Artificial Intelligence
RT804
Prof. Shoby B Mathew
Department of Information Technology
Caarmel Engineering College
Perunadu, Kerala
Teaching notes available at: http://www.shobymathew.com
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What is Artificial Intelligence?
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What is AI?
 A broad field that means different things to different people
 Defining “artificial” is easy but no broad consensus in
precise, concrete terms for “intelligence”:
 exclusive province of human being?
 natural phenomenon exhibited by living organisms?
 an arbitrarily specified set of abilities?
 other definitions??
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Artificial
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Artificial – usually has a negative
connotation (synthetic – i.e. man made)

e.g. artificial flower :
look …maybe
feel
no
smell
no
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Artificial
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artificial motion
planes
trains
automobiles
artificial light
electric light
candles
Kerosene lamp
natural motion
walking
horse

natural light
sunlight
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What is Intelligence?

Is there a “holistic” definition for intelligence?

We might list elements of intelligence:
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understanding, reasoning, problem solving, learning,
common sense, generalizing, inference, analogy,
recall, intuition, emotion, self-awareness
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What is Intelligence?
• Intelligence: “ability to learn, understand and think”
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(Oxford dictionary)
Intelligence might be defined broadly as facility at
solving problems
“Intelligence is the ability to learn, to deal with
different situations, to acquire, understand, and
apply knowledge and to analyze and reason.”
Varying kinds and degrees of intelligence occur in
people, many animals and some machines.
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What is Artificial Intelligence (AI)?
• A.I. is the study of how to make computers do things
at which, at the moment, people are better.
• It is the science and engineering of making
intelligent machines, especially intelligent computer
programs
• Artificial Intelligence is the science of making
machines do things that would require intelligence if
done by man.
• Artificial Intelligence is concerned with the design of
intelligence in an artificial device.
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What is AI ?...contd.
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The term was coined by John McCarthy in
1956.
There are two ideas in the definition.

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1. Intelligence
2. artificial device
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John McCarthy (Born 1927) in 2006
What is AI?
Thinking humanly
Thinking rationally
Acting humanly
Acting rationally
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AI Definitions
Definitions organized into four categories
The exciting new effort to
make computers think …
machines with minds, in the
full and literal sense.
The study of the
computations that make it
possible to perceive,
reason, and act. [Winston,
[Haugeland 85].
1992]
The study of how to make
computers do things at
which, at the moment,
people are better. [Rich &
The branch of computer
science that is concerned
with the automation of
intelligent behavior. [Luger
Knight, 1991]
and Stubblefield, 1993]
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Areas of Study
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Computer Science – algorithms, data representations,
programs to test theories
Psychology – theories of mind, memory, learning,
experiments with human and animal intelligence
Philosophy – mind/body problem, study of logic
Linguistics – study of language (syntax, semantics)
Neurology/Biology – study of the brain (both human
and animal), study of memory, learning
Engineering – many AI domains are in engineering
disciplines
Mathematics – many algorithms are mathematical in
nature (neural networks, statistical approaches)
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System with Intelligence

There are two possibilities:

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– A system with intelligence is expected to
behave as intelligently as a human
– A system with intelligence is expected to
behave in the best possible manner
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Turing Test

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Alan Turing's 1950 article Computing Machinery and
Intelligence discussed conditions for considering a
machine to be intelligent. He argued that if the
machine could successfully pretend to be human to a
knowledgeable observer then you certainly should
consider it intelligent.
He stated that a computer would deserves to be called
intelligent if it could deceive a human into believing
that it was human.
Considered as the basic test for intelligence
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Turing Test

Mathematician Alan
Turing devised a test for
defining artificial
intelligence:

an interrogator poses
questions to two entities, a
human and a computer

If the interrogator cannot
tell which is the human
and which is the
computer, then the
computer passes the
Turing Test and should
be considered intelligent

Turing Test – a test for
machine intelligence
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Turing Test
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Turing Test
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Eliza
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Person: Men are all alike.

Eliza: In what way?
Person: They’re always bugging us
about something or other.
Eliza: Can you think of a specific
example?
Person: Well, my boyfriend made me
come here.
Eliza: You’re boyfriend made you
come here?
Person: He says I’m depressed much
of the time.
Eliza: I am sorry to hear you are
depressed.
Person: It is true, I am unhappy.
Eliza: Do you think coming here will
help you not to be unhappy?
Person: I need some help, that much
seems certain.
Eliza: What would it mean to you if
you got some help?

Person: Perhaps I could learn to get
along with my mother.
Eliza: Tell me more about your family.
Eliza consists of a series of rules (if-then
statements)
 sample syntactic manipulations:
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<X> me <Y>  <X> you <Y>?
I like <Y>  Why do you like
<Y>?
<X> are like <Y>  In what
way?
<X> {mother | father | brother |
sister}  Tell me more about
your family
<X>  Can you think of a
specific example?
Eliza had no understanding of the text
input or its own responses
 try a non-sensical sentence, you will
get a non-sensical response!
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What can AI systems do?

