ICS 101 Fall 2011 Introduction to Artificial Intelligence Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa.

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ICS 101 Fall 2011

Introduction to Artificial Intelligence

Asst. Prof. Lipyeow LimInformation & Computer Science Department

University of Hawaii at Manoa

10/11/2011 Lipyeow Lim -- University of Hawaii at Manoa

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What is Artificial Intelligence ?


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What is human intelligence ?


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What are signs (activities, abilities etc) of human

intelligence ?

Exercise 1: Write down four examples in your worksheet


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Approaches to A.I.


Human-oriented Rationalist

Thinking

Acting

Thinking Humanly Thinking Rationally

Acting Humanly Acting Rationally

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Definitions of AI (a)• “The exciting new effort to make computer think ... machines

with minds, in the full and literal sense.” (Haugeland, 1985)

• “[The automation of] activities that associate with human thinking, activities such as decision-making, problem solving, learning ...” (Bellman, 1978)

• “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 the moment, people are better.” (Rich and Knight, 1991)


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Definitions of AI (b)• “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)

• “Computational Intelligence is the study of the design of intelligent agents.”(Poole et al., 1998)

• “AI ... is concerned with intelligent behavior in artifacts.” (Nilsson, 1998)


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Acting Humanly: Turing Test (1950)

• Operational test of intelligence• Anticipated all major arguments against AI in following 50 years• Suggested major components of AI: knowledge, reasoning,

language understanding, learning


Human Interrogator

Human

A.I.

?

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Thinking Humanly : Cognitive Science

• AI thinks like humans do• How do humans think ?• How can we find out ?

– Introspection– Psychological experiments– Brain imaging

• The goal is to formulate computer programs that mimic how humans think and hence achieve AI!


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Thinking Rationally• Aristotle: what are correct arguments/thought

processes?– Syllogism:

• Socrates is a man;• All men are mortal• Therefore Socrates is mortal

– Field of logic• AI programs represent knowledge using

formal logic and solves problems using logical inference/reasoning.


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Acting Rationally

• Acting rationally == doing the right thing• What is the “right thing” ?

– Logical / rational– maximize goal achievement, given the available

information• This approach is the focus of many AI efforts!• AI programs are rational agents : programs

that act so as to achieve the best outcome or best expected outcome


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AI Today• Robotic Vehicles: Google Self-Drive Car• Speech Recognition: Call routing, Call center• Autonomous planning: Mars Rover• Game Playing: Deep Blue, Watson• Spam Fighting• Logistic Planning: Dynamic Analysis &

Replanning Tool (DART)• Robotics : Roomba• Machine Translation10/11/2011 Lipyeow Lim -- University of Hawaii at Manoa

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Intelligent Agents

• Perceives its environment through sensors• Acts upon the environment through actuators• Percepts – perceptual input at any given instant• Agent program implements how to map a sequence of

percepts to an action


Agent

EnvironmentAgent

Program

Sensors

Actuators Actions

Percepts

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Example: Vacuum Robot

• Vacuum Robot (“agent”) needs to keep two rooms A & B clean. It can sense which room it is in and whether the carpet in that room is dirty. It can either go Right, go Left, or Suck.


A B

************ ************

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Example: Vacuum Robot Agent Program

Percept Sequence Action

[A,Clean] Go Right

[A, Dirty] Suck

[B, Clean] Go Left

[B, Dirty] Suck

[A, Clean], [A, Clean] Go Right


Agent

EnvironmentAgent Program

Sensors

Actuators Actions

PerceptsA B

********* *********

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Representation & Search• Newell & Simon argue that intelligent activity (human

or machine) is achieved by:


– Representing significant aspects of a problem using symbol patterns

– Generating potential solutions by applying operations on the representation

– Selecting a solution by searching among these possibilities

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Example: Tic-Tac-Toe• 2 Player Game: Each gets a symbol 0 or X• Each player tries to get 3 of his/her symbol in a

row/column/diagonal in a 3 by 3 grid.


Player A

X

0

X

0 X

X

0 X

0 X

0 X

0 X

X

Player B Player A Player B

Player A

Player A Wins !

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Example: State Space for Tic-Tac-Toe


x x x

x...x x

0 x 0 x x

0

x

0...

x

0

x

0

... ... ......

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Exercise • Draw the state space for the vacuum robot

starting from the following initial state for the next two state transitions.


A B

************ ************

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Podcast Supplement

Asst. Prof. Lipyeow LimInformation & Computer Science Department

University of Hawaii at Manoa


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Approaches to A.I.


