Strong AI - yarbis

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23 Φεβ 2014 (πριν από 3 χρόνια και 3 μήνες)

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CONTENTS


INTRODUCTION

TO

A
.
I
.



EVOLUTION

OF

A
.
I
.



BRANCHES

OF

A
.
I
.



APPLICATIONS

OF

A
.
I
.



CONCLUSIONS

ON

A
.
I
.





INTRODUCTION

WHAT IS A.I. ?

A
.
I
.

is

a

branch

of

computer

science

that

studies

the

computational

requirements

for

tasks

such

as

perception,

reasoning

and

learning

and

develop

systems

to

perform

those

tasks

The field of Artificial intelligence strives to understand
and build intelligent entities

A.I.

Strong A.I.

M/C can think and

act like human

Weak A.I.

Some thinking like features

can be added to M/C

INTRODUCTION

TURING TEST

*

Intelligence

is

defined

as

the

ability

to

achieve

human

level



performance

in

all

cognitive

tests,

sufficient

to

fool

a

human



interrogator
.

*

The

test

was

devised

in

response

to

the

question,”

Can



a

computer

think

?”
.

*

Result

was

+ve

if

interrogator

can

not

tell

if

responses



are

coming

from

the

M/C

or

Human
.

* Proposed by Alan Turing(1950), a British Computer


Scientist.

INTRODUCTION

TURING TEST


One person sits at a computer and types the questions.



The computer is connected to two other hidden
computers



At one computer, Human reads and responds to
questions.



At the other end, computer with no Human aid runs the
program to provide responses.

INTRODUCTION

DEFINITIONS

*

AI

is

a

branch

of

computer

science

dealing

with

symbolic,



nonalgorithmic

methods

of

problem

solving

*

AI

is

a

branch

of

computer

science

that

deals

with

ways

of



knowledge

using

symbols

rather

than

numbers

and

with



Heuristics,

method

for

processing

information
.

*

AI

works

with

pattern

matching

methods

which

attempt

to



describe

objects

,

events

or

processes

in

terms

of

their



qualitative

features

and

logical

and

computational



Relationship
.

INTRODUCTION

What is
Intelligence
?


To

respond

to

situations

very

flexibly
.


To

make

sense

out

of

ambiguous

or

contradictory

messages
.


To

recognize

the

relative

importance

of

different

elements

of



situations


To

find

similarities

between

situations

despite

difference


To

draw

distinctions

between

situations

despite

similarities

which


may

link

them
.

HISTORY

1943



McCulloh

and

Pitts,

Boolean

circuit

model

of

brain
.


1950



Turing’s

computing

machine

and

intelligence
.


1950
’s



Early

AI

programs

including

Samuel’s

checker

program,

Newell

and

Simon’s

logic

theorist,

Gelisnters

geometry

engine


1956



Dartmouth

conference
.

HISTORY


1952
-
69



“Look,

Ma,

no

hands!”

era
.



1958



McCarthy

moves

to

MIT,

LISP

was

born
.



1965



Robinson’s

complete

algorithm

for

logical

reasoning
.



1966
-
74



AI

discovers

computational

complex
.



Neural

network

research

almost

disappears
.



1969
-
79

-

Early

development

in

knowledge

based

systems
.

HISTORY


1980
-
88

:

Expert

system

industry

booms
.



1988
-
93

:

Expert

system

industry

busts
.



1985
-
88

:

Neural

networks

return

to

popularity
.




1995

:

Agents


Agents


Agents
.


(present)

BRANCHES

Logical AI


What

a

program

knows

about

the

world

in

general

the

facts

of

the

specific

situation

in

which

it

must

act

and

it’s

goal

are

all

represented

by

sentences

of

some

mathematical

logical

language
.

Pattern Recognition


When

a

program

makes

observation

of

some

kind,

it

is

often

programmed

to

compare

what

it

sees

with

already

stored

patterns
.

BRANCHES

Representation


Facts

about

the

world

have

to

be

represented

in

some

way
.

Usually

languages

of

mathematical

logic

are

used
.

Common Sense, Knowledge and Reasoning


This

is

an

era

in

which

AI

is

farthest

from

human

level
.

While

there

has

been

considerable

progress,

e
.
g
.

in

development

systems

of

non

monotonic

reasoning

and

theories

of

action

BRANCHES

Planning


Planning

programs

start

with

general

facts

about

the

world
.

They

generate

a

strategy

for

achieving

the

goal,

the

strategy

is

just

a

sequence

of

action
.

Epistemology


This

is

a

study

of

the

kinds

of

knowledge

that

are

required

for

solving

problems

in

the

world
.

Ontology


It

is

the

study

of

kinds

of

things

that

exist
.

In

AI,

things

deal

with

various

kinds

of

object
.

