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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)
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
WHY EXPERT SYSTEM?
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.
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
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.
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
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
DENDRAL(Dentritic Algorithm)
EXAMPLES OF EXPERT SYSTEM
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
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.
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.,
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
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
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
CHARACTERISTICS OF ARTIFICIAL INTELLIGENCE
 Problem solving
 Learning Ability
 Rational thinking
 Fast decision making
 Imitates human cognition
 Futuristic
APPLICATIONS OF ARTIFICIAL INTELLIGENCE
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
SUMMARY
Thank you

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Artificial Intelligence and Expert System

  • 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
  • 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
  • 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
  • 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