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Expert systems 429
generally agreed and workable definition that it is the modeling, within
a computer, of expert knowledge in a given domain, such that the resulting
system can offer intelligent advice or take intelligent decisions. One important
addition to this definition is that the system should be able to justify the
logic and reasoning underlying its advice or decision making.
It follows that expert systems act as decision aids or decision-support
systems when operating by giving advice to a (non-expert) human decision
maker. Expert systems can also act as decision makers without any
human–computer dialogue or interaction. Finally, expert systems can
act as trainers by instructing human novices to become experts in a
particular area of expertise.
Three brief sketches will give the essence of these distinctions:
(1) A fisherman goes into a tackle shop. He wants to catch a certain type
of fish in the particular river conditions where he fishes. The expert
system questions him about the fish, river conditions and weather,
etc. and advises him to use a certain type of fly or bait.
(2) In a factory, the sensors within a machine indicate an imminent
component failure. The expert system decides to close the machine
down and alert a particular fitter to attend the problem. At the same
time, the expert system orders the required spare part from the store
room and dispatches it to the fitter.
(3) A school student works through mathematical problems with an
expert system. After the student has worked through a series
of problems the system diagnoses the underlying cause of the
observed errors, gives the student some extra problems to confirm
the diagnosis and then proceeds to give tuition in the required
mathematical skills.
What is expert knowledge?
The nature of human knowledge is an area of much debate and controversy.
However, it assumes a more concrete form in the practice of
knowledge engineering. For expert systems, this is the skill of obtaining
and manipulating human knowledge so that it can be built into a computer
model which in some ways behaves like an expert. Gaining the
knowledge from the expert, an initial focus of knowledge engineering, is
termed knowledge elicitation, and this is usually concerned with obtaining
knowledge from people rather than documents. In fact, the knowledge
of experts goes far beyond that contained in textbooks. For example,
Wilkins et al. 1 cite the case of medical expertise where, despite years of