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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/ASIMO8/9/2019 Lec1-Introduction to Artificial Intelligence
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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.pdf8/9/2019 Lec1-Introduction to Artificial Intelligence
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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.