CS4341 Introduction to Artificial Intelligence
Syllabus - B 2003
WARNING:
Small changes to this syllabus may be made during the course of the term.
COURSE DESCRIPTION:
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,
and planning.
We will also study three
important application areas in AI: machine learning, machine vision,
and natural language processing. The role of these application
areas in robotics will be discussed.
For the catalog description of this course see the
WPI Undergraduate Catalog.
CLASS MEETING:
Mon, Tu, Th, Fri 10:00 - 10:50 a.m.
Classroom SL104
Please come to class on time and stay for the whole class period.
COURSE OBJECTIVES:
- Learning fundamental principles about and generalizations of
knowledge representation techniques.
Practice with and evaluation of this objective: Projects 1, 2, 3, 4. Exams 1, 2
- Learning fundamental principles about and generalizations of
computational problem solving strategies.
Practice with and evaluation of this objective: Projects 1, 2, 3, 4. Exams 1, 2
- Learning fundamental principles and generalizations
of computational approaches to learning, vision, and natural
language processing.
Practice with and evaluation of this objective: Project 4. Exam 2
- Learning to apply course material (to improve thinking, problem solving,
and decision) during the design, implementation, and analysis of computer programs
that reason and/or act intelligently.
Practice with and evaluation of this objective: Projects 1, 2, 3, 4. Exams 1, 2
- Developing creative capacities
for the design, implementation, and analysis of computer programs
that reason and/or act intelligently.
Practice with and evaluation of this objective: Projects 1, 2, 3, 4. Exams 1, 2
- Learning to analyze and experimentally evaluate
designs and implementations of the intelligent computer programs, in
particular those developed during the course projects.
Practice with and evaluation of this objective: Projects 1, 2, 3, 4.
PROFESSOR:
Prof. Carolina Ruiz
ruiz AT cs.wpi.edu
phone number: (508) 831-5640
Office Hours: Fuller Labs 232
| Mondays | 11:00 | - | 12:00 noon,
|
| Thursdays | 1:00 | - | 2:00 pm,
|
| or by appointment
|
TEACHING ASSISTANTS:
-
Matt Jarvis
Office Hours: Fuller Labs A22
| Mondays | 3:00 | - | 4:00 pm
|
| Tuesdays | 1:00 | - | 2:00 pm
|
| Wednesdays | 4:00 | - | 5:00 pm
|
-
Dharmesh Thakkar
Office Hours: Fuller Labs A22
| Tuesdays | 4:00 | - | 5:00 pm
|
| Wednesdays | 5:00 | - | 6:00 pm
|
| Thursdays | 6:00 | - | 7:00 pm
|
-
Peter Mardziel (Senior Assistant)
Office Hours: Fuller Labs A22
| Wednesdays | 11:00 | - | 12:00 noon
|
| Fridays | 12:00 | - | 1:00 pm
|
Messages sent to cs4341-staff AT cs.wpi.edu reach the professor, the TAs, and the SA.
TEXTBOOK:
RECOMMENDED BACKGROUND:
CS 2136 (Paradigms of Computation) and CS 2223 (Algorithms).
CS 3133 (Foundations of Computer Science) would be helpful, but is not
assumed.
GRADES:
| Exam 1
| 25%
|
| Exam 2
| 25%
|
| Project/Homework 1 | 12.5% (9% for Project 1, and 3.5% for Homework 1)
|
| Project/Homework 2 | 12.5% (10% for Project 2, and 2.5% for Homework 2)
|
| Project/Homework 3 | 12.5% (10% for Project 3, and 2.5% for Homework 3)
|
| Project/Homework 4 | 12.5%
|
| 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.
According to the
WPI Undergraduate Catalog, "Unless otherwise indicated,
WPI courses usually carry credit of 1/3 unit. This level of activity
suggests at least 17 hours of work per week, including class and laboratory
time." Hence,
you are expected to spend at least 13 hours
of work per week on this course outside the classroom.
