Introduction to Artificial Intelligence (40-417)

Introduction to Artificial Intelligence

(40-417)

Course Pagehttp://sina.sharif.edu/~sani/courses/ai Announcements Slides Assignments

TextbooksMain  S Russell and P Norvig, Artificial

Intelligence: A Modern Approach, Prentice Hall, 3rd ed., 2010.

Auxiliary E Rich, k Knight, and S Nair, Artificial

Intelligence, McGraw-Hill, 3rd ed., 2009.

EvaluationQuizzes and Assignments (10%)

Prolog Assignments (20%)

Mid-Term Exam (35%)

Final Exam (35%)

What is Artificial What is Artificial Intelligence (AI)?Intelligence (AI)?

Views of AI fall into four categories in Two dimensions:

Thinking/Reasoning vs. behavior/action Success according to human standards vs. success

according to an ideal concept of intelligence (rationality):

The textbook advocates "acting rationally"

Act like humans Act rationallyThink like humans

Think rationally

Act RationallyRational behavior: doing the right thing“The right thing”: is expected to maximize goal achievement,

given the available information Limited resource, imperfect knowledgeDoesn't necessarily (but often) involve thinkingDoesn’t necessarily have anything to do with how humans solve the same problem.

Rational agentsAn agent is an entity that perceives and actsThe text book focuses on designing rational agents An agent is a function from percept histories to actions:

For any given class of environments and task, we seek the agent with the best performance.

Problem: computational limitations make perfect rationality unachievable.

f :P* A

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The Origins of AI

1950 Alan Turing’s paper, Computing Machinery and Intelligence, described what is now called “The Turing Test”.

Turing predicted that in about fifty years "an average interrogator will not have more than a 70 percent chance of making the right identification after five minutes of questioning".

1957 Newell and Simon predicted that "Within ten years a computer will be the world's chess champion."

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Turing test

Experimenter

AI system

Control

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Eliza, 1965 Patient: You are like my father in some ways. Doctor: What resemblance do you see? Patient : You are not very aggressive. Doctor : What makes you think I am not very aggressive? Patient : You don’t argue with me. Doctor : Why do you think I don’t argue with you? Patient : You are afraid of me. Doctor : Does it please you to believe I am afraid of you? Patient : My father is afraid of everybody. Doctor : What else comes to mind when you think of your father? Patient : Bullies.

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The Chinese Room

Set of rules, in English, for

transforming phrases

Chinese Writing is

given to the person

Correct Responses

She does not know

Chinese

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Newell and Simon Prediction

In 1997, Deep Blue beat Gary Kasparov.

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Why Did They Get it Wrong?

They failed to understand at least three key things:

•The need for knowledge (lots of it)

•Scalability and the problem of complexity and exponential growth

•The need to perceive the world

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Scalability

Solving hard problems requires search in a large space.

To play master-level chess requires searching about 8 ply deep. So about 358 nodes must be examined.

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Exponential Growth

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But Chess is Easy

•The rules are simple enough to fit on one page

•The branching factor is only 35.

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A Harder One

John saw a boy and a girl with a red wagon with one blue and one white wheel dragging on the ground under a tree with huge branches.

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How Bad is the Ambiguity?•Kim (1) •Kim and Sue (1) •Kim and Sue or Lee (2) •Kim and Sue or Lee and Ann (5) •Kim and Sue or Lee and Ann or Jon (14) •Kim and Sue or Lee and Ann or Jon and Joe (42) •Kim and Sue or Lee and Ann or Jon and Joe or Zak (132) •Kim and Sue or Lee and Ann or Jon and Joe or Zak and Mel (469) •Kim and Sue or Lee and Ann or Jon and Joe or Zak and Mel or Guy (1430) •Kim and Sue or Lee and Ann or Jon and Joe or Zak and Mel or Guy and Jan (4862)

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Computer as Artist

Two paintings done by Harold Cohen’s Aaron program:

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What is an AI Technique?

Example: Tic-Tac-Toe programcomplexityuse of generalizationsclarity of knowledgeextensibility 1 2 3

4 5 67 8 9

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Program 1Board: 9-element vector

0 : blank, 1 : X , 2 : O Move table: 39 Rows of 9-element vectorsAlgorithm:1. transform board vector from base 3 to 102. use (1) as the move table index

3. change the board by using the vector from (2)

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Comments:Advantages:efficient in terms of time,

optimal game of tic-tac-toe in theoryDisadvantages:

space - move table spacework - move tableerror prone - move table three dimension - 327, no longer work at all

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Program 2Board: program1

2 : blank, 3 : X, 5 : OTurn: game moves 1,2,3,.....odd-numbered move : xeven-numbered move : o

Algorithm : 3 sub procedures Make2: Board[5] or Board [2, 4, 6, or 8], Posswin (p): 18 (3*3*2) for p = X 50 (5*5*2) for p = OGo (n) : Move to Board [n]

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SterategyTurn=1 Go (1)Turn=2 Go (5) or Go (1)Turn=3 Go (9) or Go (3)Turn=4 Go(Posswin(X)) or Go(Make2)Turn=5 Go(Posswin(X)), or Go(Posswin(O)), or Go(7), or Go(3) [fork]…

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Comments:Less efficient than Program 1 (time)More efficient (space)More clarity (strategy)Easier to change (strategy)

Cannot extend to three dimension

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Program 2'program 2 boardmagic square 15 possible win check:S = sum of two paired owned by a playerD = 15 – Sif 0 < D < 10 and Board [D] is empty then the player can win

8 3 41 5 96 7 2

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Program 3 : minimaxOX

XO OX

X

O OX

X

O O XX

X

O OX

X X

O X OX

X

O X OX

X O

O OX

X X

O O OX

X X

O OX

X O X

O O OX

X X

O OX

X O X

O X OX

X O10 -1 10 0 0 0

-10 10 10 0

-10 0

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Commentsmuch more complex (time and space)ExtendableAI technique