You have the opportunity to use the HUGIN System through HUGIN Runtime - an easy-to-use graphical environment. You can also use the HUGIN API (Application Program Interface) which comes as a library for C (or C++). More information about the versions of the HUGIN System that are for sale is found in the versions section.
The HUGIN System can be used to construct models as components in an application (mostly) in the area of decision support and expert systems. The application can communicate with the constructed component models either through DDE or by using the HUGIN API.
In extension to Bayesian belief networks lies the concept of influence diagrams allowing you to create decision support directly through certain action nodes. If you are not familiar with influence diagrams you can also read about them in the basic concepts section.
In the basic concepts section you can also find a specification of the Bayesian belief network technology supported by the HUGIN System.
Examples provide one of the best ways to learn about a new concept. You can get an idea of the possibilities of Bayesian belief networks and influence diagrams in the examples section.
A more complete mathematical description of Bbns and Influence diagrams can be found in the book "Introduction to Bayesian Networks" by Finn Verner Jensen.
In the HUGIN API section, you can read about the opportunity to include HUGIN Bayesian belief networks and influence diagrams in C (or C++) programs.
You can get a detailed view of the components of the HUGIN System by reading the components desciption.
In Bayesian belief networks the rumour problem appears when a cause can influence the same event through different paths in the network.
The problem was solved and general methods were made available to be used in any domain which can be modelled by a Bayesian belief network.
The methods have been programmed into a general development system, which is easy to use for anyone who wishes to construct an expert system based on Bayesian belief networks. The system is called HUGIN. Over the years the system has been extended with the facility of influence diagrams. Also, there has been research in trying to allow continuous nodes in the models. This has been added to the system in the case of continuous nodes with a Gaussian (normal) distribution.