This Presentation discusses about the following topics: Introduction to Intelligent Systems Expert Systems Neural Networks Fuzzy Logic Intelligent Agents

1. Department of Information Technology 1Soft Computing (ITC4256 )
Dr. C.V. Suresh Babu
Professor
Department of IT
Hindustan Institute of Science & Technology
Fuzzy Expert Systems

2. Department of Information Technology 2Soft Computing (ITC4256 )
Action Plan
• Introduction to Intelligent Systems
• Expert Systems
• Neural Networks
• Fuzzy Logic
• Intelligent Agents
• Quiz at the end of session`

3. Department of Information Technology 3Soft Computing (ITC4256 )
Objectives
• Explain the potential value and the potential limitations of
artificial intelligence.
• Provide examples of the benefits, applications, and limitations
of expert systems.
• Provide examples of the use of neural networks.
• Provide examples of the use of fuzzy logic.
• Describe the use case for several major types of intelligent
agents.

4. Department of Information Technology 4Soft Computing (ITC4256 )
Introduction to Intelligent Agents
• Artificial Intelligence (AI)
– Behavior by a machine that, if performed by a human being,
would be considered intelligent.
• Artificial Intelligence versus Natural (Human) Intelligence

5. Department of Information Technology 5Soft Computing (ITC4256 )
Four Activities Involved in the Transfer of Expertise
Expert  Computer  User
1. Knowledge Acquisition
2. Knowledge Representation
3. Knowledge Inferencing
4. Knowledge Transfer
Expert Systems

6. Department of Information Technology 6Soft Computing (ITC4256 )
The Components of Expert Systems
• Knowledge Base
– Facts
– Rules
• Inference Engine

7. Department of Information Technology 7Soft Computing (ITC4256 )
Applications, Benefits, and Limitations of
Expert Systems
• Expert Systems Are Especially Useful in the Following Categories
– Interpretation
– Prediction
– Diagnosis
– Design
– Planning
– Monitoring
– Debugging
– Repair
– Instruction
– Control

8. Department of Information Technology 8Soft Computing (ITC4256 )
Applications, Benefits, and Limitations of
Expert Systems
• Benefits of Expert Systems
– Increased Output and Productivity
– Increased Quality
– Capture and Dissemination of Scarce Resources
– Accessibility to Knowledge and Help Desks
– Reliability
– Ability to Work with Incomplete or Uncertain Information
– Provision of Training
– Enhancement of Decision-making and Problem-solving Capabilities
– Decreased Decision-Making Time
– Reduced Downtime
• Difficulties of Using Expert Systems
– Transferring domain expertise from human experts to the expert system can be difficult because people cannot always explain
what they know
– Even if the doman experts can explain their entire reasoning process, automating that process may not be possible
– In some contexts, there is a potential liability from the use of expert systems.

9. Department of Information Technology 9Soft Computing (ITC4256 )
Applications, Benefits, and Limitations of
Expert Systems
• Benefits of Expert Systems
– Increased Output and Productivity
– Increased Quality
– Capture and Dissemination of Scarce Resources
– Accessibility to Knowledge and Help Desks
– Reliability
– Ability to Work with Incomplete or Uncertain Information
– Provision of Training
– Enhancement of Decision-making and Problem-solving Capabilities
– Decreased Decision-Making Time
– Reduced Downtime

10. Department of Information Technology 10Soft Computing (ITC4256 )
Applications, Benefits, and Limitations of
Expert Systems
• Difficulties of Using Expert Systems
– Transferring domain expertise from human experts to the expert
system can be difficult because people cannot always explain what
they know
– Even if the domain experts can explain their entire reasoning process,
automating that process may not be possible
– In some contexts, there is a potential liability from the use of expert
systems.

11. Department of Information Technology 11Soft Computing (ITC4256 )
What is Uncertainty?
• Uncertainty is essentially lack of information to
formulate a decision.
• Uncertainty may result in making poor or bad
decisions.
• As living creatures, we are accustomed to dealing
with uncertainty – that’s how we survive.
• Dealing with uncertainty requires reasoning
under uncertainty along with possessing a lot of
common sense.