BRANCHES

Heuristics


Heuristics

is

a

way

of

trying

to

discover

something

or

an

idea

embedded

in

a

program
.

It

predicates

that

compare

two

nodes

in

a

search

tree

to

see

if

one

is

better

than

other,

e
.
I
.

constitutes

an

advance

towards

the

goal,

may

be

more

useful
.

Genetic Engineering


It

is

a

technique

for

getting

programs

to

solve

a

task

by

mating

random

LISP

programs

and

selecting

fittest

in

millions

of

generations
.

APPLICATIONS OF A.I.


Expert systems.


Natural Language Processing (NLP).


Speech recognition.


Computer vision.


Robotics.


Automatic Programming.

APPLICATIONS

EXPERT SYSTEMS


An

Expert

System

is

a

computer

program

designed

to

act

as

an

expert

in

a

particular

domain

(area

of

expertise)
.


Expert

systems

currently

are

designed

to

assist

experts,

not

to

replace

them,

They

have

been

used

in

medical

diagnosis,

chemical

analysis,

geological

explorations

etc
.

Domain of E.S.

Knowledge base

Facts

Heuristics

Phases in Expert System

APPLICATIONS

Speech Recognition


The

primary

interactive

method

of

communication

used

by

humans

is

not

reading

and

writing,

it

is

speech
.


The

goal

of

speech

recognition

research

is

to

allow

computers

to

understand

human

speech
.

So

that

they

can

hear

our

voices

and

recognize

the

words

we

are

speaking
.


It

simplifies

the

process

of

interactive

communication

between

people

and

computers,

thus

it

advances

the

goal

of

NLP
.

APPLICATIONS

Natural Language Processing

The

goal

of

NLP

is

to

enable

people

and

computers

to

communicate

in

a

natural

(humanly)

language(such

as,

English)

rather

than

in

a

computer

language
.

The

field

of

NLP

is

divided

in

2

categories




Natural

Language

understanding
.



Natural

Language

generation
.

APPLICATIONS

Computer Vision


People

generally

use

vision

as

their

primary

means

of

sensing

their

environment,

we

generally

see

more

than

we

hear,

feel

or

smell

or

taste
.


The

goal

of

computer

vision

research

is

to

give

computers

this

same

powerful

facility

for

understanding

their

surrounding
.

Here

AI

helps

computer

to

understand

what

they

see

through

attached

cameras
.

APPLICATIONS

Robotics



A

Robot

is

a

electro
-
mechanical

device

that

can

by

programmed

to

perform

manual

tasks

or

a

reprogrammable

multi

functional

manipulator

designed

to

move

materials,

parts,

tools,

or

specialized

devices

through

variable

programmed

motions

for

performance

of

variety

of

tasks
.



An


intelligent


robot

includes

some

kind

of

sensory

apparatus

that

allows

it

to

respond

to

change

in

it’s

environment
.

APPLICATIONS

Robotics

APPLICATIONS

Automatic Programming


Programming

is

a

process

of

telling

a

computer

exactly

what

you

want

it

to

do
.
Writing

a

program

is

a

tedious

job
.

It

must

be

designed,

written,

tested,

debugged

and

evaluated
.


The

goal

of

automatic

planning

is

to

create

special

programs

that

act

intelligent

tools

to

assist

programmers

and

expedite

each

phase

of

programming

process
.

Ultimate

aim

is

computer

itself

should

develop

a

program

in

accordance

with

specifications

of

programmer
.

FUTURE

The

day

is

not

far

when

you

will

just

sit

back

in

your

cozy

little

beds

and

just

command

your

personal

Robot's

to

entirely

do

your

ruts

.

He

will

be

a

perfect

companion

for

you
.

Just

enjoy

the

Technology
.

FUTURE


But

wait,

don’t

be

happy
.

It

may

end

in

other

way

too
.

Some

day

there

will

be

a

knock

to

your

door
.

As

you

open

it,

you

see

a

large

number

of

Robots

marching

into

your

house

destroying

everything

you

own

and

looting

you
.



This

is

because

ever

since

there

is

an

advantage

in

the

Technology,

it

attracts

anti
-
social

elements
.

This

is

true

for

Robots

too
.

Because

now

they

will

have

full

power

to

think

as

human,

even

as

of

anti
-
social

elements
.

So

think

trice

before

giving

them

power

of

Cognition
.


CONCLUSION

In

it’s

short

existence,

AI

has

increased

understanding

of

the

nature

of

intelligence

and

provided

an

impressive

array

of

application

in

a

wide

range

of

areas
.

It

has

sharpened

understanding

of

human

reasoning,

and

of

the

nature

of

intelligence

in

general
.

At

the

same

time,

it

has

revealed

the

complexity

of

modeling

human

reasoning

providing

new

areas

and

rich

challenges

for

the

future
.