1. Introduction Characteristics Advantages Limitations
EXPERT SYSTEMS
Introduction
Characteristics
Advantages
Limitations
MS 204/U1/L7/Ashima

2. Artificial intelligence
Vision systems
Learning systems
Robotics
Expert systems
Neural networks
Natural language processing
MS 204/U1/L7/Ashima

3. Artificial Intelligence
Duplication of human thought process by
machine
– Learning from experience
– Rapid response to varying situations
– Applying reasoning to problem-solving
– Manipulating environment by applying knowledge
– Thinking and reasoning

4. Artificial Intelligence Concepts
Expert systems
– Human knowledge stored on machine for use in problem solving
• Natural language processing
– Allows user to use native language instead of English
• Speech recognition
– Computer understanding spoken language
• Sensory systems
– Vision, tactile, and signal processing systems
• Robotics
– Sensory systems combine with programmable
electromechanical device to perform manual labor

5. Experts Experts – Have special knowledge, judgment, and experience
– Can apply these to solve problems
• Higher performance level than average person
• Faster solutions
• Recognize patterns
• Acquired from reading, training, practice

6. Expert Systems Features
Expertise
– Capable of making expert level decisions
• Symbolic reasoning
– Knowledge represented symbolically
– Reasoning mechanism symbolic
• Self-knowledge
– Able to examine own reasoning
– Explain why conclusion reached
– Knowledge base contains complex knowledge

7. Example of Expert Systems
DENDRAL
– Applied knowledge or rule-based reasoning commands
– Deduced likely molecular structure of compounds
MYCIN
– Rule-based system for diagnosing bacterial infections
XCON
– Rule-based system to determine optimal systems configuration
Credit analysis
– Ruled-based systems for commercial lenders
Pension fund adviser
– Knowledge-based system analyzing impact of regulation and
conformance requirements on fund status

8. Applications
Finance
– Insurance evaluation, credit analysis, tax planning, financial planning
and reporting, performance evaluation
• Data processing
– Systems planning, equipment maintenance, vendor evaluation,
network management
• Marketing
– Customer-relationship management, market analysis, product
planning
• Human resources
– HR planning, performance evaluation, scheduling, pension
management, legal advising
• Manufacturing
– Production planning, quality management, product design, plant site
selection, equipment maintenance and repair

9. 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.
MS 204/U1/L7/Ashima

10. Evolution of Expert Systems Software
Expert system shell
Collection of software packages & tools to design, develop, implement, and maintain expert systems
high
Expert system shells
Special and 4th generation languages
Ease of use
Traditional programming languages
low
Before s s
MS 204/U1/L7/Ashima

11. 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 heuristic- based rather than algorithmic.
Expert system has the capability to explain how the decision was made.
MS 204/U1/L7/Ashima

12. Problem Domain vs. Knowledge Domain
An expert’s knowledge is specific to one problem domain – medicine, finance, science, engineering, etc.
The expert’s knowledge about solving specific problems is called the knowledge domain.
The problem domain is always a superset of the knowledge domain.
MS 204/U1/L7/Ashima

13. Problem and Knowledge Domain Relationship
MS 204/U1/L7/Ashima

14. Representing the Knowledge
The knowledge of an expert system can be represented in a number of ways, including IF- THEN rules:
IF you are hungry THEN eat
MS 204/U1/L7/Ashima

15. 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
MS 204/U1/L7/Ashima

16. 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.
MS 204/U1/L7/Ashima

17. 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.
MS 204/U1/L7/Ashima

18. 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
MS 204/U1/L7/Ashima

19. THANK You !!!
Queries ?
MS 204/U1/L7/Ashima