Prof. Wes Huang
Office: Amos Eaton 111
Office hours: Wednesdays 4:30-6:00, Thursdays 2:00-4:00, or by appointment
TA: Kris Beevers
Office: Lally 009
Office hours: Mondays 3:00-5:00, Wednesdays 12:00-2:00, or by appointment
TA: Dave Siebecker
Office: Lally 003A
Office hours: Mondays 2:00-4:00, Thursdays 9:00-11:00, or by appointment
Student Class Representatives
The following students volunteered to be class representatives:
I will be meeting with them every other week. The purpose of these meeting is to provide me with feedback on the course. If you wish to provide feedback anonymously, you can do so through the class representatives.
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.
Prerequisite: CSCI 2300 Data Structures and Algorithms. Knowledge of Scheme or LISP is not a prerequisite.
Nuts & bolts