Lec1-Introduction to Artificial Intelligence

8/9/2019 Lec1-Introduction to Artificial Intelligence

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CS 4813 Artificial Intelligence

Shahzad Rafiq

Dept. of Computer Science,MAJU, Islamabad


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Course Objectives

Introduction to the basic principles, techniques,and applications of Artificial Intelligence.

Knowledge representation,

logic, inferencing, problem solving, search algorithms,game theory, perception, learning, planning, and agent design.

Futuristic expert systems, neural networks, fuzzy logic, robotics,natural language processing, and computer vision.


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Major Contents

Logic

Propositional Calculus, Predicate Calculus

Neural Networks

Perceptrons, Back Propagation, Self Organization Fuzzy Logic

Evolutionary Algorithms

Genetic Algorithm

Agent Based Approaches


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Reference Book

Textbook: Russell S. and Norvig P.,

Artificial Intelligence A Modern Approach,

2nd Ed, Prentice Hall 2003.


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Assessment Criteria

Quizzes 10%

Assignments & Project 30%

Presentation 10% Mid Terms 30%

End Term 20%


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Artificial Intelligence?

Lec-1


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What is Artificial Intelligence?

What is AI?

What is intelligence?

What features/abilities do humans (animals?

animate objects?) have that you think areindicative or characteristic of intelligence?

abstract concepts, mathematics, language,problem solving, memory, logical reasoning,

emotions, morality, ability to learn/adapt, etc


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Alternate Definitions (Russell + Norvig)

Like humans Not necessarily like humans

Systems that think likehumans

Systems that think rationally

Systems that act like

humans

Systems that act rationally

Thi

nk

A

ct


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Human intelligence

Shall AI imitate (copy) humans or not?

Advantage

Humans are easy acknowledged exemplar of

intelligence.

The Turing Test:

A human interrogator: Communicates with a hidden

subject that is either a computer system or a human.

If the human interrogator cannot reliably decidewhether on not the subject is a computer, the

computer is said to have passed the Turing test.


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An application of the Turing Test

See Luis von Ahn, Manuel Blum, Nicholas Hopper, and JohnLangford. CAPTCHA: Using Hard AI Problems for Security. InEurocrypt.


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Human intelligence

Question: Is any System passing a turning

test is intelligent?


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Computer vs Brain (2003)

Computer Human Brain

Computational Units 1 CPU, 108 gates 1011 neurons

Storage Units 1010 bits RAM 1011 neurons

1011 bits disk 1014 synapses

Cycle time 10-9 sec 10-3 sec

Bandwidth 1010 bits/ sec 1014 bits/ sec

Memory updates/ sec 109 1014

In general there are various reasons why trying to mimic humans mightnot be the best approach to AI.


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Imitate Human Intelligence or not?

Lack of Knowledge - brain performance of

higher level processes

Little information- for scientific

understanding of these processes

Neuroscience has been very influential in

some areas of AI e.g.

robotic sensing, vision processing, etc.


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Rationality

Alternative approach

Precise mathematical notion- do the right thing

in any particular circumstance

A precise mechanism for analyzing andunderstanding the properties of this ideal behavior we

are trying to achieve.

A precise benchmark against which we can measurethe behavior the systems we build.


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Rationality

Origin of Mathematical characterizations of rationalitysuch as logic (laws of thought) and

economics (utility theory how best to act under uncertainty,

game theory how self-interested agents interact

But No Silver Bullet solution exists

We can study them and give exact characterizations oftheir properties, good and bad.


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Computational Intelligence

AI tries to understand and model intelligence asa computational process.

Thus we try to construct systems whosecomputation achieves or approximates thedesired notion of rationality.

Hence AI is part of Computer Science. Other areas interested in the study of intelligence e.g., cognitive science: focuses on human intelligence.

related, but their central focus tends to be different


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Alternate Definitions (Russell + Norvig)

Like humans Not necessarily like humans

Systems that think likehuman

Systems that think rationally

Systems that act likehumans

Systems that act rationally

Thi

nk

A

ct


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Agency

Focus on acting rationally which has implications for thinking/reasoning

Useful to think of intelligent systems as being agents,either: with their own goals or that act on behalf of someone (a user)

An agentis an entity that exists in an environmentandthat acts on that environment based on itsperceptions of

the environment

An intelligent agentacts to further its own interests (orthose of a user).


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Agent

This diagram oversimplifies the internal

structure of the agent.

Agent

Environment

perceives acts


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Agent

Require more flexible interaction with the environment, the

ability to modify ones goals, knowledge that be applied

flexibly to different situations.