Today’s AI systems have been able to achieve limited
success in some of these tasks.
 Face recognition (Computer vision )
 Vehicles that are mostly autonomous ( Robotics )
 Simple machine translation (Natural language
processing)
 Medical diagnosis in a narrow domain (Expert systems )
 Recognizing several thousand words continuous speech
(Speech Understanding )
 AI systems can play at the Grand Master level in chess
(Games)
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What can AI systems NOT do yet?
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Understand natural language robustly (e.g., read
and understand articles in a newspaper)
Surf the web
Interpret an arbitrary visual scene
Learn a natural language
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Applications of AI
• Computer beats human in a chess game.
• Computer-human conversation using speech
recognition.
• Expert system controls a spacecraft.
•
•
•
•
Robot can walk on stairs and hold a cup of water.
Language translation for webpages.
Home appliances use fuzzy logic
......
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Applications of AI
Search engines
Science
Medicine/
Diagnosis
Labor
Appliances
Games
What else?
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Some Task Domains of AI
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Mundane tasks
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Formal Tasks
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Perception (Vision, Speech)
Natural language (Understanding, Generation, Translation)
Commonsense reasoning
Robot control
Games (Chess, checkers)
Mathematics (Geometry, logic, integral calculus)
Expert tasks
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Engineering (design, fault finding, manufacturing planning)
Scientific analysis
Medical diagnosis
Financial analysis
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AI Problems
Mundane tasks correspond to the following AI problems areas:
 Planning : The ability to decide on a good sequence of
actions to achieve our goals
 Vision :
The ability to make sense of what we see
 Robotics:
The ability to move and act in the world, possibly
responding to new perceptions
 Natural Language:
The ability to communicate with others in
any human language
Mundane tasks are generally much harder to
automate
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To Build an Intelligent System
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Why? To solve a particular problem
We need to do four things
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Define the problem precisely
Analyze the problem
Isolate and represent the task knowledge that is
necessary to solve the problem
Choose the best problem-solving techniques and
apply it to the particular problem
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Problem Solving through AI
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Problem:
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It is the question which is to be solved
For solving a problem it needs to be precisely
defined
Problem definition means, defining the start goal,
goal state, other valid states and transitions
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Problem Solving through AI
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The method of solving problem through AI
involves the process of defining the search
space, deciding start and goal states and
then finding the path from start state to goal
state through search space
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Production rules
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The movement from start state to goal state
is guided by set of rules specifically designed
for that particular problem (sometimes called
production rules)
The production rules are nothing but valid
moves described by the problems
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Search Space & Search
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Search space: It is the complete set of
states including start and goal states, where
the answer of the problem is to be searched
Search: It is the process of finding the
solution in search space. The input to search
space algorithm is problem and output is
solution in form of action sequences
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Well defined problem
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A problem description has three major
components. Initial state, final state, space
including transition function or path function.
A path cost function assigns some numeric
value to each path that indicates the
goodness of that path.
Sometimes a problem may have additional
component in form of heuristic information
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Solution of the problem
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A solution of the problem is a path from initial
state to goal state. The movement from start
states to goal states is guided by transition
rules.
Among all the solutions, whichever solution
has least path cost is called optimal solution
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Method of solving problems
through AI techniques
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It involves the process of defining the search
space, deciding about start and goal state
and then finding a path from start state to
goal state through search space
The search techniques are methods which
are used to find a way from start to goal state
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Defining the problem as a
state space search
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Problem solving = Searching for a goal state
The state space representation forms the
basis of most of the AI problems
Search is a very important process in the
solution of hard problems for which no more
direct techniques are available.
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State Space Search
1.
Define a state space that contains all the
possible configurations of the relevant objects.
2. Specify the initial states.
3. Specify the goal states.
4. Specify a set of rules:
- What are unstated assumptions?
- How general should the rules be?
- How much knowledge for solutions should be in
the rules?
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Famous Problems for
Illustrating AI Concepts
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Water Jug Problem
