ai for sem 1

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computer would deserve to be calledcomputer would deserve to be calledintelligent if it could deceive a human intointelligent if it could deceive a human into

believing that it was humanbelieving that it was humanAlan TuringAlan Turing

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It is not my aim to surprise or shock youIt is not my aim to surprise or shock you----but the simplest way I can summarize is tobut the simplest way I can summarize is to

say that there are now in the worldsay that there are now in the world

machines that canmachines that can think, that can learn andthink, that can learn andthat can createthat can create.. Moreover, their ability toMoreover, their ability to

do these things is going to increase rapidlydo these things is going to increase rapidlyuntiluntil----in a visible futurein a visible future----the range ofthe range of

problems they can handle will beproblems they can handle will becoextensive with the range to which thecoextensive with the range to which the

human mind has been applied.human mind has been applied.

----Herbert SimonHerbert Simon

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Artificial Intelligence (AI) is the area of computer science focusing onArtificial Intelligence (AI) is the area of computer science focusing oncreating machines that can engage on behaviors that humanscreating machines that can engage on behaviors that humans

consider intelligentconsider intelligent

..

Researchers are creating systems which canResearchers are creating systems which can

mimic human thought,mimic human thought,

understand speech,understand speech,

beat the best human chess player etcbeat the best human chess player etc

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IntroductionIntroduction

AI for short, is a combination of computer science, physiology, andAI for short, is a combination of computer science, physiology, andphilosophyphilosophy

The beginnings of AI reach back before electronics, to philosophersThe beginnings of AI reach back before electronics, to philosophersand mathematicians such as Booleand mathematicians such as Boole

AI really began to intrigue researchers with the invention of theAI really began to intrigue researchers with the invention of the

computer in 1943computer in 1943The technology was finally available, to simulateThe technology was finally available, to simulate

intelligent behaviorintelligent behavior

1815 - 1864

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Over the next four decades, AI has grown from programs capable ofOver the next four decades, AI has grown from programs capable of

playing checkers, to systems designed to diagnose diseaseplaying checkers, to systems designed to diagnose disease

The products available today are only bits and pieces of what areThe products available today are only bits and pieces of what aresoon to followsoon to follow

The advancements in the quest for artificial intelligence have, andThe advancements in the quest for artificial intelligence have, andwill continue to affect our jobs, our education, and our lives.will continue to affect our jobs, our education, and our lives.

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Garry Kasparov playing against Deep Blue, the first machine to

win a chess match against a world champion.

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Artificial intelligence (AI) is the intelligence of machinesArtificial intelligence (AI) is the intelligence of machines

and the branch of computer science which aims to createand the branch of computer science which aims to createit.it.

Major AI textbooks define artificial intelligence as "theMajor AI textbooks define artificial intelligence as "thestudy and design of intelligent agentsstudy and design of intelligent agents

intelligent agent is a system that perceives its environment andintelligent agent is a system that perceives its environment andtakes actions which maximize its chances of successtakes actions which maximize its chances of success

John McCarthy, who coined the term in 1956 defines itJohn McCarthy, who coined the term in 1956 defines itasas

"the science and engineering of making intelligent machines"the science and engineering of making intelligent machines

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Among the traits that researchers hope machines will exhibit areAmong the traits that researchers hope machines will exhibit are

reasoning,reasoning,

knowledge,knowledge,

planning,planning,

learning,learning,

communication,communication, perceptionperception

the ability to move and manipulate objectsthe ability to move and manipulate objects

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AI research uses tools and insights from many fields, includingAI research uses tools and insights from many fields, includingcomputer sciencecomputer sciencePsychologyPsychologyPhilosophyPhilosophyNeuroscienceNeurosciencecognitive sciencecognitive scienceLinguisticsLinguisticsontologyontologyoperations researchoperations research economicseconomics control theorycontrol theoryProbabilityProbability optimizationoptimization logiclogic

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AI research also overlaps with tasks such asAI research also overlaps with tasks such asrobotics,robotics,control systemscontrol systemsschedulingschedulingdata miningdata mininglogisticslogisticsspeech recognitionspeech recognition

facial recognition etcfacial recognition etc

Other names for the field have been proposed such asOther names for the field have been proposed such ascomputational intelligencecomputational intelligencesynthetic intelligencesynthetic intelligenceIntelligent systemsIntelligent systemsor computational rationalityor computational rationality

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HistoryHistory

Although the computer provided the technology necessary for AI, it was

not until the early 1950's that the link between human intelligence andmachines was really observed.

