introudction to Artificial Intelligence History and foundation and definition

Artificial Intelligence introduction class

1. Intorduction to
Artificial Intelligence
Course: 7
th
Semester, B. Tech(CSE)
October 2025 - Jan 2026
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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2. 10/29/25
Artificial Intelligence
Textbook:
S. Russell and P. Norvig Artificial Intelligence: A Modern
Approach Prentice Hall, 2003, Second Edition
Artificial Intelligence, Elaine Rich, Kevin Knight,
Shivasankar B. Nair, McGrawHill publications,
Third Edition, 2013
Prof. Venkatesh, CSE, UVCE, Bengaluru
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3. 10/29/25
Course overview
Prof. Venkatesh, CSE, UVCE, Bengaluru
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4. Course overview
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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5. 10/29/25
Today’s class
What is Artificial Intelligence?
A brief History
Intelligent agents
State of the art
Prof. Venkatesh, CSE, UVCE, Bengaluru
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6. Intelligence
Homo sapiens: man the wise:
Perceive, understand, predict,
manipulate, reasoning, decision-
making, problem solving, memory,
response/action.
Intelligence : Cognitive processes
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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7. 10/29/25
What is AI?
Views of AI fall into four categories:
Thinking humanlyThinking
rationally
Acting humanlyActing rationally
The textbook advocates "acting rationally“
List of AI-topics

Prof. Venkatesh, CSE, UVCE, Bengaluru
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8. Thinking Humanly
Through introspection
Through psychological experiments
Through brain imaging
Build systems that mimic the way humans think
and solve problems
Thinking Rationally
Laws of thought were supposed to govern the
operation of the mind; their study initiated the
field called logic.
Modelling thinking as a logical process.
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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9. Acting Humanly
Creating a system that can exhibit
behavior indistinguishable from that of
a human
Turing Test: NLP, Knowledge,
representation, Automated reasoning,
Machine Learning
Act Rationally
A rational agent is one that acts so as
to achieve the best outcome
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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10. Thinking Humanly
“The exciting new effort to make computers
think ...machines with minds, in the full and
literal sense.” (Haugeland, 1985)
“[The automation of] activities that we associate
with human thinking, activities such as
decision-making, problem solving, learning ...”
(Bellman, 1978)
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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11. Thinking Rationally
“The study of mental faculties through
the use of computational models.”
(Charniak and McDermott, 1985)
 “The study of the computations that
make it possible to perceive, reason,
and act.” (Winston, 1992)
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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12. Acting Humanly
“The art of creating machines that perform
functions that require intelligence when
performed by people.” (Kurzweil, 1990)
“The study of how to make computers do
things at which, at the moment, people are
better.” (Rich and Knight, 1991)
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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13. Acting Rationally
“Computational Intelligence is the
study of the design of intelligent
agents.” (Poole et al., 1998)
“AI ...is concerned with intelligent be
havior in artifacts.” (Nilsson, 1998)
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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14. 10/29/25
What is Artificial Intelligence
(John McCarthy , Basic Questions)
What is artificial intelligence?
It is the science and engineering of making intelligent machines, especially
intelligent computer programs. It is related to the similar task of using
computers to understand human intelligence, but AI does not have to confine
itself to methods that are biologically observable.
Yes, but what is intelligence?
Intelligence is the computational part of the ability to achieve goals in the
world. Varying kinds and degrees of intelligence occur in people, many
animals and some machines.
Isn't there a solid definition of intelligence that doesn't depend on
relating it to human intelligence?
Not yet. The problem is that we cannot yet characterize in general what kinds
of computational procedures we want to call intelligent. We understand some
of the mechanisms of intelligence and not others.
More in: http://www-formal.stanford.edu/jmc/whatisai/node1.html
Prof. Venkatesh, CSE, UVCE, Bengaluru
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15. 10/29/25
What is Artificial
Intelligence?
Alfred Binet (1905): “Intelligence is the ability to judge
well, to understand well, and to reason well”.
AI: Technical and Scientific field devoted to design
“Engineered system” that generate output such as
content, perform prediction, recommendations or
helps in decision-making for given human-specified
objectives.
AI : It is science of creating machine that can perform
cognitive processes such as learn, reasoning, action,
control behavior like human.
AI: Simulation of human intelligence and human
intelligence processes by machine.
Prof. Venkatesh, CSE, UVCE, Bengaluru
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16. 10/29/25
What is Artificial
Intelligence
AI: Human Intelligence exhibited by Machines.
AI: Many be defied as branch of computer
science that is concerned with automation of
intelligence behavior.
AI: Technology that enables computer and
machine to simulate human learning,
comprehension, problem-solving, decision
making, creativity, autonomy.

