experiement in various formats.
  • user info: classess for loading and storing experiment setup (parameters, conditions, etc.) in XML for easy editation by the user.

For more information see project page:


Support of grants

  • Centre of applied research DAR, Ministry of Education, Youth and Sports of the Czech Republic, 1M6 798 555 601
  •  GA ČR 102/08/P250, 2008-2010


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