Norbert Wiener was one of the first Americans to make observations onthe principle of feedback theory feedback theory.

The most familiar example of feedback theory is the thermostat: Itcontrols the temperature of an environment by gathering the actualtemperature of the house, comparing it to the desired temperature, andresponding by turning the heat up or down.

Wiener theorized that all intelligent behavior was the result of feedbackmechanisms. Mechanisms that could possibly be simulated by machines.

1894 - 1964

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In late 1955, Newell and Simon developed The Logic Theorist,In late 1955, Newell and Simon developed The Logic Theorist,

The program, representing each problem as a tree model, wouldThe program, representing each problem as a tree model, wouldattempt to solve it by selecting the branch that would most likelyattempt to solve it by selecting the branch that would most likelyresult in the correct conclusion.result in the correct conclusion.

In 1956 John McCarthy regarded as the father of AI, organized aconference to draw the talent and expertise of others interested inmachine intelligence for a month of brainstorming.In the seven years after the conference, AI began to pick upmomentum. Although the field was still undefined, ideas formed atthe conference were re-examined, and built upon. Centers for AIresearch began forming at Carnegie Mellon and MIT, and a newchallenges were faced:

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In 1957, the first version of a new program The General ProblemIn 1957, the first version of a new program The General ProblemSolver(GPS) was tested.Solver(GPS) was tested.

The program developed by the same pair which developed the LogicThe program developed by the same pair which developed the Logic

Theorist.Theorist.

The GPS was an extension of Wiener's feedback principle, and wasThe GPS was an extension of Wiener's feedback principle, and wascapable of solving a greater extent of common sense problems.capable of solving a greater extent of common sense problems.

A couple of years after the GPS, IBM contracted a team to researchA couple of years after the GPS, IBM contracted a team to researchartificial intelligence. Herbert Gelerneter spent 3 years working on aartificial intelligence. Herbert Gelerneter spent 3 years working on aprogram for solving geometry theorems.program for solving geometry theorems.

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While more programs were being produced, McCarthy was busy developing aWhile more programs were being produced, McCarthy was busy developing amajor breakthrough in AI history.major breakthrough in AI history.

In 1958 McCarthy announced his new development; the LISP language,In 1958 McCarthy announced his new development; the LISP language,which is still used today.which is still used today.

LISP stands for LISt Processing, and was soon adopted as the language ofLISP stands for LISt Processing, and was soon adopted as the language ofchoice among most AI developers.choice among most AI developers.

In 1963 MIT received a 2.2 million dollar grant from the United StatesIn 1963 MIT received a 2.2 million dollar grant from the United Statesgovernment to be used in researching Machinegovernment to be used in researching Machine--Aided Cognition (artificialAided Cognition (artificialintelligence).intelligence).

The grant by the Department of Defense's Advanced research projectsThe grant by the Department of Defense's Advanced research projectsAgency (ARPA), to ensure that the US would stay ahead of the Soviet UnionAgency (ARPA), to ensure that the US would stay ahead of the Soviet Unionin technological advancements.in technological advancements.

The project served to increase the pace of development in AI research, byThe project served to increase the pace of development in AI research, bydrawing computer scientists from arounddrawing computer scientists from around the world, and continues funding.the world, and continues funding.

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Other programs which appeared during the late 1960's wereOther programs which appeared during the late 1960's wereSTUDENT, which could solve algebra story problemsSTUDENT, which could solve algebra story problems

SIR which could understand simple English sentences.SIR which could understand simple English sentences.

