What is expert system and its type,what is knowledge base

1. Expert System
composed by Adil

2. • AI computer program
• Designed to represent human expertise in a particular domain (area of expertise)
• According to Paul Harmon and David King, expert systems can help meet the following
needs:
1. New approaches to business organization and productivity
2. Expertise
3. Knowledge
4. Competencies
5. Smart automated equipment.
• ES act as intelligent assistants to human experts, as well as assisting people who
otherwise might not have access to expertise.
Expert System

3. What is Expert System continu….
• As both ES and database programs feature the retrieval of stored information but
differ greatly.
• A database program retrieves facts that are stored; while an ES uses reasoning to
draw conclusions form stored facts.
• The name ES was derived from the term knowledge-based expert systems.
• It can be also defined as , an “ES is a system that employs human knowledge
captured by computer to solve problems that ordinarily require human expertise.”
• Unlike traditional computer hardware and software that attempts to solve problems
using defined procedures, expert systems attempt to solve problems in specific
discipline using deductive reasoning.
• ES are capable to solve problems that are unstructured and poorly defined.
• Edward Feign Baum, a leading researcher in ES, defines ES as “ a computer
program that uses knowledge and inference procedures to solve problems that
are difficult enough to require significant human expertise for their solution.”

4. Comparison of Conventional Systems and Expert Systems
Conventional Systems Expert Systems
1. Information and its processing are
usually combined in one sequential
program
2. Programs must be error free
3. No explanations of decision making
4. System may be operated after
completion
5. Execution is make on a step-by-step
(algorithmic basis)
6. Need complete and exact information to
operate
7. Effective manipulation of large
databases
8. Representation and use of data
9. Easily deal with quantitative data
10. Capture, magnify and distribute access
to numeric data or to information
1. Knowledge base is clearly separated from the
processing inference mechanism (i.e. knowledge
rules separated from the control)
2. Mistake may exist
3. Explanation for why there in most ES.
4. May operate even if completed a part
(prototypes)
5. Uses heuristics and logic, and non algorithmic
execution
6. Can operate with incomplete or uncertain
information
7. Effective manipulation of large knowledge bases
8. Representation and use of knowledge
9. Easily deal with qualitative data
10. Capture, magnify, and distribute access to
judgment and knowledge

5. Famous Expert Systems
MYCIN
–By Edward Shortliffe of Standford University in the mid 1970s.
–Medical Expert system
–Diagnoses bacterial infections
–Recommends antibiotic therapy
DANDRAL
–Early days at same Standford University.
–Molecular structure Expert system
XCON and XSEL
–Cernegie Mellon University(CMU).
–Configuring large computer system Expert system
–DEC VAX 11/780 series
–Days and weeks would spent in assembling the DEC system, XCON does in minutes.
Prospector
–Expert system for Geologists for locating ore deposits.

6. Other Expert Systems
SOPHIE
–To help students to trouble shoot electronic circuits
–Simulated electronic circuit
DELTA
–To assist engineers in locating problems in diesel electric locomotive engines.
FOLIO
–To assists financial planners.
Weather forecasting
Aircraft Identification
Battlefield Management

7. Benefits
•Permits non expert to do the work of expert
•Improve productivity by improving efficiency
•Save time
•Simplified operations
•Automate repetitive, tedious and over complex processes
Some pitfalls
•Development of expert system is extremely difficult
•Expensive
•Not 100% reliable

8. How work
Knowledge base
Rules or frames or
semantic nets.
Knowledge base
Rules or frames or
semantic nets.
Working memory
System status, facts,
Initial and present state
Working memory
System status, facts,
Initial and present state
Inference Engine
Rule interpreter
Control strategy
Inference Engine
Rule interpreter
Control strategy
User interfaceUser interface
User

9. Major Components
Knowledge Base
•Heart of ES
•Consists of domain specific knowledge
•designer can choose frames, scripts, production rules
•Best method of representation is production rules
Inference Engine
•Rule interpreter
•Software that implements a search and pattern matching operation
•Function of the IE is hypothesis proving
User interface
•A piece of software that let the user communicate with the system
•Consists of menus, questions, statements.

10. Lamp Repair
This ES diagnosing a fault in a lamp and suggests possible causes and
remedies.
The rules in the knowledge base are listed below:
1. IF the lamp does not work
THEN check to see the power is on
2. IF the power is not on
THEN check for fuse
3. IF the power is not on
AND the fuse is good
THEN check for power failure
4. IF the power is not on
AND there is no fuse
THEN check for tripped circuit breaker
5. IF the power is not on
AND the circuit breaker is on
THEN check for a power failure
Example

11. 6. IF there is a power failure
THEN wait for power to come back on
7. IF the power is on
THEN check the bulb
8. IF the bulb is bad
THEN replace the bulb
9. IF the bulb is good
THEN check the switch
10. IF the switch is bad
THEN replace the switch
11. IF the bulb is good
AND the switch is good
THEN check the plug
12. IF the plug is bad
THEN fix or replace the plug
13. IF the bulb is good
AND the switch is good
AND the plug is good
THEN check the cord
14. IF the cord is bad
THEN fix or replace the cord
15. IF the bulb is good
AND the switch is good
AND the plug is good
AND the cord is good
THEN check the wall outlet
14. IF the wall outlet is bad
THEN fix or replace the outlet

12. Development tools
Languages
•LISP and Prolog, Visual Prolog
Shell
•Provides a basic framework in which data and knowledge can be
entered and manipulated in predefined way.
•A special software package
•ESTA