CS 371 - Introduction to Artificial Intelligence
Course Information

Course Overview

A most fascinating research field, I like to describe Artificial Intelligence (AI) as the interesting "miscellaneous pile" of computer science.  For example, more expressive, computationally-complex database research finds its home in AI as "knowledge representation and reasoning".  The inverse of computer graphics is machine vision.  Where do you think the object-oriented paradigm reached its maturity?  Many interesting, cutting-edge problems and developments find their birthplace and first home in this ambitious and visionary research community.

Presented with the unifying theme of constructing intelligent software agents, we survey an interesting variety of research problems and modern problem solving techniques.  Among the topics we cover are: search, game-tree search, constraint satisfaction, knowledge representation and reasoning, reasoning under uncertainty,  robotics, and philosophical foundations.


Stuart J. Russell, Peter Norvig
Artificial Intelligence: A Modern Approach
Prentice Hall; ISBN: 0131038052


Todd Neller
Lecture: Glatfelter 203, T,Th 8:30-9:45AM
Office: Glatfelter 209
Office Hours: M-F 10-10:45AM or by appointment. Note:  Generally, feel free to drop in if my office door is open.  If it is closed, I'm desperately seeking to keep on top of things and rabid attack ferrets may drop from the ceiling in my defense.
Phone: 337-6643


80% Assignments
10% Quizzes / Exams
10% Attendance / Participation

You are responsible to know the material from each lecture and reading assignment before the start of the next class.  Homework is due at the beginning of lecture on the due date.  Late homework will not necessarily be accepted.  Source code which does not compile may not receive partial credit.  Class attendance and participation is required.  If you attend all classes and are willing to participate, you'll get 100% for this part of your grade.  Even if you know enough to give a particular lecture, please consider the value of helping your peers during in-class exercises.

Honor Code

Honesty, Integrity, Honor.  These are more important than anything we will cover in this class.  Students can and are encouraged to help each other understand course concepts, but all graded work must be done independently unless otherwise stated.  In group work, great care must be given to "giving credit where credit is due".  For detailed information about the honor code, see http://www.gettysburg.edu/college_life/orgs/honor_code/index.html.