The result of these programs was a refinement in languageThe result of these programs was a refinement in languagecomprehension and logiccomprehension and logic

Another advancement in the 1970's was the advent of the expertAnother advancement in the 1970's was the advent of the expertsystem. Expert systems predict the probability of a solution under setsystem. Expert systems predict the probability of a solution under setconditionsconditions

over the course of ten years, expert systems had been introduced toover the course of ten years, expert systems had been introduced toforecast the stock market, aiding doctors with the ability to diagnoseforecast the stock market, aiding doctors with the ability to diagnosedisease, and instruct miners to promising mineral locations. This wasdisease, and instruct miners to promising mineral locations. This was

made possible because of the systems ability to store conditionalmade possible because of the systems ability to store conditionalrules, and a storage of information.rules, and a storage of information.

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During the 1980's AI was moving at a faster pace, and further intoDuring the 1980's AI was moving at a faster pace, and further intothe corporate sector.the corporate sector.

In 1986, US sales of AIIn 1986, US sales of AI--related hardware and software surged torelated hardware and software surged to

$425 million.$425 million.

Expert systems in particular demand because of their efficiency.Expert systems in particular demand because of their efficiency.Companies such as Digital Electronics were using XCON, an expertCompanies such as Digital Electronics were using XCON, an expertsystem designed to program the large VAX computers. DuPont,system designed to program the large VAX computers. DuPont,General Motors, and Boeing relied heavily on expert systemsGeneral Motors, and Boeing relied heavily on expert systems

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The Transition from Lab to LifeThe Transition from Lab to Life

The personal computer made its debutThe personal computer made its debut

Such foundations as the American Association for Artificial Intelligence were foundedSuch foundations as the American Association for Artificial Intelligence were foundedwith the demand for AI development, created a push for researchers to join private companies.with the demand for AI development, created a push for researchers to join private companies.

150 companies such as DEC which employed its AI research group of 700 personnel, spend $1150 companies such as DEC which employed its AI research group of 700 personnel, spend $1billion on internal AI groups.billion on internal AI groups.

Other fields of AI also made there way into the marketplace during theOther fields of AI also made there way into the marketplace during the1980's. One in particular was the machine vision field.1980's. One in particular was the machine vision field.

The work by Minsky and Marr were now the foundation for the cameras andThe work by Minsky and Marr were now the foundation for the cameras and

computers on assembly lines, performing quality control.computers on assembly lines, performing quality control.Although crude, these systems could distinguish differences shapes inAlthough crude, these systems could distinguish differences shapes inobjects using black and white differences. objects using black and white differences.

By 1985 over a hundred companies offered machine vision systems in theBy 1985 over a hundred companies offered machine vision systems in theUS, and sales totaled $80 million.US, and sales totaled $80 million.

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The 1980's were not totally good for the AI industry.The 1980's were not totally good for the AI industry.

In 1986In 1986--87 the demand in AI systems decreased, and the industry87 the demand in AI systems decreased, and the industrylost almost a half of a billion dollars.lost almost a half of a billion dollars.

Companies such as Teknowledge and Intellicorp together lost moreCompanies such as Teknowledge and Intellicorp together lost morethan $6 million, about a third of there total earnings. The large lossesthan $6 million, about a third of there total earnings. The large lossesconvinced many research leaders to cut back funding.convinced many research leaders to cut back funding.

Another disappointment was the so called "smart truck" financed byAnother disappointment was the so called "smart truck" financed bythe Defense Advanced Research Projects Agency.the Defense Advanced Research Projects Agency.

The projects goal was to develop a robot that could perform manyThe projects goal was to develop a robot that could perform manybattlefield tasks. In 1989, due to project setbacks and unlikelybattlefield tasks. In 1989, due to project setbacks and unlikelysuccess, the Pentagon cut funding for the project.success, the Pentagon cut funding for the project.

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Despite these discouraging events, AI slowly recovered.Despite these discouraging events, AI slowly recovered.

New technology in Japan was being developed. Fuzzy logic, firstNew technology in Japan was being developed. Fuzzy logic, firstpioneered in the US has the unique ability to make decisions underpioneered in the US has the unique ability to make decisions under

uncertain conditions.uncertain conditions.

Also neural networks were being reconsidered as possible ways ofAlso neural networks were being reconsidered as possible ways ofachieving Artificial Intelligence.achieving Artificial Intelligence.

The 1980's introduced to its place in the corporate marketplace, andThe 1980's introduced to its place in the corporate marketplace, and

showed the technology had realshowed the technology had real life uses, ensuring it would be a keylife uses, ensuring it would be a key

in the 21st century.in the 21st century.

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AI put to the TestAI put to the TestThe military put AI based hardware to the test of war during Desert Storm.The military put AI based hardware to the test of war during Desert Storm.

AIAI--based technologies were used in missile systems, headsbased technologies were used in missile systems, heads--upup--displays, anddisplays, andother advancements.other advancements.

AI has also made the transition to the home. With the popularity of the AIAI has also made the transition to the home. With the popularity of the AIcomputer growing, the interest of the public has also grown.computer growing, the interest of the public has also grown.

Applications for the Apple Macintosh and IBM compatible computer, such asApplications for the Apple Macintosh and IBM compatible computer, such asvoice and character recognition have become available.voice and character recognition have become available.

Also AI

technology has made steadying camcorders simple using fuzzy logic.Also AI

technology has made steadying camcorders simple using fuzzy logic.

With a greater demand for AIWith a greater demand for AI--related technology, new advancements arerelated technology, new advancements arebecoming available.becoming available.

Inevitably Artificial Intelligence has, and will continue to affecting our livesInevitably Artificial Intelligence has, and will continue to affecting our lives

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Timeline of major AI events

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ApproachesApproaches

bottombottom--upupthe best way to achieve artificial intelligence is to build electronicthe best way to achieve artificial intelligence is to build electronicreplicas of the human brain's complex network of neuronsreplicas of the human brain's complex network of neurons

the best way to achieve artificial intelligence is to build electronicthe best way to achieve artificial intelligence is to build electronicreplicas of the human brain's complex network of neuronsreplicas of the human brain's complex network of neurons

AI researchers who prefer this bottomAI researchers who prefer this bottom--up approach to constructup approach to constructelectronic circuits that act as neurons do in the human brain.electronic circuits that act as neurons do in the human brain.

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much of the working of the brain remainsmuch of the working of the brain remainsunknownunknown

complex network of neurons is what givescomplex network of neurons is what giveshumans intelligent characteristics.humans intelligent characteristics.

By itself, a neuron is not intelligent, butBy itself, a neuron is not intelligent, butwhen grouped together, neurons are ablewhen grouped together, neurons are able

to pass electrical signals through networks.to pass electrical signals through networks.

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Warren McCulloch after completing medical school atWarren McCulloch after completing medical school atYale, along with Walter Pitts a mathematician proposed aYale, along with Walter Pitts a mathematician proposed ahypothesis to explain the fundamentals of how neuralhypothesis to explain the fundamentals of how neuralnetworks made the brain work.networks made the brain work.

Based on experiments with neurons, McCulloch and PittsBased on experiments with neurons, McCulloch and Pittsshowed that neurons might be considered devices forshowed that neurons might be considered devices forprocessing binary numbers.processing binary numbers.

binary numbers (represented as 1's and 0's or true andbinary numbers (represented as 1's and 0's or true andfalse) were also the basis of the electronic computer.false) were also the basis of the electronic computer.

This link is the basis of computerThis link is the basis of computer--simulated neuralsimulated neural

networks, also know as Parallel computing.networks, also know as Parallel computing.

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Booles contributionBooles contributionA century earlier the true / false nature of binaryA century earlier the true / false nature of binarynumbers was theorized in 1854 by George Boole in hisnumbers was theorized in 1854 by George Boole in hispostulates concerning the Laws of Thought.postulates concerning the Laws of Thought.

Boole's principles make up what is known as BooleanBoole's principles make up what is known as Booleanalgebra,algebra,

the collection of logic concerning AND, OR, NOTthe collection of logic concerning AND, OR, NOToperands.operands.