BS/MS GRADUATE CREDIT
This course may be taken for graduate credit by students in the BS/MS CS program.
Written permission from the CS department and the professor is required.
In order to receive graduate credit, students who have signed up for this program
need to complete the grad-credit additional work included in each project/homework.
EXAMS
Format
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.
Exams will be in-class, 50 minute, closed-book, individual exams.
Collaboration or other outside assistance on exams is not allowed.
Makeups
Regarding makeup exams,
I follow Prof. Gennert's policy:
"Makeup and/or early examinations are not given except under the most
dire of circumstances, and then only with corroborating documentation.
Note well that neither oversleeping, forgetting to show up for an exam,
nor conflicting travel arrangements are considered dire circumstances."
PROJECTS/HOMEWORK
There will be a total of 4 projects/homework.
Code and Documentation
These projects must be implemented using any high level programming language like Java,
Lisp, Prolog, C, and C++.
Code documentation must follow the Departmental Documentation Standard
(see
http://www.cs.wpi.edu/Help/documentation-standard.html).
Teams
Students are expected to organize themselves into groups of exactly 2
for each of the projects/homework.
Submissions and Late Policy
Late projects/hw, with a 25% late penalty, will be accepted
until 12:00 noon of the day after the project is due (if the project is due on a
Friday, then the late deadline is Saturday at 12:00 noon).
ONLY projects submitted using the turnin
system by the deadline
or the late deadline (with the corresponding penalty)
will be accepted. Email submissions will be rejected.
Project Descriptions
More detailed descriptions of the projects/homework 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
references,
the design and all code you use and submit for your projects/homework MUST be
your own original work.
- Project 1
Design, implementation, and experimental evaluation of a search system.
- Project 2
Design, implementation, and experimental evaluation of an AI system that plays a game.
- Project 3
Design, implementation, and experimental evaluation of a planning system.
- Project 4
Design, implementation, and experimental evaluation of a machine learning system.
CLASS PARTICIPATION
Students are expected to read the material assigned to each
class in advance. Class participation will add extra points to
students' grades.
CLASS MAILING LIST
There are two mailing lists for this class:
- messages sent to cs4341-all AT cs.wpi.edu go to the entire class (students, professor, TAs,
and SA), and
- messages sent to cs4341-staff AT cs.wpi.edu go to the professor, the TAs, and the SA only.
CLASS WEB PAGES
The web pages for this class are located at:
http://www.cs.wpi.edu/~cs4341/b03/
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
General AI
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.
- (Additional recommended textbook for this class)
S. Russell, P. Norvig.
"Artificial Intelligence: A Modern Approach" Second Edition.
Prentice Hall, 1995.
ISBN: 0-13-790395-2.
-
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
1990.
-
E. Rich and K. Knight.
"Artificial Intelligence" Second edition
McGraw Hill
1991.
-
P. Norvig
"Paradigms of Artificial Intelligence Programming:
Case Studies in Common Lisp"
Morgan Kaufmann Publishers, 1992.
-
M. Ginsberg
"Essentials of Artificial Intelligence"
Morgan Kaufmann Publishers, 1993.
-
G. F. Luger and W. A. Stubblefield
"Artificial Intelligence
Structures and Strategies for Complex Problem Solving"
Third edition
Addison-Wesley, 1998.
-
M.R. Genesereth and N. Nilsson,
"Logical Foundations of Artificial Intelligence"
Morgan Kaufmann, 1987.
Machine Learning
- Tom M. Mitchell
"Machine Learning"
McGraw-Hill, 1997.
- P. Langley
"Elements of Machine Learning"
Morgan Kauffamann Publishers, Inc.
1996.
Lisp/Prolog Textbooks and Manuals
-
G. L. Steele Jr.
"Common Lisp: The language'' 2nd edition
Digital Press, 1990.
(ISBN 1-55558-041-6)
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: