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Expert systems 431
that knowledge elicitation for expert system development shares many
characteristics of knowledge elicitation for decision analysis, discussed
in Chapter 6.
How is expert knowledge represented in expert systems?
Having completed the difficult process of elicitation, the knowledge
must be represented in a form that can be implemented in a computer
language. This is most commonly achieved in the form of production
rules. For example:
IF a car is a VW beetle THEN the car has no water-cooling system.
More formally:
IF (condition in database) THEN (action to update the database)
Production rules can have multiple conditions and multiple actions.
The action of a production rule may be required to ask a question of
the user of the system or interact with a physical device in addition to
updating the database. Production rule-based expert systems often use
many hundreds of rules and so control of their action becomes a serious
problem for the knowledge engineer.
The control structure determines what rule is to be tried next. The
control structure is often called the rule interpreter or inference engine.
In response to information gained from the user in interaction with the
expert system, the inference engine selects and tests individual rules in
the rule base in its search for an appropriate decision or advice. It usually
does this by forward chaining, which means following pathways through
from known facts to resulting conclusions. Backward chaining involves
choosing hypothetical conclusions and testing to see if the necessary
rules underlying the conclusions hold true. As an added complication,
we note that the rules elicited from experts often contain a degree of
uncertainty. For example:
IF a car won’t start THEN the cause is likely to be a flat battery but it could be
lack of fuel and might be ...
Most expert systems that can tolerate uncertainty employ some kind of
probability – like a measure to weigh and balance conflicting evidence.
It is important to recognize the significance of the user–system interface
in systems design. Expert systems are often used by non-experts, many