For example according to the Laws of thought the statement:For example according to the Laws of thought the statement:(for this example consider all apples red)(for this example consider all apples red)

Apples are redApples are red---- isis TrueTrue

Apples are red AND oranges are purpleApples are red AND oranges are purple---- isis FalseFalse

Apples are red OR oranges are purpleApples are red OR oranges are purple---- isis TrueTrue

Apples are red AND oranges are NOT purpleApples are red AND oranges are NOT purple---- is alsois also TrueTrue

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Boole also assumed that the human mind worksBoole also assumed that the human mind worksaccording to these lawsaccording to these laws

it performs logical operations that could beit performs logical operations that could bereasonedreasoned

Ninety years later, Claude Shannon appliedNinety years later, Claude Shannon appliedBoole's principles in circuits the blueprint forBoole's principles in circuits the blueprint for

electronic computerselectronic computers

Boole's contribution to the future of computingBoole's contribution to the future of computingand Artificial Intelligence was immeasurable, andand Artificial Intelligence was immeasurable, and

his logic is the basis of neural networks.his logic is the basis of neural networks.

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Frank Rosenblatt, experimenting with computerFrank Rosenblatt, experimenting with computersimulated networks, was able to create asimulated networks, was able to create amachine that could mimic the human thinkingmachine that could mimic the human thinkingprocess, and recognize letters.process, and recognize letters.

But, with new topBut, with new top--down methods becomingdown methods becomingpopular, parallel computing was put on hold.popular, parallel computing was put on hold.

Now neural networks are making a return, andNow neural networks are making a return, andsome researchers believe that with new computersome researchers believe that with new computerarchitectures, parallel computing and the bottomarchitectures, parallel computing and the bottom--up theory will be a driving factor in creatingup theory will be a driving factor in creatingartificial intelligence.artificial intelligence.

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Top Down Approaches; Expert SystemsTop Down Approaches; Expert Systems

TopTop--down approachdown approach attempts to mimic the brain'sattempts to mimic the brain'sbehavior with computer programs.behavior with computer programs.

Because of the large storage capacity of computers,Because of the large storage capacity of computers,expert systems had the potential to interpret statisticsexpert systems had the potential to interpret statistics

in order to formulate rules. An expert system worksin order to formulate rules. An expert system works

much like a detective solves a mystery. Using themuch like a detective solves a mystery. Using theinformation, and logic or rules, an expert system caninformation, and logic or rules, an expert system cansolve the problemsolve the problem

For example it the expert system was designed toFor example it the expert system was designed todistinguish birds it may have the following:distinguish birds it may have the following:

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Charts like these represent the logic ofCharts like these represent the logic ofexpert systemsexpert systems

Using a similar set of rules, experts canUsing a similar set of rules, experts canhave a variety of applicationshave a variety of applications

With improved interfacing, computers mayWith improved interfacing, computers maybegin to find a larger place in society.begin to find a larger place in society.

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ChessChess

AIAI--based game playing programs combine intelligence withbased game playing programs combine intelligence withentertainmententertainment One game with strong AI ties is chessOne game with strong AI ties is chess

WorldWorld--champion chess playing programs can see ahead twenty pluschampion chess playing programs can see ahead twenty plusmoves in advance for each move they make.moves in advance for each move they make.

In addition, the programs have an ability to get progressably betterIn addition, the programs have an ability to get progressably betterover time because of the ability to learnover time because of the ability to learn

Chess programs do not play chess as humans do. In three minutes,Chess programs do not play chess as humans do. In three minutes,Deep Thought (a master program) considers 126 million moves whileDeep Thought (a master program) considers 126 million moves whilehuman chessmaster on average considers less than 2 moveshuman chessmaster on average considers less than 2 moves

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Herbert Simon suggested that human chess masters are familiarHerbert Simon suggested that human chess masters are familiarwith favorable board positions, and the relationship with thousands ofwith favorable board positions, and the relationship with thousands ofpieces in small areas. Computers on the other hand, do not takepieces in small areas. Computers on the other hand, do not takehunches into account. The next move comes from exhaustivehunches into account. The next move comes from exhaustivesearches into all moves, and the consequences of the moves basedsearches into all moves, and the consequences of the moves based

on prior learning.on prior learning.

