The Prentice Hall Guide to Expert Systems

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Summary: Prentice Hall Guide to Expert Systems by Edmunds
Review: This is an excellent guide for formulating an expert system.
The work shows how systems learn. The process of learning
progresses from formal experience, inference drawing and
heuristics in order to combine knowledge/experience to form
judgments. An expert system contains a domain which is the
subject of automation. An expert or group of experts/opinion
is synthesized. The knowledge engineer functions as an
intermediary between the computer and the users. A semantic
network is a group of computerized representations of objects
connected by nodes and links representing relations between
common objects.

The inference engine matches patterns of words/phrases.
There is a process of forward/backward chaining. For instance,
the forward chain utilizes and optimizes the use of data
provided by users in order to consult the system in real time.