Foundation and Comparison of Expert system and Artificial Intelligence

1. D R . R . G U N A V A T H I ,
H E A D , P G A N D R E S E A R C H D E P A R T M E N T O F
C O M P U T E R A P P L I C A T I O N S ,
S R E E S A R A S W A T H I T H Y A G A R A J A C O L L E G E ,
P O L L A C H I
M O B I L E : 9 4 8 6 3 5 4 5 2 5
E - M A I L - H O D M C A @ S T C . A C . I N
Webinar on
Artificial Intelligence & Expert System
(13-06-2020)

2. Expert system Artificial Intelligence
 What are Expert Systems?
 Components
 Characteristics
 Examples
 Applications
 Advantages and Disadvantages
 What is Artificial intelligence?
 Components
 Characteristics
 Examples
 Applications
 Advantages and Disadvantages
AGENDA

3. WHY EXPERT SYSTEM?

4. WHAT IS EXPERT SYSTEM?
The computer applications
developed to solve
complex problems in a
particular domain, at the
level of extra-ordinary
human intelligence and
expertise.

5. COMPONENTS OF EXPERT SYSTEM
 Knowledge Base
 Quality, Completeness,
Accuracy of the information
stored in the knowledge base.
 Inference Engine
 Use of efficient procedures and
rules by the Inference Engine is
essential in deducting a correct,
flawless solution.
 User Interface
 It provides interaction between
user of the ES and the ES itself.
It is generally Natural Language
Processing

6. CHARACTERISTICS OF EXPERT SYSTEM
 High Performance
 It provides efficiency, accuracy and imaginative problem-solving.
 Adequate response time
 An Expert System interacts in a very reasonable period of time with the user
 Good reliability
 The expert system needs to be reliable, and it must not make any a mistake.
 Understandable
 The expert system should have an explanation capability similar to the
reasoning ability of human experts.
 Flexibility
 It is vital that it remains flexible as it the is possessed by an Expert system.

7. Human expert Expert system
 Expensive
 Difficult to Transfer
 Difficult to Document
 Unpredictable
 Perishable
 Cost effective System
 Transferable
 Easy to Document
 Consistent
 Permanent
HUMAN EXPERT VS. EXPERT SYSTEM

8. EXAMPLES OF EXPERT SYSTEM
 MYCIN: It was based on
backward chaining and
could identify various
bacteria that could cause
acute infections. It could
also recommend drugs
based on the patient's
weight.
Example:
 COVID 19
 Serious symptoms:
 difficulty breathing
 chest pain or pressure
 loss of speech or movement

9. DENDRAL(Dentritic Algorithm)
EXAMPLES OF EXPERT SYSTEM

10. CaDeT – Detect Cancer
EXAMPLES OF EXPERT SYSTEM
 The CaDet expert system is a
diagnostic support system that
can detect cancer at early
stages.
 Clinical data related to early
cancer detection and to cancer
risk factors was collected and
incorporated in database,
together with heuristic rules for
evaluating this data

11. PXDES
EXAMPLES OF EXPERT SYSTEM
 It is used to determine the type
and level of lung cancer.
 To determine the disease, it
takes a picture from the upper
body, which looks like the
shadow.
 This shadow identifies the type
and degree of harm.

12. APPLICATIONS OF EXPERT SYSTEM
 Medical domain
 Eg. Diagnosing of diseases
 Planning and scheduling
 Eg. Airline scheduling of flights
 Financial decision making
 Eg. Insurance, Share market
 Design and Manufacturing
 Eg. CAD, CAM
 Knowledge Domain
 Eg. Finding out faults in vehicles,
computers.
 Monitoring Systems
 Eg. Leakage monitoring in long
petroleum pipeline.
Others:
 Virus detection
 Employee performance analysis
 Helpdesk assistance, etc.,

13. Advantages Disadvantages
 Provide answers for decisions
 Hold huge amounts of information
 Minimize employee training costs
 Centralize the decision making process
 More efficient by reducing the time
needed to solve problems
 Combine various human expert
intelligences
 Reduce the number of human errors
 No common sense used in making
decisions
 Lack of creative responses that
human experts are capable of
 It is not easy to automate complex
processes
 There is no flexibility and ability to
adapt to changing environments
 Not able to recognize when there is
no answer
ADVANTAGES AND DISADVANTAGES OF
EXPERT SYSTEM

14. ARTIFICIAL INTELLIGENCE
 Simulation of human
intelligence in machines
that are programmed to
think like human
 Sometimes called
machine intelligence
 Makes it possible for
machines to learn from
experience

15. COMPONENTS OF ARTIFICIAL INTELLIGENCE
 Expert system
 Robotics
 intelligent machines that can help and
assist humans
 Vision Systems
 distinguish between objects and even
recognize objects.
 Natural Language Processing
 the interactions between computers and human
(natural) languages
 Learning system
 Machine learning
 Neural Networks
 Deep learning
 Genetic Algorithm
 Darwin's Theory
 Intelligent agents
 Sensors automatically collect information
from Internet

16. CHARACTERISTICS OF ARTIFICIAL INTELLIGENCE
 Problem solving
 Learning Ability
 Rational thinking
 Fast decision making
 Imitates human cognition
 Futuristic

17. APPLICATIONS OF ARTIFICIAL INTELLIGENCE

18. Advantages Disadvantages
 Reduction in Human Error
 Takes risks instead of Humans
 Available 24x7
 Digital Assistance
 Faster Decisions
 New innovations
 High Costs of Creation
 Making Humans Lazy
 Unemployment
 No Emotions
 Lacking Out of Box Thinking
ADVANTAGES AND DISADVANTAGES OF AI

19. SUMMARY

20. Thank you