THE HUGIN TOOL FOR PROBABILISTIC GRAPHICAL MODELS

Abstract

As the framework of probabilistic graphical models becomes increasingly popular for knowledge representation and inference, the need for efficient tools for its support is increasing. The Hugin Tool is a general purpose tool for construction, maintenance, and deployment of Bayesian networks and influence diagrams. This paper surveys the key functionality of the Hugin Tool and reports on new advances of the tool. Furthermore, an empirical analysis reports on the efficiency of the Hugin Tool on common inference and learning tasks.