Transcript Course outline

CS 331 / CMPE 334 –
Intro to AI
CS 531 / CMPE 531 - AI
Course Outline
Description

This course covers the foundations of artificial
intelligence (AI) and intelligent systems.
 first
course in the stream
 provides grounding in knowledge representation, reasoning,
search, machine learning, and intelligent system design
 covers basic complex problem solving techniques in search,
logic, and learning
 introduces AI languages such as Lisp and Prolog
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A lecture, tutorial, and assignment intensive course
 graduate students
will be given additional reading material
and assignment questions
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Goals
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Present a survey of the various concepts and
techniques in AI
Provide understanding of complex problem solving
through logic, search, and learning
Introduce intelligent system design and AI
programming languages
Develop research interest in the theory and
application of AI
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Before Taking This Course…
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Pre-requisites
213 – Data Structures and Algorithms AND
 Junior standing
 NOT recommended to 2010 batch
 CS
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Familiarity
 Probability
 Programming
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These requirements apply equally to both grads and
under-grads
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Grading
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Point distribution
Quizzes (about 6)
Assignments (hand + computer + lab)
Project
Midterm exam
Final exam
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
10%
15%
10%
30%
35%
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Policies (1)
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Quizzes
 Quizzes
may or may not be announced. If a quiz is
announced it will be done 1 to 2 days in advance
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Sharing
 No
copying is allowed for labs/assignments. Discussions are
encouraged; however, you must submit your own work
 Violators can face mark reduction and/or reported to
Disciplinary Committee for action
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Plagiarism
 Do
NOT pass someone else’s work as yours! Write in your
words and cite the reference. This applies to code as well.
 Violators can face mark reduction and/or reported to
Disciplinary Committee for action
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Policies (2)
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Submission policy
 Submissions
are due at the day and time specified
 Late penalties: 1 day = 10%; 2 day late = 20%; not accepted
after 2 days
 An extension will be granted only if there is a need and when
requested several days in advance.
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Rechecking policy
 For
quizzes and labs/assignments: No recheck request will be
entertained after 2 days of return
 For exams: No recheck request will be entertained after
return (requests should be made at the time of collection)
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Project
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Under-grads: Term paper on a (current) topic of interest
Grads: A research project involving implementation
Detailed policies will be provided soon
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Summarized Course Contents
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Introduction and intelligent agents
Blind search
Heuristic search
Adversarial search
Constraint satisfaction problem
Logic and inference
Uncertainty and inference
Concept learning
Intro to natural language processing
AI languages and systems
CS/CMPE 531 - Artificial Intelligence(Au 2007-2008) - Asim Karim @ LUMS
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Course Material
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Required textbook
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Supplementary material
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Artificial Intelligence – A Modern Approach, by Russell
and Norvig, 2nd Edition, Prentice Hall, 2003.
Artificial Intelligence: Structures and Concepts for
Complex Problem Solving, by G. Luger, 4th Edition,
Pearson Education, 2002.
Machine Learning, by T. Mitchell, McGraw-Hill, 1997.
Handouts (as and when necessary)
Other resources
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Books in library
Web
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Course Web Site
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For announcements, lecture slides, handouts,
assignments, quiz solutions, web resources:
http://suraj.lums.edu.pk/~cs531a07/
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The resource page has links to information available on
the Web. It is basically a meta-list for finding further
information.
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Other Stuff
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How to contact me?
 Office
hours: 10.30 to 12.30 MW (office: 429)
 E-mail: [email protected]
 By appointment
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Philosophy
 Knowledge
cannot be taught; it is learned.
 Be excited. That is the best way to learn. I cannot teach
everything in class. Develop a inquisitive mind, ask
questions, and go beyond what is required.
 I don’t believe in strict grading. But… there has to be a way
of rewarding performance.
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Reference Books in LUMS Library
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There are many related books in LUMS library. You
can find them by searching or browsing around call
numbers 006.3.
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