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CSC463-Fundamentals of AI(UiTM Trg MP Jul 2009) 1

What is AIFoundation of AI

History of AIState of the Art of AI (applications)

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Artificial? not genuine made by human and do not occur by nature

Intelligent? Ability to perform reasoning Ability to acquire knowledge Ability to apply knowledge (sense) Ability to perceive and manipulate things (understand)


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There is no agreed definition of the termArtificial Intelligence (AI). However,there are various definitions that havebeen proposed.

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Discipline that automates reasoning processes tocreate machines that:Thinking humanlyActing humanlyThinking rationallyActing rationally

Goal create computer systems that performtasks regarded as requiring intelligence when done

by humans.


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AI methodologyBased on application to be developed, such asExpert System (ES) software & hardware

Knowledge representationSearch methodRule basedReasoning logic, uncertaintyAgents

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Example of intelligent action

What to buy at the mall? A birthday present for a friendWhat present do I buy?What reason to buy?

How could a computer achieve this task?

Try to figure what basic AI processes would be involvedin the following :

Translating English sentences into Malay Teaching a child to subtract integers Solving a crossword puzzle

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The Turing Test just consists of a machinebehaving as a human impersonator. If the

machine can fool humans into thinking it ishuman, then the machine is considered

intelligent.

Basically the Turing Test is like the old saying,"if something looks like a duck, quacks like aduck, and walks like a duck (and tastes like

duck), then it's a duck".

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Turing treats the computer and the humanbrain as "black boxes". He is notinterested in the inner workings, only the

outward performance.

He provides a scientific, empirical,performance test by which to judge the

success of the AI project.

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Behavioral approach to determine whether or not a system is

intelligentProposed by Alan Turing (1950)Conversation key to judge intelligenceMeasures the performance of an allegedly intelligent machineagainst that of a human being (the best and standard forintelligent behavior)Called Imitation GamePlace machine and human counterpart apart from secondhuman being ( interrogator)

Interrogator not able to see or speak directly does not knowwhich entity is machineCommunicate by textual device (terminal)

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Distinguish the machine from human base on their answer toquestions asked over terminal deviceIf can not distinguish the machine may be assumed to beintelligentInterrogator need to uncover the machines identity may askarithmetic calculation assume machine will be more likely toget it correct than human.So the machine need to know when they should fail in orderto seem like human

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Important outcomes/results/features: Give understanding or idea or belief of intelligence i.e. the

behavior to response to a particular set of questions. Prevent from being sidetracked by such confusing andcurrently unanswerable question as whether or not thecomputer uses the appropriate internal processes. Eliminates any bias forcing interrogator to focus solely onthe content of the answers to the questions.

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1. The Dark Age: Birth of Artificial Intelligence (1943-1956

2. The Rise of Artificial Intelligence great expectation(1956 late 1960s)3. Unfulfilled promises impact of reality (late 1960s early

1970s)4. The technology of expert system key to success (early

1970s mid 1980s)5. How to make machine learn rebirth of neural networks

(mid 1980s onwards)6. Evolutionary Computation learning by doing (early

1970s onwards)7. The new era of knowledge Engineering computing with

words ( late 1980s onwards)

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1943 McCulloch & Pitts: Boolean circuit model of brain1950 Turings Computing Machinery and Intelligence

1950s Early AI programs, including Samuels checkers program, Newell & Simons Logic Theorist, Gelernters Geometry Engine 1656 Dartmouth meeting: Artificial Intelligence adopted 1965 Robinsons complete algorithm for logical reasoning 1966-74 AI discovers computational complexity , Neural

network research almost disappears1969-79 Early development of knowledge-based systems1980-88 Expert systems industry booms

1988-93 Expert systems industry busts: AI Winter 1985-95 Neural networks return to popularity 1988 Resurgence of probability: general increase in technicaldepth Nouvelle AI: ALife, GAs, soft computing

1995 Agents, agents, agentseverywhere 2003 Human-level AI back on the agenda


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Game playing IBMs Deep Blue

First AI to beat a human chess champion : Garry

Kasparov, 1997 Blondie24

Machine learning program that won a checkerstournament

Commercial game AIIncrease in more sophisticated AI work for non -academic games


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Logistics Planning Trip itinerariesEngines such as MapQuest use AI to propose drivingdirections from one location to another

Dynamic Analysis and replaning Tool (DART)Used during the 1991 Persian Gulf crisis to assist inmanaging military resources (over 50,000 people,vehicles and cargo shipments)

Airline flight schedulingIf flights are delayed or re-routed, AI planners are usedto figure the best way to re-schedule departures andarrivals


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Speech recognition Airline reservation systems

Often robust to many different voice pitches and

accents Automatic transcription

Monitor language and content for live radio andtelevision

Assist in the transcribing of closed-captionedtelevision programs


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Text processing Automated language translation

Altavistas Babelfish server Information retrieval

Google search engine Text classification and organization

Google news, SPAM filtering Document summarization

Columbia Universitys Newsblaster


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Biology & Medicine Diagnosis systems

Specialists often use statistical AI tolls to diagnose a patient has a disease based in his/her symptoms

Genome analysis software Now that the human and other genomes are complete.AI is used to identify new genes, infer biochemical

pathways, and compare genomes of multiple species


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Vision Handwriting recognitionUS Postal Service automatically sorts mail

Face recognition

Government/bank security systems Autonomous Land Vehicle In a Neural Network

(ALVINN)Uses camera data to automatically steer a car on a

highway at speeds up to 65 mph (from Washington,DC to San Diego and back)


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A computer program with problem solvers situated in interactive environments,which are each capable of flexible , autonomous , yet socially organized actionsthat can be.

Criteria Explanation ExampleSituatedness Receives input from environment in which

it is active and can also effect changeswithin that environment

ROBOCUP (soccer player) interactwith ball and opponent without fullknowledge of locations, challenges,etc.

Autonomous Interact with environment without directintervention of other agents.

Pass the ball to teammate or on goaldepending on its individual situation.

Flexible Responsive and proactive depending on itscurrent situation.

Move the ball depending to opponent pattern.

Social Interact with other software, orientedtowards the goal.

To score a goal interact with eachother.


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Most intelligent solutions require a variety of agents (society)Including Rote agents capture and communicate pieces of

information Coordination agents support the interactions between

other agents Search agents examine multiple pieces of information and

return some bit of it Learning agents examine collections of information and

form concepts or generalizations Decision agents dispatch tasks and come to conclusions in

the light of limited information and processing


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Main requisites for design and build such society Structures for the representation of information Strategies for the search through alternative solutions The creation of architectures that can support the

interaction of agents

CSC463 Fundamentals of AI

mp 2009 intro ai

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