The automation of activities that we associate
with human thinking, activities such as
decision-making, problem solving, learning…
(Bellman)
Prof. Venkatesh, CSE, UVCE, Bengaluru
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17. 10/29/25
The Turing Test
(Can Machine think? A. M. Turing, 1950)
Requires
Natural language
Knowledge representation
Automated reasoning
Machine learning
(vision, robotics) for full test
Prof. Venkatesh, CSE, UVCE, Bengaluru
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18. 10/29/25
What is AI?
Turing test (1950)
Requires:
Natural language
Knowledge representation
automated reasoning
machine learning
(vision, robotics.) for full test
Thinking humanly:
Introspection, the general problem solver (Newell and
Simon 1961)
Cognitive sciences
Thinking rationally:
Logic
Problems: how to represent and reason in a domain
Acting rationally:
Agents: Perceive and act
Prof. Venkatesh, CSE, UVCE, Bengaluru
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19. 10/29/25
Foundation to AI
The disciplines that contributed ideas, viewpoints, and
techniques to AI.
Philosophy,
Mathematics
Economics
Neuroscience
Psychology
Computer Engineering
Control theory and Cybernetics
Linguistics
Prof. Venkatesh, CSE, UVCE, Bengaluru
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20. 10/29/25
History of AI
McCulloch and Pitts (1943)
Neural networks that learn
The physiology and function of neurons in the brain,
propositional logic, Turing’s theory of computation.
Model of artificial neurons, characterised as being “on” or
“off,” with a switch to “on” occurring in response to
stimulation by a sufficient number of neighbouring neurons.
Minsky (1951)
Built a neural net computer: SNARC
Prof. Venkatesh, CSE, UVCE, Bengaluru
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21. History of AI, continued
Dartmouth conference (1956):
McCarthy, Minsky, Shannon, and Rochester,
automata theory, neural nets, and the study of
intelligence.
Every aspect of learning or any other feature of
intelligence can be precisely described that a
machine can be made to simulate it.
Newell, Simon: reasoning program: Logic theorist
(LT)- proves a theorem in Principia Mathematica :
Russell.
The name “Artificial Intelligence” was coined.
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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22. History of AI, continued
1952-1969
GPS- Newell and Simon, start to imitate human problem-
solving protocols, puzzles it could handle
Geometry theorem prover - Gelernter (1959), proves
theorems
Samuel Checkers that learns to play (1952)
McCarthy - Lisp (1958), Advice Taker, use knowledge to
search for solutions to problems.
Robinson’s discovery : theorem-proving algorithm
Microworlds: limited problems that appeared to require
intelligence to solve.
1962- the perceptron(Rosenblatt)
could be shown to learn anything they were capable of
representing.
10/29/25Prof. Venkatesh, CSE, UVCE, Bengaluru
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23. 10/29/25
The Birthplace of
“Artificial Intelligence”, 1956
Dartmouth workshop, 1956: historical meeting of the
precieved founders of AI met: John McCarthy, Marvin
Minsky, Alan Newell, and Herbert Simon.
A Proposal for the Dartmouth Summer Research Project on
Artificial Intelligence. J. McCarthy, M. L. Minsky, N.
Rochester, and C.E. Shannon. August 31, 1955. "We propose
that a 2 month, 10 man study of artificial intelligence be
carried out during the summer of 1956 at Dartmouth College
in Hanover, New Hampshire. The study is to proceed on the
basis of the conjecture that every aspect of learning or any
other feature of intelligence can in principle be so precisely
described that a machine can be made to simulate it." And this
marks the debut of the term "artificial intelligence.“
50 anniversery of Darmouth workshop
Prof. Venkatesh, CSE, UVCE, Bengaluru
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24. 10/29/25
History, continued
1966-1974 a dose of reality
Problems with computation
1969-1979 Knowledge-based systems
Weak (not handle different problem instances, domain-specific knowledge )
 vs. strong methods
Expert systems:
•Dendral: Inferring molecular structures from formula of the molecule (e.g.,
C6H13NO2) and the mass spectrum.
•Mycin: diagnosing blood infections
•Prospector: recommending exploratory drilling (Duda).
Roger Shank: no syntax only semantics
1980-1988: AI becomes an industry
R1: McDermott, 1982, helped configure orders for computer systems
1981: Fifth generation, human-interface research
1986-present: return to neural networks
Recent event:
AI becomes a science: HMMs, planning, belief network
Prof. Venkatesh, CSE, UVCE, Bengaluru
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25. 10/29/25
Abridged history of AI
1943 McCulloch & Pitts: Boolean circuit model of brain
1950 Turing's "Computing Machinery and Intelligence"
1956Dartmouth meeting: "Artificial Intelligence" adopted
1952—69 Look, Ma, no hands!
1950sEarly AI programs, including Samuel's checkers
program, Newell & Simon's Logic Theorist,
Gelernter's Geometry Engine
1965Robinson's complete algorithm for logical reasoning
1966—73 AI discovers computational complexity
Neural network research almost disappears
1969—79 Early development of knowledge-based systems
1980-- AI becomes an industry
1986-- Neural networks return to popularity
1987--AI becomes a science
1995--The emergence of intelligent agents
Prof. Venkatesh, CSE, UVCE, Bengaluru
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26. 10/29/25
State of the art
Deep Blue defeated the reigning world chess
champion Garry Kasparov in 1997
Proved a mathematical conjecture (Robbins
conjecture) unsolved for decades
No hands across America (driving autonomously 98%
of the time from Pittsburgh to San Diego)
During the 1991 Gulf War, US forces deployed an AI
logistics planning and scheduling program that
involved up to 50,000 vehicles, cargo, and people
NASA's on-board autonomous planning program
controlled the scheduling of operations for a spacecraft
Proverb solves crossword puzzles better than most
humans
DARPA grand challenge 2003-2005, Robocup
Prof. Venkatesh, CSE, UVCE, Bengaluru
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27. 10/29/25
Summary
What is Artificial Intelligence?
modeling humans thinking, acting, should think,
should act.
History of AI
Intelligent agents
We want to build agents that act rationally
Real-World Applications of AI
AI is alive and well in various “every day” applications
•many products, systems, have AI components
Prof. Venkatesh, CSE, UVCE, Bengaluru
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