2. What is an Expert System?
An expert system is
computer software that attempts
to act like a human expert on a
particular subject area.
Expert systems are often used
to advise non-experts in situations
where a human expert in
unavailable (for example it may
be too expensive to employ a
human expert, or it might be a
difficult to reach location).
3. How Do Expert Systems Work?
The non-expert user queries the expert system. This is done by asking a
question, or by answering questions asked by the expert system.
The inference engine uses the query to search the knowledge base and then
provides an answer or some advice to the user.
4. A rules base is a set of rules which an inference engine uses, together
with the data or facts in the knowledge base, to reason through a
A knowledge engineer must be employed in order to create an expert
system. The engineer collects information and knowledge from the expert.
The engineer also gathers data from other sources. This process is often
called data mining.
Tell the user what facts and rules
were used to find the solution
Decides which rule to go with
5. The inference engine is able to find solutions by using a form of reasoning. This
FORWARD CHAINING (data driven search)
BACKWARD CHAINING (goal driven search)
How do we choose between backward or forward inference?
Answer: Study how an expert solves a problem. If an expert needs to gather information
and then tries to infer, then forward inference is more likely to be suitable. If the expert
hypothesizes about solutions, then use backward inference.
Attribute Forward Chaining Backward Chaining
Also known as Data-driven Goal-driven
Starts from New data Possible conclusion
Processing Somewhat wasteful Efficient
Aims for Any Conclusion(s) Necessary data
Practical if Combinatorial explosion creates an
infinite number of possible right
Number of possible final answers is
reasonable or a set of known
alternatives is available.
Appropriate for Planning, monitoring, control and
Diagnostic, prescription and debugging