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Semester II (2010-11)
Introduction: Chapter 1
IS- 341
 Homepage:
http://sites.google.com/site/pnuis341/
 Visit the web page for schedule, lecture notes,
tutorials, assignment, grading, office hours, etc.
 Textbook:
S. Russell and P. Norvig Artificial
Intelligence: A Modern Approach Prentice Hall,
2003, Second Edition
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Outline
 Course overview
 What is AI?
 A brief history
 What AI can do today ?
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Intelligence?
 What do you believe what intelligence is?
Is
it intelligent to think like a human?
Is it intelligent to act like a human?
Is “human” equivalent to “intelligent”?
Intelligence = Knowledge + feel, understand, process,
communicate, judge, and learn
Characteristics of Intelligence
‰
Ability to Communicate
‰
Internal Knowledge
‰
Ability to Learn
‰
Self Awareness
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Artificial Intelligence Tasks
 Problem Solving

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Find a solution to a given problem
Find the shortest route from KFUPM to PNU
Assign pilots to flights so that costs are minimized
Devise a plan to get an A+ in IS 341
 Reasoning



Express your knowledge and derive hypotheses
Proof mathematical theorems
Make “justifiable” decisions in uncertain environments
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Artificial Intelligence Tasks
 Learning
 Adjust an internal representation so that it is in
accordance with observations made
 Revise Newton’s idea of space and time after
observing that light travels at a constant speed
 Interaction
 Communicate

Understand spoken language
 Perceive
 Look at a photo an identify Trinity
 Act
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AI in Action !!
Applications of AI
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Acting humanly: Turing Test
 Turing (1950) "Computing machinery and intelligence":
 "Can machines think?"  "Can machines
behave
intelligently?"
 Operational test for intelligent behavior: the Imitation Game
 Predicted that by 2000, a machine might have a 30% chance
of fooling a lay person for 5 minutes
 Anticipated all major arguments against AI in following 50
years
 Suggested major components of AI: knowledge, reasoning,
language understanding, learning
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AI prehistory
 Philosophy
Logic, methods of reasoning, mind as physical
system
foundations
of
learning,
language,
rationality
 Mathematics
Formal
representation
and
proof
algorithms,
computation,
(un)decidability,
(in)tractability,
probability
 Economics
utility, decision theory
Psychology
phenomena of perception
experimental techniques
 Computer
building
and
motor
fast
control,
computers
engineering
 Control theory
design systems
function over time
that
maximize
an
objective
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Abridged history of AI
 1943
 1950
 1956
 1952—69
 1950s
 1965
 1966—73





1969—79
1980-1986-1987-1995--
McCulloch & Pitts: Boolean circuit model of brain
Turing's "Computing Machinery and Intelligence"
Dartmouth meeting: "Artificial Intelligence"
adopted
Look, Ma, no hands!
Early AI programs, including Samuel's checkers
program, Newell & Simon's Logic Theorist,
Gelernter's Geometry Engine
Robinson's complete algorithm for logical
reasoning
AI
discovers
computational
complexity
Neural network research almost disappears
Early development of knowledge-based systems
AI becomes an industry
Neural networks return to popularity
AI becomes a science
The emergence of intelligent agents
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What AI Systems can do today?
 Planning:
 DARPA's DART system used in Desert Storm and
Desert Shield operations to plan logistics of people
and supplies.
 European space agency planning and scheduling of
spacecraft assembly, integration and verification.
 Speech Recognition:
 Computer Vision:
 Face
recognition programs
government, etc.
 Handwriting recognition.
in
use
by
banks,
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What AI Systems can do today?
 Game Playing:


Computer programs beat world’s best players
in chess e.g Deep Blue by IBM
Playing “Jeopardy” – question answering
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