CSC 550: Introduction to Artificial Intelligence
CSC 650: Advanced Artificial Intelligence

Spring 2002

5:00 - 7:45 Tu
411 Old Gymnasium
Dr. David Reed
215 Old Gymnasium      x2583

Text: Artificial Intelligence: Structures and Strategies for Complex Problem Solving (4th ed.),
George F. Luger, Addison-Wesley, 2002.

Course Description

Artificial Intelligence is the subfield of computer science concerned with automating tasks that would require "intelligence" if performed by people. AI is a highly eclectic field, with roots in mathematics, logic, psychology, philosophy, and engineering. The goal of this course is to introduce and survey the field of Artificial Intelligence, paying special attention to foundational concepts and theories. In addition, current trends and approaches in AI research will be studied.

Specific goals for the course are:

Required Work

There will be five to seven homework assignments spread throughout the term. These assignments will cover concepts and problems from class and the readings, and may involve writing and modifying AI programs in Prolog. Assignments are due at the beginning of class on the date specified. Late assignments will receive 75% of full credit if they are handed in within one week of the specified due date. After one week, no credit will be given. In addition, students will be expected to independently research a topic in AI and present that topic to the class. There will be weekly quizzes, a midterm exam and a cumulative final exam (see the schedule below for exam dates).

Students registered for graduate credit (CSC650) will complete additional assignments and/or extensions to existing homeworks to allow more depth of study.

There is no specific attendance policy for the course, although it is expected that absences will leave the student unprepared for tests and assignments. Quizzes and tests will not be rescheduled except in extreme circumstances. However, the lowest quiz grade will be dropped.

Grades will be determined as follows:

homework assignments 35 %
student presentation 10 %
weekly quizzes 05 %
midterm exam 20 %
(cumulative) final exam 30 %

At the minimum, traditional grading cutoffs will apply. That is, 90% is guaranteed an A, 87% is guaranteed a B+, etc. Depending on class performance, some shifting of grades (in an upward direction only) may occur as final letter grades are assigned.

Policy on Collaboration

The college policy on cheating and plagiarism is spelled out in the Student Handbook. In addition to this, the following guidelines hold pertaining to programs. Programs are to be the sole work of the student -- collaboration on the design or coding of a program is not allowed. Students may seek debugging assistance or clarifications on assignments using the class mailing list:

Repeat: All student interactions regarding homework assignments must take place via the class mailing list!

Tentative Schedule

Jan 22
course overview,
AI history
Chapter 1
predicate logic, Prolog
Chapters 2, 14 HW1: due 2/5
Feb 5
Prolog: unification,
resolution, lists
Chapter 14
more Prolog: built-in predicates,
operators, AI example
Chapter 14 HW2: due 2/26
state spaces, uninformed strategies
Chapter 3
constraint-based search
midterm review
HW3: due 3/19
12 *** SPRING BREAK ***
informed strategies
Chapters 4, 5 Class Presentation
optimization problems,
game trees
Chapters 4, 5 HW4: due 4/9
Apr 2
semantic nets, frames
Chapter 6
expert systems, uncertainty
rule-based reasoning
Chapters 7, 8
connectionist models
Chapters 9, 10 HW5: due 4/30
emergent models
genetic algorithms, a-life
Chapter 11
student presentations
course overview
Vision, NLP,
Fuzzy Control
May 7 FINAL EXAM    (Tue 5:00 - 7:45)