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G51IAI
Introduction to AI
Instructor: Ho Sooi Hock
Introduction
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Module Introduction
Goals and Module Context
Delivery and Assessment Methods
Learning Support
Lecture Schedules
AI Terminologies
Applications of AI
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Module Aims and Objectives
Define what we mean by AI (or at leastgive us a working definition for thismodule)
Allow the students to become familiarwith some basic AI algorithms
Provide an understanding of the basictheory of a range of AI techniques andapplications
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Module Context
G51IAI
Introduction to AI
G52PAS
Planning and Search
G53CLP Constraint
Logic Programming
G53IDS Individual Dissertation
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Who Can Attend? (2010/2011)
G51IAI - Introduction to AI
CS First Year Compulsory
CIS/CSM Second Year Option
G52PASPlanning and Search
CS Second/Third Year Option
CIS Third Year Option
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Delivery & Assessments
Lectures
approx, 20 hours
supplemented by self readings 2 hrs/week, Wednesday 11:00 a.m.1:00 p.m.
Assessment
100% examination (2 hours)4 out of 6questions
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Recommended TextsArtificial Intelligence :
A Modern Approach
Third Edition by Stuart J. Russell & Peter Norvig
(2010, Prentice Hall, ISBN 0-13-207148-7) (Course Text)
Artificial Intelligence :
Structures and Strategies for Complex Problem Solving
Sixth Edition by George F. Luger
(2008, Addison Wesley, ISBN 0-321-54589-3)
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Recommended TextsArtificial Intelligence :
A Modern Approach
Second Edition by Stuart J. Russell & Peter Norvig
(2003, Prentice Hall, ISBN 0-13-080302-2) (Course Text)
Artificial Intelligence :
Structures and Strategies for Complex Problem Solving
Fifth Edition by George F. Luger
(2005, Addison Wesley, ISBN 0-321-26318-9)
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Useful Readings
Artificial Intelligence
by Elaine Rich & Kevin Knight, McGraw-Hill
The Essence of Artificial Intelligence by Alison Cawsey, Prentice Hall
Artificial Intelligence: a Guide to IntelligentSystems
by Michael Negnevitsky, Addison Wesley
Fundamentals of Neural Networks: Architectures,Algorithms and Applications
by Laurene Fausett, Prentice Hall
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Proposed Lecture Schedule
Lecture 1 : Introduction
Lecture 2 : History & Philosophy of AI
Lecture 3 : Problem Formulation
Lecture 4 : Blind Searches
Lecture 5 : Heuristic Search
Lecture 6 : Game Playing
Lecture 7 : Neural Networks
Lecture 8 : Neural Networks
Lecture 9 : Other AI Techniques
Lecture 10: Other AI Techniques
Revision
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What is AI?
A broad field that means different things to different people
Defining artificial is easy but no broad consensus in
precise, concrete terms for intelligence:
exclusive province of human being?
natural phenomenon exhibited by living organisms?
an arbitrarily specified set of abilities?
other definitions??
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Natural vs Machine Intelligence
Intelligence is not an unique and unshared capability of
human. It is more an open collection of attributes than it is
a single well-defined entity
Humans embody many aspects of intelligence whileanimals typically embody a smaller number of intelligent
characteristics, and usually at a much lower level
The advent of digital computers made possible credible
attempts to fulfill the AI dreams
Computer based intelligence must be specialised to very
restricted domains to be at all comparable to human
performance
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Human vs Machine Intelligence
Many tasks which we might
reasonably think requireintelligence
are performed by computers withouteven thinking
Complex
Arithmetic
Other tasks that people do without
thinking are extremely difficult to
automate
Recognizing
a Face
The two hemispheres of the human brain deal with problems intwo distinct paradigms:
sequential (or logical) approach that considers only a small
portion of the available data at a time
parallel (or gestalt) processinglooks at data on a global basis
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AI Problems
Experts tasks (require specialised skills and training) include :
Medical diagnosis
Equipment repair
Computer configuration
Financial planning
AI is concerned with automating both mundane
and expert tasks.
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AI Problems
Mundane tasks correspond to the following AI problems areas:
Planning :
Vision :
Robotics:
Natural Language:
The ability to decide on a good sequence of
actions to achieve our goals
The ability to make sense of what we see
The ability to move and act in the world, possibly
responding to new perceptions
The ability to communicate with others in
any human language
Mundane tasks are generally much harder to
automate
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AI Terminologies
Strong AI machines can actually think intelligently
Weak AI machine can possibly act intelligently
AIMA: Most AI researchers take the weakhypothesis for granted, and dont care about the
strong AI hypothesis(Chap. 26. p. 947)
Strong vs Weak AI Methods
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Applications of AI?
Search engines
Labor
Science
Medicine/Diagnosis
AppliancesWhat else?
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Contents
History and Philosophy
AI Definitions
Turing Test and Chinese Room
Search Techniques
Problem Formulation
State Space Search
o Tree Search: Depth-First and Breadth-First
o Heuristic Search: A* Search
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Contents
Game Playing
History
Game Tree Search: mini-max and alpha-beta pruning
Neural Networks
Perceptrons
Limitations
Learning Algorithms
Others
TBD
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Summary
Module goals, Structure and Contents
Course Schedule and Assessment
Practical and Administrative Matters
Review of Some Key Definitions
Applications of AI
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Directed Readings
Definitions of AI
Differentiate between
Strong and Weak AI
Strong and Weak AI Methods
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