CS 475 - Artificial Intelligence I
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Objectives: Understanding
what AI is all about (at a introductory level) and getting familiar with
key concepts of AI (as many as time allows) are the two main objectives
of this introductory course.
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Prerequisite:
At least a C in MATH 370 and CS 372.
Good mathematical logic background and
good programming skill in any language,
especially in PROLOG, will be an assert.
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Textbook: "Computational Intelligence - A Logical Approach" by
David Poole, Alan Mackworth, and Randy Goebel, Oxford University Press, 1998.
ISBN 0-19-510270-3. The book will be used extensively during
the course. The website of the book is
http://www.cs.ubc.ca/spider/poole/ci.html. You can find slides,
tools, codes for examples from the book at this URL.
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Class: SH 113; 3:30 pm - 4:45 pm, Mon. and Fri. Final on
May 5, 2001, 3:30 pm - 5:30 pm
The class web site is at:
http://www.cs.nmsu.edu/~tson/classes/spring03-475
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Instructor:
Son Cao Tran, Ph.D
Office: SH 155, Tel. 646-1930
Email: tson@cs.nmsu.edu
Office hours: 3:00 pm - 4:00 am, Tue. and Thus. (or by appointment)
Questions can be sent to me via email but not preferred.
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TA:
Tu Phan
SH 128, Phone: 646-6232
Email: tphan@cs.nmsu.edu
Office hours: 4:00 pm - 5:00 pm, Tue. and Thus.
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Other sources:
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"Logical Foundation of AI" by Michael R. Genesereth and Nils J. Nilsson,
Morgan Kaufmann
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"AI - A Modern Approach" by Stuart J. Russel and Peter
Norvig (Prentice Hall, 1997).
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"Artificial Intelligence - A New Synthesis" by Nils J. Nilsson, Morgan
Kaufman
Class Policy
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Students are strongly encouraged to attend class since material covered
in class and not present in the textbook will be used in the tests
and homeworks. Withdrawing must be done on time, in accordance with the
university calendar.
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The grade of I (incomplete) may be given only if you are unable to complete
the course due to documented circumstances beyond your control that develop
after the last day to withdraw from the course. Appropriate circumstances
include illness and death or crisis in your immediate family. Consult
the university catalog for regulations regarding the I grade. In no case
will an I grade be assigned to avoid a grade of D or F in the course.
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If you elect to be graded under the S/U option, you must declare your intention
when registering for the course. All work in the class will be graded
in a manner identical to that for students choosing the letter grade
option. At the end of the semester, your final letter grade in the course
will be used to assign either a S or an U. You must achieve a minimum grade
of C in order to receive a grade of S.
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It is expected that students follow the code of conduct stated
in the University
Student Handbook. Any violations of the code will result in a grade of
F for the course, in addition to any further sanctions imposed by the university.
Unless explicitly stated by the instructor, you are assumed to perform
the assigned work by yourself, without any external collaboration. Note
that a person copying an assignment is guilty of a violation of academic
conduct, as is the person from whom the assignment was copied.
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If you have or believe you have a disability and would benefit from accommodations,
you may wish to self-identify. You can do so by providing documentation
to the Office for Services for Students with Disabilities (SSD), located
at Garcia Annex Room 102 (phone: 646-6840, TTY 646-1918). If you are already
registered with the SSD Office and need accommodations please provide your
"Accommodations Memo" from the SSD Office within the first two weeks of
class. If you have a condition which may affect your ability to exit
safely from the premises in an emergency or which may cause an emergency
during class, you are encouraged to discuss this in confidence with the
instructor and/or the Coordinator for SSD. Feel free to call Ms. Elva G.
Telles, EEO/ADA & Employee Relations Director at 646-3333 with any
questions about the Americans with Disabilities Act (ADA) and/or
Section 504 of the Rehabilitation Act of 1973. All medical information
will be held in strict confidence.
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Grade: Computed based on the standard scale of 100 points
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90% up
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A
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80% - 89%
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B
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70%v-79%
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C
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< 70%
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D
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with the following distribution:
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three tests (two midterm and one final exam) (25% each),
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homework assignments and projects (25%)
Homework has to be submitted using the class submission website
on the dateline unless otherwise noticed. Late homework will be
deducted 10% (of the total)
for each day late. After 4 days, no submission will be graded.
- Syllabus: tentative.
We will follow the one semester (12-modules) of the book with the
emphasis on knowledge representation and reasoning techniques and planning
techniques. If time allows reading materials may be added. Likewise, some
will be removed if time is insufficient. The 12 modules are:
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Module 1: AI, Agents and Intelligence
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Module 2: Symbols and Semantics.
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Module 3: Reasoning with Symbols.
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Module 4: Search, blind and heuristic.
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Module 5: Search issues: loops, directions,
space/time tradeoffs, dynamic programming.
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Module 6: Constraint satisfaction.
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Module 7: Knowledge representation issues.
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Module 8: Metainterpreters.
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Module 9: Action representations.
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Module 10: Planning.
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Module 11: Learning: decision trees.
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Module 12: Learning: neural networks.
Last modified: Fri Jan 24 12:54:03 MST 2003