Chess programs, running on Cray super computers have attained aChess programs, running on Cray super computers have attained arating of 2600 (senior master), in the range ofGary Kasparov, therating of 2600 (senior master), in the range ofGary Kasparov, theRussian world championRussian world champion

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FramesFramesOne method that many programs use to represent knowledge areOne method that many programs use to represent knowledge areframesframes

Pioneered by Marvin Minsky, frame theory revolves around packetsPioneered by Marvin Minsky, frame theory revolves around packetsof informationof information

For example, say the situation was a birthday party. A computerFor example, say the situation was a birthday party. A computercould call on its birthday frame, and use the information contained incould call on its birthday frame, and use the information contained inthe frame, to apply to the situationthe frame, to apply to the situation

The computer knows that there is usually cake and presents becauseThe computer knows that there is usually cake and presents becauseof the information contained in the knowledge frame. Frames canof the information contained in the knowledge frame. Frames canalso overlap, or contain subalso overlap, or contain sub--framesframes

The use of frames also allows the computer to add knowledge.The use of frames also allows the computer to add knowledge.Although not embraced by all AI developers, frames have been usedAlthough not embraced by all AI developers, frames have been used

in comprehension programs such asin comprehension programs such as SamSam

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SamSam

Sam is a program from Yale's AI lab which is able to readSam is a program from Yale's AI lab which is able to readbetween the lines, and assume certain facts.between the lines, and assume certain facts.

The Story:The Story:

John went to New York by bus. On the bus he talked toJohn went to New York by bus. On the bus he talked toan old lady. When he left the bus, he thanked the driver.an old lady. When he left the bus, he thanked the driver.He took the subway to Leone's. On the subway his pocketHe took the subway to Leone's. On the subway his pocket

was picked. He got off the train and entered Leone's. Hewas picked. He got off the train and entered Leone's. Hehad some lasagna. When the check came, he discoveredhad some lasagna. When the check came, he discoveredhe couldn't pay. The management told him he wouldhe couldn't pay. The management told him he wouldhave to wash dishes. When he left, he caught a bus tohave to wash dishes. When he left, he caught a bus toNew Haven.New Haven.

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Sam's comprehension: (Sam's answersSam's comprehension: (Sam's answersare inare in redred.).)

Why did John go to New York?Why did John go to New York?

Because John wanted to go to Leone'sBecause John wanted to go to Leone's

How did John get to Leone's?How did John get to Leone's?John took a bus to New York and then heJohn took a bus to New York and then hetook the subway to Leone's.took the subway to Leone's.

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Did anything unusual happen on the bus?Did anything unusual happen on the bus?I don't remember anythingI don't remember anything

Did anything unusual happen on the subway?Did anything unusual happen on the subway?A thief picked John's pocket.A thief picked John's pocket.

What did John order?What did John order?

John ordered lasagna.John ordered lasagna.

Did anything unusual happen at the restaurant?Did anything unusual happen at the restaurant?John discovered that he could not pay the check andJohn discovered that he could not pay the check and

so he had to wash dishes.so he had to wash dishes.

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Why couldn't John pay the check?Why couldn't John pay the check?Because John didn't have any money.Because John didn't have any money.

Why didn't John have any money?Why didn't John have any money?Because a thief picked John's pocket.Because a thief picked John's pocket.

How did John get back to New Haven?How did John get back to New Haven?John went from Leone's by subway and then he wentJohn went from Leone's by subway and then he went

to New Haven by bus.to New Haven by bus.

How was John able to take the bus to NewHow was John able to take the bus to NewHaven?Haven?

Probably he had a ticket.Probably he had a ticket.

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Sam's logic is represented in frames. For this story SamSam's logic is represented in frames. For this story Sammight use a restaurant frame, and a subway and busmight use a restaurant frame, and a subway and busframe. These frames spell out what events in order mostframe. These frames spell out what events in order mostlikely would occur in situations.likely would occur in situations.

Sam is impressive, because it can draw conclusions fromSam is impressive, because it can draw conclusions fromthe story that are not specifically stated. Also, with thethe story that are not specifically stated. Also, with thelast response, Sam shows that he can make conjectureslast response, Sam shows that he can make conjectureswithout information from the story, with the use ofwithout information from the story, with the use offrames.frames.

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ELIZAELIZA

Eliza, Joseph Wiezbaum's result of trying to make aEliza, Joseph Wiezbaum's result of trying to make aprogram converse in English amazed people when itprogram converse in English amazed people when itappeared in mid 1960's.appeared in mid 1960's.

