On January 13th, 2003 - we have released new versions of the Hugin Graphical User Interface (v6.2) and Hugin Decision Engine (v6.0).
The main new features of this release
are: support for object-oriented Bayesian
networks and influence diagrams in the Hugin Decision Engine, a new
algorithm for learning the structure of a Bayesian network from a database of
cases in the Hugin Graphical User Interface, and various other improvements of
the Hugin Graphical User Interface.
The PC algorithm for learning the
graphical structure of a Bayesian network from a database of cases has been
extended with a necessary path condition. This condition is a necessary
condition for the existence of a perfect map of the conditional dependence and
independence statements derived by statistical tests. This has produced a new
algorithm, which will be referred to as the NPC
algorithm. The NPC algorithm has a number of advantages over the PC
algorithm. For instance, the user now has the possibility to interact with the
learning process in order to resolve structural uncertainties by making
decisions on the presence or absence of uncertain edges. Both the PC and the NPC
algorithm now supports user decisions on the directionality of edges, which
cannot be directed using data alone. In the Hugin Graphical User Interface it is
now possible to learn arbitrarily complex structures, as tables for the
conditional probability distributions are not created as part of the structural
learning.
Various other aspects of the Hugin Graphical User Interface have been improved:
node tables, belief monitors, and operations on sets of nodes.
The node table has been greatly improved. For instance, expressions and manually
specified tables can now coexist, cut-and-paste functionality has been improved
(e.g., it is possible to cut and paste to/from Excel), tables can be exported to
text files, it is possible to work with bars instead of numbers and to have
numbers and bars simultaneously, the functionality for printing a table has been
improved, and other new functionalities have been added to the node table.
It is possible to specify different display mode for the belief monitors in
runmode. This facilitates viewing the changes in beliefs induced by a
propagation of evidence.
It is now possible to perform an increased number of operations on sets of nodes
(i.e., set type and set interface of sets of nodes simultaneously).
Finally, the Hugin Decision Engine has been extended with support for
object-oriented Bayesian networks and influence diagrams to make this
functionality accessible through our Application Programming Interfaces (APIs).
This implies that object-oriented Bayesian networks and influence diagrams are
now supported both by the Hugin Decision Engine and by the Hugin Graphical User
Interface.