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1. Artificial Intelligence
What is Artificial Intelligence?

2. What is Intelligence?
• The ability of problem solving demonstrates
intelligence.
• The ability to think, plan and schedule
demonstrate intelligence.
• Memory and correct and efficient memory
and information manipulation also counts
towards ones intelligence.

3. What is Intelligence?
• The ability to tackle ambiguous and fuzzy
problems demonstrates intelligence.
• The ability to learn and recognize
demonstrates intelligence.
• The ability to understand and perceive
demonstrates intelligence.

4. Intelligent Machines
• A machine searches through a mesh and finds
a path.
• A machine solves problems like the next
number in the sequence.
• A machine develops plans.
• A machine diagnoses and prescribes.
• A machine answers ambiguous questions.

5. Intelligent Machines
• A machine recognizes fingerprints.
• A machine understands.
• A machine perceives.
• A machine does MANY MORE SUCH THINGS!
• A machine behaves as HUMANS do.

6. Intelligent Machines
• We will have to call such a machine
Intelligent. Is this real or natural
intelligence? NO! This is Artificial
Intelligence.

7. What is Artificial Intelligence?
• According to the father of Artificial
Intelligence, John McCarthy, it is “The science
and engineering of making intelligent
machines, especially intelligent computer
programs”.

8. Formal Definitions for Artificial
Intelligence
Systems that think like humans Systems that act like humans
“The exciting new effort to make
computers think … machines with minds,
in the full and literal sense
“The art of creating machines that
perform functions that require
intelligence when performed by people”
(Kurzweil 1990)
“[The automation of] activities that we
associate with human thinking, activities
such as decision making, problem
solving, learning …” (Bellman, 1978)
“The study of how to make computers do
things at which, at the moment, people
are better” (Rich and Knight, 1991)
“The study of mental faculties through
the use of computational models”
(Charniak and McDermott)
“A field of study that seeks to explain and
emulate intelligent behavior in terms of
computational processes” (Schalkoff,
1990)
“The study of computation that make it
possible to perceive reason and act”
(Winston 1992)
“The branch of computer science that is
concerned with the automation of
intelligent behavior” (Luger and
Stubblefield, 1993)

9. How Humans Think?
• Introspection: that is trying to catch out own
thoughts as they go by.
• Psychological Experiments: that concern with
the study of science of mental life.

10. To Put In Brief
• Artificial Intelligence is an effort to create
systems that can learn, think, perceive,
analyze and act in the same manner as real
humans.
• Strong AI: Machines act intelligently and they
have real conscious minds
• Weak AI: Machines can be made to act as if
they are intelligent.

11. Philosophy of AI
• A question by John McCarthy ‘’Can a machine
think and behave like humans do?”
• The development of AI started with the
intention of creating similar intelligence in
machines that we find and regard high in
humans.

12. Goals of AI
• To Create Expert Systems − The systems which
exhibit intelligent behavior, learn,
demonstrate, explain, and advice its users.
• To Implement Human Intelligence in
Machines − Creating systems that understand,
think, learn, and behave like humans.

13. What Contributes to AI?
• Artificial intelligence is a science and
technology based on disciplines such as
Computer Science, Biology, Psychology,
Linguistics, Mathematics, and Engineering. A
major thrust of AI is in the development of
computer functions associated with human
intelligence, such as reasoning, learning, and
problem solving.

14. What Contributes to AI?

15. Applications of AI
• Gaming
-In games where machine can think based on
large numbers
• Natural Language Processing
-where machines understand human natural
language spoken by humans
• Expert Systems
-Provide reasons and advices for users
• Vision Systems
• Speech Recognition
• Handwriting Recognition
• Intelligent Robots

16. Expert Systems
Who are human experts?
• They possess specialized knowledge in a
certain area
• They possess experience in the given area
• They can provide, upon elicitation, an
explanation of their decisions
• They have a skill set that enables them to
translate the specialized knowledge gained
through experience into solutions.

17. What is an expert system?
• A computer program designed to model the
problem solving ability of a human expert
• Expert Systems
• Knowledge
• Reasoning

18. History and Evolution
• There was a realization in the late 60’s that the
general framework of problem solving was not
enough to solve all kinds of problem.
• Specialized knowledge is very important of
practical systems.

19. Some Expert Systems
DENDRAL
• DENDRAL, an early expert system, developed
beginning in 1965 at Stanford University.
• A chemical-analysis expert system for NASA to
perform chemical analysis of Martian soil for
space missions.
• To determine molecular structure which was
based on “Test & Generate” method.

20. MYCIN
• MYCIN is the name of a decision support system
developed by Stanford
University in the early- to mid-seventies.
• Built to assist physicians in the
diagnosis of infectious diseases as particular blood
disease.
• The system (also known as an "expert system")
would ask a series of questions designed to emulate the
thinking of an expert in the field of infectious disease
(hence the "expert-"), and from the responses to
these questions give a list of possible diagnoses, with
probability, as well as recommend treatment (hence the
"decision support-").

21. Comparison of a human expert system
and an expert system

22. Roles of an expert system
• Replacement of expert: To replace human
expert to an expert system where it is feasible
in some situations. The solution would be
based on safety, location or cost.
• Assisting expert: An assisting expert system
would aid an expert in a task to increase
productivity, managing a complex situation.

23. How are expert systems used
• Control applications:
In control applications, ES are used to adaptiv
ely govern/regulate the behavior of a system.
• Design:
ES are used for design applications to
configure objects under given design
constraints.

24. How are expert systems used
• Diagnosis and Prescription:
ES can serve to identify system malfunction points.
• Instruction and Simulation:
ES can be used to model processes or systems for operational
study, or for use along with tutoring applications
• Interpretation:
Producing an understanding of situation
from given information.
• Planning and prediction:
ES may be used for planning applications, e.g. recommending
steps for a robot
to carry out certain steps, cash management planning.

25. How are expert systems used
• Appropriate domains for expert systems:
When analyzing a particular domain to see if
an expert system may be useful, ES ask:
1.Can the problem be effectively solved by conventio
nal programming?
2. Is the domain well-bounded?
3. What are the practical issues involved?

26. Expert system structure
• Focused area of expertise
• Specialized Knowledge (Long-
term Memory, LTM)
• Case facts (Short-term Memory, STM)
• Reasons with these to form new knowledge
• Solves the given problem

27. Expert system structure