The program was able to converse about any subject,The program was able to converse about any subject,because it stored subject information in data banks.because it stored subject information in data banks.Another feature of Eliza was its ability it picked up speechAnother feature of Eliza was its ability it picked up speechpatterns.patterns.notably, after creating one of the most famous programsnotably, after creating one of the most famous programsWiezbaum objected to the bonds that interviewees wereWiezbaum objected to the bonds that interviewees weremaking with his creation, and denounced the intelligencemaking with his creation, and denounced the intelligenceof Eliza.of Eliza.The following passage shows Elizas talking to a teenageThe following passage shows Elizas talking to a teenagegirl. The teenager speaks first, and Eliza's answers are ingirl. The teenager speaks first, and Eliza's answers are inblue.blue.

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Men are all alike.Men are all alike.

IN WHAT WAYIN WHAT WAY

They're always bugging us aboutThey're always bugging us aboutsomething or other.something or other.

CAN YOU THINK OF A SPECIFIC EXAMPLECAN YOU THINK OF A SPECIFIC EXAMPLE

Well, my boyfriend made me come here.Well, my boyfriend made me come here.

YOUR BOYFRIEND MADE YOU COME HEREYOUR BOYFRIEND MADE YOU COME HERE

He says that I am depressed all the time.He says that I am depressed all the time.

I AMSORRY TO HERE YOU AREI AMSORRY TO HERE YOU ARE

DEPRESSEDDEPRESSED

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It's true that I am unhappyIt's true that I am unhappy

DO YOU THINK COMING HERE WILL HELPDO YOU THINK COMING HERE WILL HELPYOU NOT TO BE UNHAPPYYOU NOT TO BE UNHAPPY

I need help, that seems certain.I need help, that seems certain.

WHAT WOULD IT MEAN IF YOU GOT SOMEWHAT WOULD IT MEAN IF YOU GOT SOMEHELPHELP

Perhaps I could learn to get along with myPerhaps I could learn to get along with mymother.mother.

TELL ME MORE ABOUT YOUR FAMILYTELL ME MORE ABOUT YOUR FAMILY

My mother takes care of me.My mother takes care of me.

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WHO ELSE IN YOUR FAMILY TAKES CAREWHO ELSE IN YOUR FAMILY TAKES CAREOF YOUOF YOU

My father.My father.YOUR FATHERYOUR FATHER

You are like my father in some ways.You are like my father in some ways.

WHAT RESEMBLANCE DO YOU SEEWHAT RESEMBLANCE DO YOU SEEYou are not very aggressive but I thinkYou are not very aggressive but I thinkyou don't want me to notice that.you don't want me to notice that.

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WHAT MAKES YOU THINK THAT I AM NOTWHAT MAKES YOU THINK THAT I AM NOTVERY AGGRESSIVEVERY AGGRESSIVE

You dont argue with me.You dont argue with me.WHY DON'T YOU THINK I ARGUE WITHWHY DON'T YOU THINK I ARGUE WITHYOUYOU

You are afraid of me.You are afraid of me.DOES IT PLEASE YOU TO BELIEVE I AMDOES IT PLEASE YOU TO BELIEVE I AMAFRAID OF YOUAFRAID OF YOU

My father is afraid of everybody.My father is afraid of everybody.

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WHAT ELSE COMES TO MIND WHEN YOU THINK OFWHAT ELSE COMES TO MIND WHEN YOU THINK OFYOUR FATHERYOUR FATHER

Bullies.Bullies.

DOES THAT HAVE ANYTHING TO DO WITH THE FACTDOES THAT HAVE ANYTHING TO DO WITH THE FACTTHAT YOUR BOYFRIEND MADE YOU COME HERETHAT YOUR BOYFRIEND MADE YOU COME HERE

As impressive as Eliza looks, Wiezbaum noted that itAs impressive as Eliza looks, Wiezbaum noted that itunderstood no more of the girl's problems as an alarmunderstood no more of the girl's problems as an alarm

clock understands when to go off. For example, the lastclock understands when to go off. For example, the lastsentence gives the impression of comprehension, but insentence gives the impression of comprehension, but infact the program is written so that at one point, itfact the program is written so that at one point, itmodifies the first sentence and applies it as a response.modifies the first sentence and applies it as a response.

ai for sem 1

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