“So you think you

are the only one

who has to follow

laws ?”

Page 8

Special Issue

Artificial Intelligence

TIME

May 3, 2010Newsletter Date

Through-

out the

Years: AI

By Lea Balcerzak

Letters to the edi-tor.

Page 10

Deep Blue Champion

Page 8

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In This Issue...

Page 3

Table of

Contents:

explains where

everything is

Main

Article:

talks

about the 3 main AI

approaches

3

4

8

9

10

11

Deep Blue

Champion:

the AI program that

beat the world

champion in chess

Three

Rules of

Robotics: the

rules all robot have to

follow

Turing

Test: the machine

test for intelligence

Letters to

the

Editor:

Question

from our readers

Artificial

Intelligence

Fun

8

T he scientific understand-

ing of the mechanism,

underlying thought, in-

telligent behavior, em-

bodiment in machines,” AI

(artificial intelligence) is the abil-

ity for a computer system to proc-

ess information in a manner similar

to human thought or to exhibit hu-

man-like behavior. AI is a devel-

oping program which involves cre-

ating a computer program, which

could be used in a robot so that it

could operate by itself with an in-

telligence equal to a human one.

It is taken that the field of

AI has its beginning with the publi-

cation of the British mathemati-

cian, Alan Turning’s paper

“Computer Machinery and Intelli-

gence.” (1950)

Main Approaches

“Knowledge representation

and reasoning are two core chal-

lenges in AI. They can be handled

in various ways:” (Litman)

Logical Approach

- Knowledge represented by

precise logical rules.

Probabilistic Approach

- Knowledge represented using

numerical probabilities.

Neural Network

-Knowledge represented as a

network of interconnected units that

perform certain task by exchanging

information.

-Mimics the behavior of neu-

rons (nerve cells) in the brain.

The three most important types of AI

are:

1. Symbolic AI

2. Functional AI

3. Relational AI

Page 4

Throughout the Years: AI

Symbolic AI

Success?

“The earliest approach to AI is

called symbolic or classical AI and is

predicated on the hypothesis that every

process in which a human being or a

machine engages, can be expressed by

a string of symbols that is modifiable

according to a limited set of rules that

can be logically defined.” (Harzfeld)

Just as complex geometry is

based on axiom and primitive objects

such as lines and points, symbolists

(scientists working with symbolic AI)

predict that human thought can be bro-

ken down into basic rules and primi-

tive objects. Symbolists believe that a

simple idea can be directly expressed

by a single symbol, while a more com-

plex idea would be presented with

more than one object, combined with

certain rules. Step by step, rule by rule,

scientists hope to construct a working

AI program.

Symbolic AI came to great success in

areas where task could be described in

simple rules. For example, a symbolic

AI program, Deep Blue, beat the

world champion in chess, (read more

on page 8). Other successes of sym-

bolic AI including: medical diagnosis,

mineral prospecting, chemical analy-

sis, and mathematical theorem prov-

ing. Symbolic AI failed, however, not

in complex tasks such as passing a

calculus exam, but in tasks a two-year

old could perform, such as recogniz-

ing a face or understanding a simple

story

Critique

Symbolic AI also came to be a

figure of great critique. Why? This pro-

gram achieved many things, and brought

researchers so much further in technol-

ogy, still some are not happy with it!

Terry Winograd and Fernando Flores, in

their 1986 book, Understanding Com-

puters and Cognition provided a critique

for symbolic AI, stating that human in-

telligence cannot be laid out by symbols

Page 5

or rules. Humans do not carry mental

models around in their heads,” they

state. Rather, these men suggest that

humans use intuition, gained through

multiple experiences in the real

world.

Can It Exist?

Scientist now ponder if sym-

bolic AI was such a great idea...

“Should it exist, it is now clear to AI

researchers that the set of primitive

facts, necessary for representing hu-

man knowledge is exceedingly

large.” (Harzfeld) What about intui-

tion? It can’t be learned, but can a

successful AI work without it? So

can a good working, very intelligent,

symbolic AI program, really exist?

Functional AI

“The scientific understanding

of the mechanism, underlying

thought and intelligent behavior and

their embodiment in machines,” is

the politically correct definition of

functional AI according to the Mer-

riam-Webster Online Dictionary. It is

also the basic foundation of func-

tional AI.

Many papers were written on

AI. In 1980, John Searle, in his pa-

per, Minds, Brains, and Programs

divided the field of functional AI into

two categories: strong artificial intel-

ligence and weak artificial intelli-

gence. In his opinion, strong AI,

works to develop a full human-like

intelligence, while weak AI is used

for the better understanding of hu-

man reasoning and to solve less com-

plex problems. This type of AI has

been the most helpful to scientists in

performing experiments. For right

now, researchers that this type of AI

would not prove very helpful.

Maybe...someday...in the future,

functional AI will achieve success...

Some Success

So far functional artificial intel-

ligence has achieved success such as:

fuzzy logic, heuristic searching, ma-

chine learning via statistical methods,

to practical problems.

The Problem

There are two problems with func-

tional AI:

1. Determination whether a task

should be considered an AI pro-

gram or just simply a computer

application.

