Documentation

InstanceNodes are the key building block of object-oriented Bayesian networks and influence diagrams.

An InstanceNode represents an instance of a Class (i.e., a Bayesian network or an influence diagram). In other words, an instance node represents a subnetwork. The Class of which InstanceNodes exist in other Classes can itself contain InstanceNodes, whereby an object-oriented network can be viewed as a hierarchical description of a problem domain. Describing a network in a hierarchical fashion often makes the network much less cluttered, and thus provides a much better means of communicating ideas among knowledge engineers and users.

As systems often are composed of collections of identical or similar components, models of systems often contain repetitive patterns. The notion of InstanceNodes makes it very easy to construct multiple identical instances of a network fragment.

An InstanceNode is connected to other nodes via its <it>interface nodes</it>, which are the input Nodes and the output Nodes of the Class of which the InstanceNode is an instance. Chance nodes and decision nodes of the encapsulating Class (i.e., network) as well as output nodes of InstanceNodes of the encapsulating Class can be bound to input nodes of an InstanceNode.

As the output nodes of an InstanceNode can be parents of non-InstanceNodes, these output nodes are represented in the "home Class" of the InstanceNode as clones of the output nodes of the "instance Class" of the InstanceNode. Therefore, the output nodes of InstanceNodes are sometimes referred to as "output clones".

This class has no child classes.