12. Department of Information Technology 12Soft Computing (ITC4256 )
How to Expert Systems Deal with Uncertainty?
• Expert systems provide an advantage when dealing with
uncertainty as compared to decision trees.
• With decision trees, all the facts must be known to arrive at an
outcome.
• Probability theory is devoted to dealing with theories of
uncertainty.
• There are many theories of probability – each with advantages and
disadvantages.

13. Department of Information Technology 13Soft Computing (ITC4256 )
Theories to Deal with Uncertainty
• Bayesian Probability
• Hartley Theory
• Shannon Theory
• Dempster-Shafer Theory
• Markov Models
• Zadeh’s Fuzzy Theory

14. Department of Information Technology 14Soft Computing (ITC4256 )
Dealing with Uncertainty
• Deductive reasoning – deals with exact facts and exact conclusions
• Inductive reasoning – not as strong as deductive – premises support
the conclusion but do not guarantee it.
• There are a number of methods to pick the best solution in light of
uncertainty.
• When dealing with uncertainty, we may have to settle for just a good
solution.

15. Department of Information Technology 15Soft Computing (ITC4256 )
Neural Networks
• A system of programs and data structures that simulates the
underlying functions of the biological brain
– Examples of the Use of Neural Networks
• Bruce Nuclear Facility (Ontario, Canada)
• Research into Diseases (Alzheimer’s, Parkinson’s, Epilepsy, etc.)
• Banking System Fraud Detection

16. Department of Information Technology 16Soft Computing (ITC4256 )
Fuzzy Logic
• A branch of mathematics that deals with uncertainties by
simulating the processes of human reasoning.

17. Department of Information Technology 17Soft Computing (ITC4256 )
Intelligent Agents
• A software program that assists, you, or acts on your behalf,
in performing repetitive computer-related tasks.
• Information Agents
• Monitoring-and-Surveillance Agents
• User Agents (or Personal Agents)

18. Department of Information Technology 18Soft Computing (ITC4256 )
Test Yourself
1. The first widely-used commercial form of Artificial Intelligence (Al) is being used in many popular products like microwave ovens, automobiles and plug in
circuit boards for desktop PCs. It allows machines to handle vague information with a deftness that mimics human intuition. What is the name of this
Artificial Intelligence?
a) Boolean logic
b) Human logic
c) Fuzzy logic
d) Functional logic
2. _____ are knowledge based system to which present rules are applied to solve a particular problem.
a. ES
b. AI
c. KBS
d. Base rule 0
3. Which of the following is not true about expert systems?
a. Expert systems are collections of human knowledge
b. Export systems are expensive to design.
c. export systems are usually designed to run on small general-purpose computers
d. Maintenance support may be difficult to obtain for an expert system.
4. Which of the following is a component of an expert system?
a. explanation module
b. knowledge base
c. natural language interface for the user
d. All of the above
5. The components of an expert system include a .......... that perform interfaces on the knowledge base and communicate answers to a user's questions?
a. Database and software module
b. Knowledge base and software module
c. communication base and software module
d. Knowledge base and interactive module

19. Department of Information Technology 19Soft Computing (ITC4256 )
Answers
1. The first widely-used commercial form of Artificial Intelligence (Al) is being used in many popular products like microwave ovens, automobiles and plug in
circuit boards for desktop PCs. It allows machines to handle vague information with a deftness that mimics human intuition. What is the name of this
Artificial Intelligence?
a) Boolean logic
b) Human logic
c) Fuzzy logic
d) Functional logic
2. _____ are knowledge based system to which present rules are applied to solve a particular problem.
a. ES
b. AI
c. KBS
d. Base rule 0
3. Which of the following is not true about expert systems?
a. Expert systems are collections of human knowledge
b. Export systems are expensive to design.
c. export systems are usually designed to run on small general-purpose computers
d. Maintenance support may be difficult to obtain for an expert system.
4. Which of the following is a component of an expert system?
a. explanation module
b. knowledge base
c. natural language interface for the user
d. All of the above
5. The components of an expert system include a .......... that perform interfaces on the knowledge base and communicate answers to a user's questions?
a. Database and software module
b. Knowledge base and software module
c. communication base and software module
d. Knowledge base and interactive module