Chess Problem
Tic-Tac-Toe
8-Puzzle Problem
8-Queens Problem
Tower of Hanoi Problem
Traveling Salesperson Problem
Magic Square
Monkey and Bananas problem
Missionaries and Cannibals problem
Cryptarithmetic
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State Space Search: Water Jug
Problem
“You are given two jugs, a 4-gallon (litre) one
and a 3-gallon (litre) one. Neither has any
measuring markers on it. There is a pump
(tap) that can be used to fill the jugs with
water. How can you get exactly 2 litres of
water into 4-litre jug.”
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State Space Search: Water Jug
Problem
• State: (x, y) i.e
Where X is gallons of water in 4 gallon jug
& y is gallons of water in 3 gallon jug
• x = 0, 1, 2, 3, or 4
• Start state: (0, 0).
y = 0, 1, 2, 3
• Goal state: (2, n) for any n.
• Attempting to end up in a goal state.
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Production rules for Water Jug
Problem
(x, y)
if x  4
 (4, y)
2. (x, y)
if y  3
 (x, 3)
3. (x, y)
if x  0
 (x - d, y)
4. (x, y)
if y  0
 (x, y - d)
1.
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Production rules for Water Jug
Problem
5. (x, y)
if x  0
 (0, y)
6. (x, y)
if y  0
 (x, 0)
7. (x, y)
 (4, y - (4 - x))
if x  y  4, y  0
8. (x, y)
 (x - (3 - y), 3)
if x  y  3, x  0
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Production rules for Water Jug
Problem
9. (x, y)
 (x  y, 0)
if x  y  4, y  0
10.(x, y)
 (0, x  y)
if x  y  3, x  0
11.(0, 2)
 (2, 0)
12.(2, y)
 (0, y)
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Production rules for Water Jug
Problem
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Production rules for Water Jug
Problem
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State Space Search: Water Jug
Problem
1.
Current state = (0, 0)
2. Loop until reaching the goal state (2, 0)
- Apply a rule whose left side matches the
current state
- Set the new current state to be the resulting
state
(0, 0)
(0, 3)
(3, 0)
(3, 3)
(4, 2)
(0, 2)
(2, 0)
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One Solution to the Water jug
Problem
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State Space Search: Water Jug
Problem
The role of the condition in the left side of a
rule
 restrict the application of the rule
 more efficient
1. (x, y)
if x  4
 (4, y)
2. (x, y)
if y  3
 (x, 3)
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State Space Search: Water Jug
Problem
Special-purpose rules to capture special-case
knowledge that can be used at some stage in
solving a problem
11.(0, 2)
 (2, 0)
12.(2, y)
 (0, y)
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Partial Search Tree of Water Jug
Problem
(0, 0)
(4, 0)
(4, 3)
(0, 0)
(0, 3)
(1, 3)
(4, 3)
(0, 0)
(3, 0)
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Formal Description of the
Problem: Summary
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Define a state space that contains all the possible
configurations of the relevant objects.
Specify one or more states within that space that
describe possible situations from which the
problem solving process may start (initial state)
Specify one or more states that would be
acceptable as solutions to the problem. (goal
states)
Specify a set of rules that describe the actions
(operations) available.
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Problem Solving: Chess
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Game playing
 Game playing is considered an intelligent human activity.
Games of perfect information are really just search problems
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Problem Solving: Chess
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Number of possible unique chess games is 10120.
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In 1957, artificial intelligence pioneers Herbert Simon and
Allen Newell predicted that a computer would beat a human
at chess within 10 years.
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BELLE, a chess program by Ken Thompson and Joe
Condon, became the first computer to be awarded the title of
US chess master, in 1983.
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BELLE didn’t try to do what a human would do. Instead,
BELLE took advantage of what computers do well.
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In May 1997, IBM's Deep Blue Supercomputer played a
fascinating match with the reigning World Chess Champion,
Garry Kasparov and won 3 ½ to 2 ½
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Defining chess problem as
State Space search
• State space is a set of legal positions.
• Starting at the initial state.
• Using the set of rules to move from one state to
another.
• Attempting to end up in a goal state.
• Define the problem of playing chess as a problem of
moving around in a state space, where each state
corresponds to a legal position of the board
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Defining chess problem as
State Space search
• Each position can be described by an 8-by-8 array.
• Initial position is the game opening position.
• Goal position is any position in which the opponent does
not have a legal move and his or her king is under
attack.
• Legal moves can be described by a set of rules:
- Left sides are matched against the current state.
- Right sides describe the new resulting state.
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Cryptarithmetic
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Consider an arithmetic problem represented by letters, as shown
below:
SEND
DONALD
+MORE
+GERALD
----------------------MONEY
ROBERT
Assign a decimal digit to each of the letters in such a way that
the answer to the problem is correct. If the same letter occurs
more than once, it must be assigned the same digit each time.
No two different letters may be assigned the same digit.
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Tic-Tac-Toe - Game Trees
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Tic-tac-toe
x
x
1 ply
x
x o
x
o x
o
x
x
o
o
x
1 move
o
x
o x
o
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Tic-Tac-Toe - Game Trees
x o x
ox
o
win
lose
x o x
x ox
o
x o x
x ox
o
o
x o x
x ox
o x o
x o x
ox
x
o
x o x x o x
x ox o ox
oo x
o
x o x
x ox
x oo
x o x
o ox
x xo
x o x
ox
x o
x o x
ox
x oo
x o x
o ox
x o
x o x
o ox
x x o
draw
x o x
ox
o x o
x o x
x ox
o x o
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