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Announcements, etc
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To begin semester, we will be reading these classic articles
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Grades
Semester Schedule
A preliminary schedule based
on earlier class offererings
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Course Overview
CS724 Surveys major areas of AI including theorem
proving, heuristic search, problem-solving, computer analysis of
scenes, robotics, natural
language understanding, and knowledge-based systems. Prereq. CS
372 or Graduate
standing.
EXPECTED BACKGROUND FOR COURSE
Ability to deal with formal symbolic notations such as FOPC and
mathematics.
Skill in programming and reading programs in more than one
programming
language.
Background in data structures and
formal notations for describing programs, such as BNF grammars.
GOALS
The student will: develop an understanding of
the philosophy of AI and of several AI techniques,
will be able to use the techniques and
could evaluate the appropriateness of using the techniques for a
real
problem.
OBJECTIVES
The student will: be able to solve problems using AI
techniques within the overall AI philosophy,
will be able to develop programs
in LISP, or PROLOG and use other AI programming notations,
will be able to present a case, in English, for using
various AI techniques.
MATERIAL
Readings in addition to the book will be required.
The material will be on reserve in the library under CS724.
Occasionally notices will be posted to the class home page.
You are responsible for checking this information twice a week.
Problem statements, old tests and notes will be available.
General Comments
- You are expected to be here. Come to class -- attendance
will be taken semi-regularly. If you miss class, come and
speak to me. This WILL affect your grade.
- Participate, cooperate, and help others.
- You can expect a substantial amount of outside class effort
for this course.
- This document will change over the course of the semester.
You should check here at least once a week.
- Periodically you might be asked to take a survey or some
other in-class activity. These will not be graded, but they will
be a form of taking attendance.
Required Reading:
The book for the course is:
Artificial Intelligence:
Structrues and Strategies for Complex Problem Solving,
Fourth edition,
Addison-Wesley
by
George Luger
The book's LISP and PROLOG programs, along with additional code
and
other support mattrials, are avaible at:
http://www.ndsu.nodak.edu/instruct/juell/cs724s98/books/luger98
A optional book that can help with the Lisp and Prolog is:
Mueller, Robert A. and Rex L. Page,
Symbolic Computing with LISP and PROLOG,
John Wiley and Sons, New York,
1988.
ISBN: 0-471-60771-1
Relevant Links
Software
Grading
Grades will be assigned according to the customary system:
- A 100%-90%;
- B 89%-80%;
- C 79%-70%;
- D 69%-60%;
- F 59% or less
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Assignments and exams will be scored as follows:
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Policy on Late Assignments
There is no happy way to assign lateness demerits. For the
purposes of this class, it is never too late to turn in work
(until grades are turned in at the end of the semester)
However, the later an assignment is produced, the less it is worth.
Therefore, the policy will be this: late assignments will lose a
letter grade immediately, and then another letter grade after
two weeks.
Special Needs
NDSU Academic Affairs New Course Syllabi Requirement
Any student with disabilities or other special needs, who needs
special accomodations in this course, is invited to share these
concerns or requests with the instructor as soon as possible.
Academic Dishonesty or Misconduct
NDSU Academic Affairs New Course Syllabi Requirement
Work in this course must adhere to the Code of Academic
Responsibility and Conduct as cited in "Rights &
Responsibilities of Community: A Code of Student Conduct" (1993)
pp. 29-30. "The academic community is operated on that basis of
honesty, integrity, and fair play. Occasionally, this trust is
violated when cheating occurs, either inadvertently or
deliberately .....Faculty members may fail the student for the
particular assignment, test, or course involved, or they may
recommend that the student drop the course in question, or these
penalties may be varied with the gravity of the offense and the
circumstances of the particular case."
Academic dishonesty can be divided into four categories and
defined as follows:
- Cheating: Intentionally using or attemping to use
unauthorized materials, information or study aids in any
academic exercise.
- Fabrication: Intentional and unauthorized falsification or
invention of any information or citation in an academic exercise.
- Facilitating academic dishonesty: Intentionally or knowingly
helping or attempting to help another to commit an act of
academic dishonesty.
- Plagiarism: Intentionally or knowingly representing the
words or ideas of another as one's own in any academic exercise.
Would you like to know the
Current Time?
Send comments to:
slator@cs.ndsu.edu
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