CSCI 4150: Introduction to Artificial Intelligence, Fall 2005

Here are the two midterm exams that I said I would provide. I think of these as more examples of format than of topics.

General information
Time: Mondays and Thursdays, 12:00 – 1:50pm
Location: Darrin 330
Prerequisite: CSCI 2300 Data Structures and Algorithms
Required text: "Artificial Intelligence: a modern approach, Second edition" by Stuart Russell & Peter Norvig, Prentice Hall, 2003. ISBN: 0-13-790395-2.

Teaching staff

If you have a question not suitable for posting to the WebCT discussion boards, send email to aistaff@cs.rpi.edu which will go the instructor and the TA. You will get a faster response this way.

Instructor: Prof. Wes Huang
email: whuang@cs.rpi.edu
Office: Amos Eaton 107
Office hours: T 2-4, W 11-12
TA: Kris Beevers
email: beevek@cs.rpi.edu
Office hours location: Amos Eaton 217
Office hours: W 3-5, F 1-2

Course description

This course is an introduction to the theory and practice of Artificial Intelligence. We will be studying techniques for solving problems and making intelligent decisions. The first half of the course will focus on the foundations of Artificial Intelligence: search and logic. The second half of the course will focus on machine learning techniques, including decision trees, reinforcement learning, and neural networks. Knowledge representation and probability will be addressed in conjunction with several topics during the semester.

Students will implement many of the algorithms we cover in programming assignments. The implementation language for these assignments will be Scheme (a dialect of LISP) which will be taught in the first two weeks of the course. Knowledge of Scheme or LISP is not a prerequisite.

Items on Reserve

The following items are on reserve in the Folsom library:

Assignment web pages

Links