introduction to artificial intelligence

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7/21/2019 Introduction to Artificial Intelligence http://slidepdf.com/reader/full/introduction-to-artificial-intelligence-56da4ecd6ea7e 1/4 INTELLIGENT SYSTEMS – CSM 351 L01 - INTRODUCTION TO ARTIFICIAL INTELLIGENCE Outline of ti! Le"tu#e Course overview What is AI? A brief history The state of the art Cou#!e o$e#$ie% Introduction to AI Intelligent Agents Search as Problem Solving Method More Search Strategies Constraint Satisfaction Problems Knowledge e!resentation " easoning # Knowledge e!resentation " easoning $ Inference in %irst&'rder (ogic &'t i! AI(  )iews of AI fall into four categories* Thin+ing humanly Thin+ing rationally Acting humanly Acting rationally The main te,tboo+ advocates -acting rationally- A"tin) u*'nl+, Tu#in) Te!t Turing .#/012 -Com!uting machinery and intelligence-* -Can machines thin+?-  -Can machines behave intelligently?- '!erational test for intelligent behavior* the Imitation 3ame  Predicted that by $1114 a machine might have a 516 chance of fooling a lay !erson for 0 1

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Basis of Artificial Intelligence

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Page 1: Introduction to Artificial Intelligence

7/21/2019 Introduction to Artificial Intelligence

http://slidepdf.com/reader/full/introduction-to-artificial-intelligence-56da4ecd6ea7e 1/4

INTELLIGENT SYSTEMS – CSM 351

L01 - INTRODUCTION TO ARTIFICIAL INTELLIGENCE

Outline of ti! Le"tu#e• Course overview

• What is AI?

• A brief history

• The state of the art

Cou#!e o$e#$ie%• Introduction to AI

• Intelligent Agents

• Search as Problem Solving Method

• More Search Strategies

• Constraint Satisfaction Problems

• Knowledge e!resentation " easoning #

• Knowledge e!resentation " easoning $

• Inference in %irst&'rder (ogic

&'t i! AI( )iews of AI fall into four categories*

• Thin+ing humanly

• Thin+ing rationally

• Acting humanly

• Acting rationally

The main te,tboo+ advocates -acting rationally-

A"tin) u*'nl+, Tu#in) Te!t

• Turing .#/012 -Com!uting machinery and intelligence-*

• -Can machines thin+?- -Can machines behave intelligently?-

• '!erational test for intelligent behavior* the Imitation 3ame

 

• Predicted that by $1114 a machine might have a 516 chance of fooling a lay !erson for 0

1

Page 2: Introduction to Artificial Intelligence

7/21/2019 Introduction to Artificial Intelligence

http://slidepdf.com/reader/full/introduction-to-artificial-intelligence-56da4ecd6ea7e 2/4

minutes

• Antici!ated all ma7or arguments against AI in following 01 years

• Suggested ma7or com!onents of AI* +nowledge4 reasoning4 language understanding4

learning

Tinin) u*'nl+, "o)niti$e *o.elin)

• #/81s -cognitive revolution-* information&!rocessing !sychology• e9uires scientific theories of internal activities of the brain

 && :ow to validate? e9uires#2 Predicting and testing behavior of human sub7ects .to!&down2

or $2 ;irect identification from neurological data .bottom&u!2

• <oth a!!roaches .roughly4 Cognitive Science and Cognitive =euroscience2

are now distinct from AI

Tinin) #'tion'll+, /l'%! of tou)t/

• A#i!totle* what are correct arguments>thought !rocesses?

• Several 3ree+ schools develo!ed various forms of logic* notation and rules of derivation 

for thoughts may or may not have !roceeded to the idea of mechani@ation

• ;irect line through mathematics and !hiloso!hy to modern AI

• Problems*

# =ot all intelligent behavior is mediated by logical deliberation

$ What is the !ur!ose of thin+ing? What thoughts should I have?

A"tin) #'tion'll+, #'tion'l ')ent

• ational behavior is doing the right thing

• The right thing is that which is e,!ected to ma,imi@e goal achievement4 given the

available information

• ;oesnBt necessarily involve thin+ing eg4 blin+ing refle, but thin+ing should be in theservice of rational action

R'tion'l ')ent!• An agent is an entity that !erceives and acts

• AI is about designing rational agents

• Abstractly4 an agent is a function from !erce!t histories to actions*

D f * PE AF

• %or any given class of environments and tas+s4 we see+ the agent .or class of agents2 with

the best !erformance• Caveat* com!utational limitations ma+e !erfect rationality unachievable

 design best !rogram for given machine resources

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Page 3: Introduction to Artificial Intelligence

7/21/2019 Introduction to Artificial Intelligence

http://slidepdf.com/reader/full/introduction-to-artificial-intelligence-56da4ecd6ea7e 3/4

AI #ei!to#+Philoso!hy (ogic4 methods of reasoning4 mind as !hysical system foundations

of learning4 language4 rationality

Mathematics %ormal re!resentation and !roof algorithms4 com!utation4

.un2decidability4 .in2tractability4 !robability

Gconomics utility4 decision theory

 =euroscience !hysical substrate for mental activity

Psychology !henomena of !erce!tion and motor control4 e,!erimentaltechni9ues

Com!uter building fast com!uters

engineering

Control theory design systems that ma,imi@e an ob7ective function over time

(inguistics +nowledge re!resentation4 grammar  

A#i.)e. i!to#+ of AI#/H5 McCulloch " Pitts* <oolean circuit model of brain

#/01 TuringBs -Com!uting Machinery and Intelligence-#/08 ;artmouth meeting* -Artificial Intelligence- ado!ted

#/0$8/ (oo+4 Ma4 no handsJ

#/01s Garly AI !rograms4 including SamuelBs chec+ers !rogram4 =ewell "

SimonBs (ogic Theorist4 3elernterBs 3eometry Gngine#/80 obinsonBs com!lete algorithm for logical reasoning

#/885 AI discovers com!utational com!le,ity =eural =etwor+ research almost

disa!!ears#/8// Garly develo!ment of +nowledge&based systems

#/L1&& AI becomes an industry

#/L8&& =eural =etwor+s return to !o!ularity#/L&& AI becomes a science

#//0&& The emergence of intelligent agents

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Page 4: Introduction to Artificial Intelligence

7/21/2019 Introduction to Artificial Intelligence

http://slidepdf.com/reader/full/introduction-to-artificial-intelligence-56da4ecd6ea7e 4/4

St'te of te '#t• ;ee! <lue defeated the reigning world chess cham!ion 3arry Kas!arov in #//

• Proved a mathematical con7ecture .obbins con7ecture2 unsolved for decades

•  =o hands across America .driving autonomously /L6 of the time from Pittsburgh to San

;iego2

• ;uring the #//# 3ulf War4 S forces de!loyed an AI logistics !lanning and scheduling

 !rogram that involved u! to 014111 vehicles4 cargo4 and !eo!le

•  =ASABs on&board autonomous !lanning !rogram controlled the scheduling of o!erations

for a s!acecraft

•   Proverb solves crossword !u@@les better than most humans

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