Page 186 - DCAP506_ARTIFICIAL_INTELLIGENCE

Artificial Intelligence

Notes reasoning. Thus, when a conclusion is drawn, it is possible to understand how this conclusion
was reached. Furthermore, because the expert system uses knowledge in a form similar to the
expert, it may be easier to retrieve this information from the expert.

13.3.4 Procedure Node Interface

The function of the procedure node interface is to receive information from the procedures
coordinator and create the appropriate procedure call. The ability to call a procedure and receive
information from that procedure can be viewed as simply a generalization of input from the
external world. While in some earlier expert system external information has been obtained,
that information was obtained only in a predetermined manner so only certain information
could actually be acquired. This expert system, disclosed in the cross-referenced application,
through the knowledge base, is permitted to invoke any procedure allowed on its host system.
This makes the expert system useful in a much wider class of knowledge domains than if it had
no external access or only limited external access.
In the area of machine diagnostics using expert systems, particularly self-diagnostic applications,
it is not possible to conclude the current state of “health” of a machine without some information.
The best source of information is the machine itself, for it contains much detailed information
that could not reasonably be provided by the operator. The knowledge that is represented in the
system appears in the rulebase. In the rulebase described in the cross-referenced applications,
there are basically four different types of objects, with associated information present.

1. Classes: These are questions asked to the user.
2. Parameters: A parameter is a place holder for a character string which may be a variable
that can be inserted into a class question at the point in the question where the parameter
is positioned.
3. Procedures: These are definitions of calls to external procedures.
4. Rule Nodes: The inferencing in the system is done by a tree structure which indicates the
rules or logic which mimics human reasoning. The nodes of these trees are called rule
nodes. There are several different types of rule nodes.
The rulebase comprises a forest of many trees. The top node of the tree is called the goal node,
in that it contains the conclusion. Each tree in the forest has a different goal node. The leaves of
the tree are also referred to as rule nodes, or one of the types of rule nodes. A leaf may be an
evidence node, an external node, or a reference node.
An evidence node functions to obtain information from the operator by asking a specific question.
In responding to a question presented by an evidence node, the operator is generally instructed
to answer “yes” or “no” represented by numeric values 1 and 0 or provide a value of between
0 and 1, represented by a “maybe.” Questions which require a response from the operator other
than yes or no or a value between 0 and 1 are handled in a different manner. A leaf that is an
external node indicates that data will be used which was obtained from a procedure call.
A reference node functions to refer to another tree or subtree. A tree may also contain intermediate
or minor nodes between the goal node and the leaf node. An intermediate node can represent
logical operations like And or Or. The inference logic has two functions. It selects a tree to trace
and then it traces that tree. Once a tree has been selected, that tree is traced, depth-first, left to
right. The word “tracing” refers to the action the system takes as it traverses the tree, asking
classes (questions), calling procedures, and calculating confidences as it proceeds.
As explained in the cross-referenced applications, the selection of a tree depends on the ordering
of the trees. The original ordering of the trees is the order in which they appear in the rulebase.
This order can be changed, however, by assigning an evidence node an attribute “initial” which

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