Human-oriented Rationalist

Thinking

Acting

Thinking Humanly Thinking Rationally

Acting Humanly Acting Rationally

22

Acting Humanly: Turing Test (1950)

• Operational test of intelligence• Anticipated all major arguments against AI in following 50 years• Suggested major components of AI: knowledge, reasoning,

language understanding, learning


Human Interrogator

Human

A.I.

?

23

Thinking Humanly : Cognitive Science

• AI thinks like humans do• How do humans think ?• How can we find out ?

– Introspection– Psychological experiments– Brain imaging

• The goal is to formulate computer programs that mimic how humans think and hence achieve AI!


24

Thinking Rationally• Aristotle: what are correct arguments/thought

processes?– Syllogism:

• Socrates is a man;• All men are mortal• Therefore Socrates is mortal

– Field of logic• AI programs represent knowledge using

formal logic and solves problems using logical inference/reasoning.


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Acting Rationally

• Acting rationally == doing the right thing• What is the “right thing” ?

– Logical / rational– maximize goal achievement, given the available

information• This approach is the focus of many AI efforts!


AI programs are rational agents : programs that act so as to achieve the best outcome or best expected outcome

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Intelligent Agents

• Perceives its environment through sensors• Acts upon the environment through actuators• Percepts – perceptual input at any given instant• Agent program implements how to map a sequence

of percepts to an action to achieve some goal


Agent

EnvironmentAgent

Program

Sensors

Actuators Actions

Percepts

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Example: Vacuum Robot (“Agent”)

• Goal/outcome: keep two rooms A & B clean. • Percepts: which room it is in and whether the

carpet in that room is dirty. • Actions: go Right, go Left, or Suck.


Agent


Sensors

Actuators Actions

PerceptsA B

********* *********

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Example: Vacuum Robot Agent Program

Percept Sequence Action

[A,Clean] Go Right

[A, Dirty] Suck

[B, Clean] Go Left

[B, Dirty] Suck

[A, Clean], [A, Clean] Go Right


Agent


Sensors

Actuators Actions

PerceptsA B

********* *********

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Example: Tic-Tac-Toe Agent

• Goal/outcome: Play by the rules and win• Percepts: the tic-tac-toe board and the

human’s move on the board.• Actions: put a “0” on any of the empty cell on

the board


Human Agent

0

X

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Example: Car Driving Agent

• Goal/outcome: Navigate and drive to destination safely obeying traffic rules

• Percepts: its own location, speed, direction, and location, speed, direction of nearby objects

• Actions: accelerate, decelerate, hardstop, turn x degrees left, turn x degrees right, maintain speed


Agent


Sensors

Actuators Actions

Percepts

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Representation & Search• Newell & Simon argue that intelligent activity

(human or machine) is achieved by:– Representing significant aspects of a problem

using symbol patterns– Generating potential solutions by applying

operations on the representation– Selecting a solution by searching among these

possibilities


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Example: Vacuum Robot

• State representation: – Cleanliness status of each room– Location of robot

• State Transitions (generating possibilities)– Triggered by actions of robot (L, R, S)

• Goal states (selecting solutions)– Any state where both rooms are clean


A B

***** *****Right

A B

*****

A B

*****Suck

A B

Suck

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Example: Vacuum Robot State Space


A B

***** *****

RA B

*****A B

*****

S

A B

SR

A B

**********

L

A B

*****

L

L

R

S

RA B

S

A B

*****

LL

S

R

R

L

L RS

S

L

R

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Example: Tic-Tac-Toe• State representation:

– Tic-tac-toe board– Location of X’s and 0’s

• State Transitions (generating possibilities)– Triggered by players putting

X/0 on empty cells• Goal states (selecting

solutions)– Any state where symbols form

a line10/11/2011 Lipyeow Lim -- University of Hawaii at Manoa

Player A

X

0

X

0 X

X

0 X

0 X

0 X

0 X

X

Player B Player A

Player B Player A

Player A Wins !

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Example: State Space for Tic-Tac-Toe


x x x

x...x x

0 x 0 x x

0

x

0...

x

0

x

0

... ... ......

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Summary• Four different approaches to AI

– Acting vs Thinking– Human-oriented vs Rationalist

• Intelligent Agents– Sensors– Actuators– Agent Program

• Representation and Search– Representing the state of the problem– Generating the state space– Searching the state space for goal states


ICS 101 Fall 2011 Introduction to Artificial Intelligence Asst. Prof. Lipyeow Lim Information & Computer Science Department University of Hawaii at Manoa.

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