1.2 - Introduction - Short

8/8/2019 1.2 - Introduction - Short

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Introduction to AI


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OutlineWhat is AI ?A brief history of AIState of the art


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What is AI?AI is a branch of CS with connections topsychology, linguistics, economics, Goal

make artificial systems solve (or help solve) problems thathumans can solve [in the same way as we do??]

Two fundamental aspects:Knowledge representation: making it explicit

Problem solving: heuristic


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What is AI?

Systems that actrationally

Systems that actlike humans

Systems thatthink rationally

Systems that thinklike humans


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What is AI? - Thinking like humans






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Thinking humanly1960s cognitive revolution

information-processing psychology replaced prevailingorthodoxy of behaviorism

Requires scientific theories of internal activitiesof the brainWhat level of abstraction? knowledge'' (cognitive science)or circuits'' (cognitive neuroscience) ?How to validate? Requires ( top-down ) predicting andtesting behavior of human subjects, or ( bottom-up ) directidentification from neurological data


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Thinking humanly: Cognitive ScienceThe interdisciplinary field of cognitive science brings together computer models from AI andexperimental techniques from psychology to try

to construct precise and testable theories of theworking of the human mind


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Thinking humanly: Cogn. NeurosciencMassively parallel neuron networks

Rosenblatts PerceptronMore complex ANN architectures

EvolutionGenetic algorithms (Holland)Evolutionary computation

Artificial lifealife.org


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What is AI? - Acting like humans






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Acting humanly: The Turing Test

Turing (1950): Computing machinery andintelligence

Can machines think?

Can machines behave intelligently?


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Operational test for intelligent behavior: theImitation Game


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Alan Turing ...predicted that by 2000, a machine might have a 30%chance of fooling a lay person for 5 minutesanticipated all major arguments against AI in following 50years

Problemthe Turing test is not reproducible, constructive, or amenable to mathematical analysis


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Acting humanly: Turing Test

To pass the Turing test, a computer would needto possess the following capabilitiesKnowledge representationAutomated reasoning

Machine learningNatural language (processing and) understanding

In so doing,Turing suggested the maincomponents of AI


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Acting humanly: Turing test - Eliza

A snapshot of a dialogue between Eliza ( E) andBBNs Vice President (V)V: Do you think that I can use the computer this morning?E: Why do you ask?

V: I might be able to make some additional Telcom sales.E: Why aren't you so sure?V: My perspective customers have never seen a

demonstration of the system.E: Does this mean very much to you?

Eliza: Weizembaum, 1965


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Acting humanly: Turing test - Eliza

A snapshot of a dialogue between Eliza ( E) andBBNs Vice President (V) [continued ]V: Of course it does.E: You seem very positive about that.

V: This is ridiculous.E: What do you mean, this is ridiculous?V: Is there any reason why I can't use the computer now?E: Tell me more about your perspective customers.V: Please dial me up on 491-1850

Eliza: Weizembaum, 1965


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Acting humanly: total Turing test

To pass the so-called total Turing test, acomputer would need to possess the followingcapabilities

Knowledge representation

Automated reasoningMachine learningNatural language (processing and) understandingComputer vision

Robotics


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What is AI? Thinking rationally






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Thinking rationally: Laws of thought

Aristotlewhat are correct arguments / thought processes?his famous syllogisms provided patterns for argumentstructures that always give correct conclusions givencorrect premises

The development of formal logic ...in the late nineteenth and early twentieth centuriesprovided a precise notation for reasoning about facts

Two main obstaclesnot easy to take informal knowledge and state it in theformal terms required by logical notationbig difference between being able to solve a problem inprinciple and doing so in practice


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What is AI? - Acting rationally






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Acting rationally: Rational behaviorRational behavior: doing the right thing

The right thing: that which is expected to maximize goalachievement, given the available information

Does not necessarily involve thinking (e.g.,blinking reflex) ...

but thinking should be in the service of rational action

Aristotle (Nicomachean Ethics):Every art and every inquiry, and similarly every action andpursuit, is thought to aim at some good


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Acting rationally: Rational agentsWe want to design rational agentsAn agent is an entity that perceives and actsAbstractly, an agent is a function from percepthistories to actions: f: P A


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Acting rationally: Rational agentsFor any given class of environments and tasks,we seek the agent (or class of agents) with thebest performance

Caveat: computational limitations make perfectrationality unachievable design best programfor given machine resourcesLimited or bounded rationality: optimize vssatisfy (Herbert Simon)


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Acting rationally: EngineeringRobotics (building artifacts that work)

Control: differential equations vs learningActing: mechanics of effectors (arms, legs, )Perception: sensors, vision, speech recognition...


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An example: Mars Exploration RoversSeveral generations of rovers: Pathfinder andSojourner 1997, Spirit and Opportunity 2003

mars.jpl.nasa.gov/mer


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Another example: RobocupSimulation and real robotsMulti-agent cooperationAn annual event

www.robocup.org


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AI and CS

Automatic problem solvingExpert systemsHeuristic programmingUncertainty management and reasoning

New programming paradigmsObject orientedFunctionalLogicWeb agents

Natural language analysis and synthesis


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AI: PrehistoryPhilosophy logic, methods of reasoning

mind as physical systemfoundations of learning, language, rationality

Mathematics formal representation and proof

algorithms, computation, (un)decidabilityprobabilityPsychology adaptation

phenomena of perception and motorial control

experimental techniques (psychophysics, etc.)


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AI: PrehistoryEconomics formal theory of rational decisionsGames games theoryLinguistics knowledge representation

grammar

Neuroscience physical substrate for mental activityControl theory homeostatic systemsstabilitysimple optimal agent designs


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AI: Some points in time1943 McCulloch & Pitts: Boolean circuit model of

brain1950 Turing's Computing Machinery and

Intelligence article

1952-69 Look, Ma, no hands! (early enthusiasm)1950s Early AI programs:- Samuel's checkers program,- Newell & Simon's Logic Theorist,

- Gelernter's Geometry Engine1956 Dartmouth meeting: term Artificial

Intelligence adopted


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AI: Some points in time1960s Lisp (McCarthy)1965 Robinson's complete algorithm for logical

reasoning1966-74 AI discovers computational complexity

Artificial Neural Networks research almostdisappears1969-79 Early development of knowledge-based systems

(Buchanan & Shortliffe)

Prolog (Colmerauer)1980-88 Expert systems industry booms

Machine learning1988-93 Expert systems industry busts: AI Winter


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AI: Some points in time1985-95 Artificial Neural Networks return to popularity1988-now Resurgence of probability; technical depth

Nouvelle AI'': ALife, GAs, soft computing1995-now Agents, ... agents everywhere

Data mining, SoftbotsChess: Deep Thought vs Kasparov


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AI: State of the art

Autonomous planning and schedulingGame playingAutonomous controlMedical diagnosis based on probabilistic analysisLogistics planningRobotic microsurgeryLanguage understanding and problem solving...


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AI: Schools

Problem solving (Simon, Newell)Simple agent societies (Minsky, Brooks)Robotics (Nilsson)Language and representation (Shank)Common sense reasoning (McCarthy, Lenat)Evolutionary Computation (Holland, Koza)Artificial Neural Networks (McCulloch, Pitts)Expert systems (Buchanan, Shortliffe)Machine learning (Samuel, Mitchell)Logic (Robinson, Colmerauer)

h f


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AI: The future you name it

Intelligent homesPersonalized assistants in cell phones and PDAsRoboticsDynamically created moviesSoccer between humans and robots...

Documents

1.2 - Introduction - Short