2. Expert Systems
“..An intelligent computer program that uses
knowledge and inference procedures to solve
problems that are difficult enough to require
significant human expertise for their solution..”
(Feigenbaum 1982)
3. Expert System
Basic concept of expert system :
User supplies facts or other information to the expert system
and receives expert advice or expertise in response.
Internally, the expert system consists of two main components :
the knowledge-base contains the knowledge
the inference engine draws conclusions from the knowledge
Knowledge-base
Inference Engine
User
Expertise
Expert System
Facts
4. Expert System
Functionality
• Assist human expert when integrating various decisions
• Replace human expert decision making when not available
Expert systems : programming computers to make decisions in
real-life situations (for example, some expert systems help doctors
diagnose diseases based on symptoms)
5. Applications of Expert Systems
Peachtree:
Used by accountant for
making Database,
Financial documents
6. Applications of Expert Systems
PROSPECTOR:
Used by geologists to
identify sites for
drilling or mining
PUFF:
Medical system
for diagnosis of
respiratory conditions
7. Components of an Expert System
• The knowledge base is the collection of facts
and rules which describe all the knowledge
about the problem domain
• The inference engine is the part of the
system that chooses which facts and rules to
apply when trying to solve the user’s query
• The user interface is the part of the system
which takes in the user’s query in a readable
form and passes it to the inference engine. It
then displays the results to the user.
8. Why use Expert Systems?
• Experts are not always
available. An expert system
can be used anywhere, any
time.
• Human experts are not
100% reliable or consistent
• Experts may not be good at
explaining decisions
• Cost effective
9. Problems with Expert Systems
• Limited domain
• Systems are not always
up to date, and don’t
learn
• No “common sense”
• Experts needed to setup
and maintain system
10. Limitations of Expert
Systems
• Limited to relatively narrow problems
• Cannot readily deal with “mixed”
knowledge
• Possibility of error
• Cannot refine own knowledge base
• Difficult to maintain
• May have high development costs
• Raise legal and ethical concerns
