3. EXPERT SYSTEMS
Expert systems are designed to solve real
problems in a particular domain that normally
would require a human expert. It can solve many
types of problems
Developing an expert system involves extracting
relevant knowledge from human experts in the
area of problem, called domain experts.
4. Components of Expert System
Knowledge acquisition facility
Knowledge base
Knowledge-based management system
Inference engine,
Work space
Explanation facility
Reasoning capability and ,
User interface.
5. Characteristics of ES
Expert system is capable of handling challenging
decision problems and delivering solutions.
Expert system uses knowledge rather than data
for solution. Much of the knowledge is heuristicbased rather than algorithmic.
Expert system has the capability to explain how
the decision was made.
6. Characteristics contd…
Can…
Explain their reasoning or suggested decisions
Display intelligent behavior
Draw conclusions from complex relationships
Provide portable knowledge
Expert system shell
A collection of software packages and tools used to develop
expert systems
7. Limitations of Expert Systems
Not widely used or tested
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
8. Capabilities of Expert Systems
Strategic goal setting
Planning
Design
Decision making
Quality control and monitoring
Diagnosis
Explore impact of strategic goals
Impact of plans on resources
Integrate general design principles and
manufacturing limitations
Provide advise on decisions
Monitor quality and assist in finding solutions
Look for causes and suggest solutions
9. Components of Expert System
Fuzzy logic
A specialty research area in computer science that allows shades
of gray and does not require everything to be simply yes/no, or
true/false
Backward chaining
A method of reasoning that starts with conclusions and works
backward to the supporting facts
Forward chaining
A method of reasoning that starts with the facts and works
forward to the conclusions
11. Rules for a Credit Application
Mortgage application for a loan for Rs.100,000 to Rs.200,000
If there are no previous credits problems, and
If month net income is greater than 4x monthly loan payment, and
If down payment is 15% of total value of property, and
If net income of borrower is > Rs.25,000, and
If employment is > 3 years at same company
Then accept the applications
Else check other credit rules
12. Explanation Facility
A part of the expert system that allows a user or decision
maker to understand how the expert system arrived at certain
conclusions or results
13. Knowledge Acquisition Facility
Knowledge acquisition facility
Provides a convenient and efficient means of capturing and storing all
components of the knowledge base
Knowledge
base
Knowledge
acquisition
facility
Expert
14. Expert Systems Development
Determining requirements
Identifying experts
Domain
Construct expert system components • The area of knowledge
addressed by the
expert system.
Implementing results
Maintaining and reviewing system
15. Participants in Expert Systems
Development and Use
Domain expert
The individual or group whose expertise and knowledge is
captured for use in an expert system
Knowledge user
The individual or group who uses and benefits from the expert
system
Knowledge engineer
Someone trained or experienced in the design, development,
implementation, and maintenance of an expert system
17. Evolution of Expert Systems
Software
Expert system shell
Collection of software packages & tools to design, develop,
implement, and maintain expert systems
Ease of use
high
low
Traditional
programming
languages
Before 1980
Special and 4th
generation
languages
1980s
Expert system
shells
1990s
18. Limitations of Expert Systems
Not widely used or tested
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
19. When to Develop an ES?
The problem cannot be specified in terms of a
well-defined algorithm.
The problem requires consistency and
standardization.
The domain or problem area is narrow or
limited.
When the task is hazardous.
There is scarcity of experts in the area.
The problem involves complex logic or a large
number of rules.
Human experts have successfully solved similar
problems
20. Advantages of ES
It enhances decision quality.
It reduces the cost of consulting experts for
problem solving.
It provides quick and efficient solutions to
problems in narrow area of specialization.
It offers high reliability of expert suggestions or
decisions.
It gathers scarce expertise and uses it efficiently.
21. Advantages of ES contd…
It can tackle very complex problems that are
difficult for human experts to solve.
It can work on standard computer hardware.
It can not only give solutions, but also the
decision logic and how the solution was arrived
at.
22. Limitations of ES
The knowledge base may not be complete
Each problem is different. Hence the solution from a human
expert too may be different
Expensive to build and maintain
Takes long time to develop and fine tune ES
Large ES is difficult to build and maintain