2. Functional AI is rarely designed

Page 6

to communicate with other pro-

grams. Because of this it is usually

unable to understand the techniques

other programs use. How is that a

problem? To have a fully working

functional AI program, many dif-

ferent “parts” would have to com-

bine. Presently, this is not possible.

Relational AI

“ A third approach is to con-

sider intelligence as acquired., held,

and demonstrated only through re-

lationships with other intelligent

beings.” (Harzfeld) Alan Turing

was one of the most involved and

outspoken researchers of relational

AI. He suggested that programmers

should stop trying to create a pro-

gram with the intelligence of an

adult human being, and instead,

construct a mind that would simu-

late one that of a child. Such a

mind then, if given proper educa-

tion, would develop into an adult

mind. This idea came to be called

functional AI. Rodney Brooks of

the Massachusetts Institute of

Technology expanded on Turing’s

idea and created a few robots in-

cluding Cog and Kismet. Their pro-

gramming is distributed among the

various physical parts. Each joint

has a small processor that controls

only the movement of that joint.

The processors are then connected

to a larger processor which con-

trols the whole. So far these robots

have been trained to perform tasks

as those of an infant: eye-hand co-

ordination, handling simple objects,

and face recognition. Through so-

cial interaction with a team of re-

searchers.

The Turing Test

In 1997 in his paper Comput-

ing Machinery and Intelligence, Tur-

ing suggested a test which has now

been generously accepted as the ma-

chine test for intelligence ( more on

page 11 ) .

Neural Network

A branch of relational AI.

This area of AI shows much prom-

ise, it works by imitating the neurons

found in the brain. “Even though,

this field is also a bit limited, since

the human brain has billions of brain

cells, and scientists are yet to fully

understand how they work. It is

though that the neural network has

shown the most promise in areas

such as speech or image recognition,

and learning.

Page 7

I n 1997, a chess-playing com-

puter AI program, Deep Blue,

won a match against the Chess

World Champion. This symbolic

AI program was able to beat the cham-

pion because “the game of chess takes

place in a world where the only objects

are thirty-two pieces moving on a sixty

-four square board according to a lim-

ited number of rules.” (Herzfeld) The

limited options gave the program the

advantage of looking ahead, seeing all

(and I mean ALL) the possible moves,

and choosing the one which would

provide it with the largest benefit. This

accomplishment gave researchers hope

that symbolic AI, could prove helpful.

S o you think you are the only one who has to follow laws? Not true!

In Isaac Asimov’s science fiction books, he presented three main

“laws” that all robots had to follow. These laws were first presented in

his book “I, Robot: Runaround”, published in 1942.

“The Three Laws of Robotics:

1. A robot may not injure a human being, or through inaction, allow a human be-

ing to come to harm.

2. A robot must obey any orders given to it by human beings, except where such

orders would conflict with the First Law.

3. A robot must protect its own existence as long as such protection does not

conflict with the First or second Law.”

The Laws, so popular and sensible, are now being used by modern robot

constructors, as the foundation of the robot’s artificial intelligence.

The Three Laws of Robotics

Deep Blue Champion

Page 8

I n 1997, in his paper Computing

Machinery and Intelligence,

Turing suggested a test which

has now been generously ac-

cepted as the machine test for intelli-

gence. (from page 6) In this test, a

human interrogator is connected

through one terminal each, a human

and a machine with an installed AI.

The interrogator ask both ends the

same questions. If he fails to distin-

guish as often as he succeeds in deter-

mination who the machine and who

the human is, the machine/ computer

is considered to have a well working

artificial intelligence. “The Turing

Test is not based on the completion of

tasks or the solution of problem by

the machine, but on the machine’s

ability to relate to a human being in a

conversation.” (Herzfeld)

When Turing first presented

the idea of the test, he predicted that

by the year 2000, computers could

fool at least 30% of the interrogators.

So far no computer has came even

close to passing! After acknowledg-

ing that no program could pass his

test, Turing preformed more research

and predicted (again!) that it would

take about 300 more, human years to

construct a program which could

score the Turing Test with a perfect

score!!!

Turing Test

Page 9

Dear Editor,

Do AI programs have names?

Paulette T.

Dear Paulette,

Many AI programs have been cre-

ated, so it would be very hard for research-

ers to remember all their names. Only the

most successful AI programs have been

given a name.

Editor

Dear Editor,

What are AI programs used for?

Clint K.

Dear Clint,

Researchers hope that in the future

AI programs will make our daily life easier.

So far, AI is grouped into the following

categories, according to what the program

does:

knowledge representation and reasoning

speech and natural language processing

planning and problem solving

machine learning

computer vision

robotics

Editor

Dear Editor,

What is AI, anyway?

Camden A.

Dear Camden,

AI is the ability of a computer or

machine to act, but mostly think like a hu-

man.

Editor

Dear Editor,

Is a computer or video game AI?

Martin S.

Dear Martin,

No, a computer or video game is not

artificial intelligence. It is simply a com-

puter/TV application or program.

Editor

Dear Editor,

Do AI programs have attitude?

Lilliane F.

Dear Lilliane,

So far, no. AI programs are very

loyal to their creators. Lets hope that in the

future, artificial intelligence programs don’t

develop one.

Editor

Letters to the Editor

Page 1010

Artificial Intelligence Fun!

Page 11

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