Agent

Environmentperceives

acts

Knowledge Goals

prior knowledge user


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Degrees of Intelligence

Dream: Building an intelligent system as capableas humans (Humanoids)

Systems have been built which exhibit variousdegrees of intelligence e.g.

Development of useful formalisms and algorithmsfor construction of intelligent systems. forms the foundation of our attempt to understand

intelligence as a computational process.


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ASIMO, a humanoid robot

manufactured by Honda

A U.S. Marine Corps technician

prepares to use a telerobot to detonate

a buried improvised explosive device

nearCampFallujah, Iraq
http://en.wikipedia.org/wiki/ASIMOhttp://en.wikipedia.org/wiki/Humanoidhttp://en.wikipedia.org/wiki/Hondahttp://en.wikipedia.org/wiki/U.S._Marine_Corpshttp://en.wikipedia.org/wiki/Improvised_explosive_devicehttp://en.wikipedia.org/wiki/Camp_Fallujahhttp://en.wikipedia.org/wiki/Camp_Fallujahhttp://en.wikipedia.org/wiki/Iraqhttp://en.wikipedia.org/wiki/Iraqhttp://en.wikipedia.org/wiki/Camp_Fallujahhttp://en.wikipedia.org/wiki/Camp_Fallujahhttp://en.wikipedia.org/wiki/Improvised_explosive_devicehttp://en.wikipedia.org/wiki/U.S._Marine_Corpshttp://en.wikipedia.org/wiki/Hondahttp://en.wikipedia.org/wiki/Humanoidhttp://en.wikipedia.org/wiki/ASIMO


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Artificial Intelligence


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Applied Areas

Planning

ComputerVision

NLP

ExpertSystems

Robotics

Search,

Reasoning,Learning

o Disciplines which form the core of AI- inner circleo Fields which draw from these disciplines- outer circle.


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Applied Areas

Game Playing Deep Blue Chess program

beat world champion GaryKasparov

Speech Recognition PEGASUS spoken language

interface to American Airlines'EASY SABRE reservation

system, which allows users toobtain flight information andmake reservations over thetelephone.


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Applied Areas

Mathematical Theorem Proving

Use of inference methods to prove new theorems.

Natural Language Understanding

AltaVista automated translation of web pages. Translation of Catepillar Truck manuals into 20

languages.

(Note: One early system translated the English sentence "The

spirit is willing but the flesh is weak" into the Russian equivalent

of "The vodka is good but the meat is rotten.")


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Computer Vision

Face recognition programs in use by banks,government, etc.

The ALVINN system autonomously drove a vanfrom Washington, D.C. to San Diego (all but 52 of

2,849 miles), averaging 63 mph day and night,and in all weather conditions.

Handwriting recognition, electronics andmanufacturing inspection, photo-interpretation,

baggage inspection, reverse engineering toautomatically construct a 3D geometric model.


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Expert Systems

Application-specific systems that rely onobtaining the knowledge of human experts in anarea and programming that knowledge into asystem.

DENDRAL, mass spectrometer interpreter

MYCIN, modeling medical expert

Microsoft Office Assistant:- customized help toindividual user


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Financial Decision Making

Credit card companies, mortgage companies and

banks AI systems detect fraud

expedite financial transactions like credit checks.

profiles of customer usage patterns use profiles to detect unusual patterns take

appropriate action.


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Scheduling and Planning

Automatic scheduling for manufacturing.

American Airlines rerouting contingency

planner.

European space agency planning and

scheduling of spacecraft assembly,

integration and verification


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Intelligent Robotics

Robot Toys

Aibo, I-Cybie, LEGO etc

Robot Security

Cye robot

Robot Home Help

Lawn mower, Vacuum cleaner etc


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Future: Autonomic Computing:

Concept CHOP

The Vision of Autonomic Computing, Jeffrey O.Kephart, David M.Chess, IBM Thomas J.Watson

Research, Retrieved on December 08, 2010,http://www.research.ibm.com/autonomic/research/papers/AC_Vision_Computer_Jan_2003.pdf
http://www.research.ibm.com/autonomic/research/papers/AC_Vision_Computer_Jan_2003.pdfhttp://www.research.ibm.com/autonomic/research/papers/AC_Vision_Computer_Jan_2003.pdf


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AI Challenges

Translating telephone

Accident-avoiding car

Home help robot

Smart clothes Intelligent agents that monitor and manage

information by filtering, digesting, abstracting

Tutors

Self-organizing systems, e.g., that learn toassemble something by observing a human doit.


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Summary

Objectives of AI:

Studies the design of systems that

{think, act} like {humans, rationally}.

AI successful applications:

decision making, expert systems, natural language

understanding, image processing.

See Chapter 1 of Russell & Norvig.

Documents

Lec1-Introduction to Artificial Intelligence