CS4341 Introduction to Artificial Intelligence
Small changes to this syllabus may be made during the course of the term.
Syllabus - C 2000
This is an introductory, upper level, undergraduate AI course.
We will cover general knowledge representation techniques and problem
solving strategies, including semantic nets, search, game playing,
rule-based systems, frames and inheritance, logic-based systems,
planning, and constraint satisfaction.
We will also discuss three
important application areas in AI: machine learning, machine vision,
and natural language processing.
For the catalog description of this course see the
WPI Undergraduate Catalog.
Mon, Tu, Th, Fri 10:00 - 10:50 a.m.
Prof. Carolina Ruiz
Office: FL 232
Phone Number: (508) 831-5640
| Mon. || 2:30 || - || 3:30 pm
| Th. || 3:00 || - || 4:00 pm, or by appointment
Room: FL A20
| Tu. || 9:00 || - || 10:00 am
| Wed. || 10:00 || - || 11:00 am
| Th. || 11:00 || - || 12:00 noon
Room: FL A20
| Mon. || 11:00 || - || 12:00 noon
| Tu. || 1:30 || - || 2:30 pm
| Fr. || 12:00 || - || 1:00 pm
Messages sent to email@example.com reach both the instructor and the
Patrick H. Winston
"Artificial Intelligence". 3rd edition
Addison Wesley, 1993.
CS 2136 (Paradigms of Computation) and CS 2223 (Algorithms).
CS 3133 (Foundations of Computer Science) would be helpful, but is not
| Exam 1
| Exam 2
| Homework || 20%
| Project 1 || 15%
| Project 2 || 15%
| Class Participation and Pop Quizzes
|| Extra Points
Your final grade will reflect your own work and achievements
during the course. Any type of cheating will be penalized
with an NR grade for the course and will be reported to the WPI Judicial Board
in accordance with the
Academic Honesty Policy.
There will be a total of 2 exams. Each exam will cover the
material presented in class since the beginning of the term.
In particular, the final exam is cumulative.
The midterm exam is scheduled for Friday, Feb. 4
and the final exam is scheduled for Tuesday, Feb. 29.
Both will be in-class exams.
Collaboration or other outside assistance on exams is not allowed.
There will be a total of 4 homework assignments.
Solutions to the homework will be made available soon after
homework is collected,
so no late homework will be accepted.
You are encouraged to discuss the homework with your classmates,
but you should develop and write your own solutions.
You should explicitly
acknowledge any sources of ideas used that are not your own; this
includes books, web pages, etc. Failure to identify
non-original work is considered academic dishonesty.
There will be a total of 2 projects.
These projects may be implemented using any high level programming
language (Lisp, Prolog, C, C++, ...).
Students are expected to organize themselves into groups of 3 for each
of the term projects.
Groups need not be the same for both projects.
Code documentation must follow the Departmental Documentation Standard
More detailed descriptions of the projects will be posted to the course webpage
at the appropriate times during the term.
Although you may find similar programs/systems available online or in the
the design and all code you use and submit for your projects MUST be
your own original work.
Design and implementation of a computer program that plays tic-tac-toe.
Design and implementation of a learning system using:
- decision trees; AND
- neural networks and the error back propagation procedure.
Pop quizzes may be given during the term. Be prepared!
Students are expected to read the material assigned to each
class in advance. Class participation will add extra points to
CLASS MAILING LIST
There are two mailing lists for this class: firstname.lastname@example.org and
- messages sent to email@example.com go to the entire class (professor, TAs,
and students), and
- messages sent to firstname.lastname@example.org go to the professor and the TAs only.
CLASS WEB PAGES
The web pages for this class are located at:
Announcements will be posted on the web pages and/or
the class mailing list, and so you are urged to check your email and
the class web pages frequently.
ADDITIONAL SUGGESTED REFERENCES
The following additional references complement and/or supplement
the material contained in the required textbook. I have listed
them in decreasing order of interest according to my preferences.
In particular, the first one listed is my favorite one.
S. Russell, P. Norvig. "Artificial Intelligence:
A Modern Approach". Prentice Hall, 1995.
T. Dean, J. Allen, Y. Aloimonos.
"Artificial Intelligence: Theory and Practice"
The Benjamin/Cummings Publishing Company, Inc. 1995.
B. L. Webber, N. J. Nilsson, eds.
"Readings in Artificial Intelligence"
Tioga Publishing Company, 1981.
S. L. Tanimoto.
"The Elements of Artificial Intelligence
Using Common Lisp"
Computer Science Press
E. Rich and K. Knight.
"Artificial Intelligence" Second edition
"Paradigms of Artificial Intelligence Programming:
Case Studies in Common Lisp"
Morgan Kaufmann Publishers, 1992.
"Essentials of Artificial Intelligence"
Morgan Kaufmann Publishers, 1993.
G. F. Luger and W. A. Stubblefield
Structures and Strategies for Complex Problem Solving"
M.R. Genesereth and N. Nilsson,
"Logical Foundations of Artificial Intelligence"
Morgan Kaufmann, 1987.
- Tom M. Mitchell
- P. Langley
"Elements of Machine Learning"
Morgan Kauffamann Publishers, Inc.
Lisp/Prolog Textbooks and Manuals
G. L. Steele Jr.
"Common Lisp: The language'' 2nd edition
Digital Press, 1990.
This reference is online.
Patrick H. Winston and Berthold K.P. Horn "Lisp" 3rd edition.
L. Sterling, E. Shapiro "The Art of Prolog" MIT Press, 1986.
OTHER AI RESOURCES ONLINE: