The tutorial section is a comprehensive user guide for all main features within the Hugin GUI. You will learn to build Hugin Knowledge Bases using Bayesian network and influence diagrams. Furthermore you will learn to use the major features.

Building a Bayesian Network
This tutorial shows you how to implement a small Bayesian network in the Hugin GUI.

Building an Influence Diagram
This tutorial shows you how to implement a small influence diagram in the Hugin GUI. It helps plantation owner Apple Jack to decide whether or not to give his apple tree, which is losing its leaves, some treatment.

Using the Learning Facilities
Currently the Hugin GUI supports two kinds of parametric learning; adaptation and EM. Parametric learning is the task where you have build the structure of your knowledge base and wants to fill out the conditional probability tables. Look into our two examples of how its is done.

Building Object Oriented Bayesian Networks
This tutorial shows how to implement a small object-oriented Bayesian network in the Hugin GUI.

Using the Table Generator
This tutorial shows you how the table generator functionality can be used to simplify how tables are specified for discrete chance nodes.

Case Generator
Shows you how to generate a database of cases from an existing knowledge base.