Prof. Wes Huang
email: whuang@cs.rpi.edu
Office: Amos Eaton 111
Office hours: Tuesdays 4-6pm (or by appointment)
TA: Arvind Venkatesan
email: venkaa@rpi.edu
Office: Lally 03A (basement)
Office hours: Wednesdays, 2-4pm and Thursdays 9-11am (or by appointment)
undergraduate TA: Adam Goode
email: goodea@rpi.edu
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.
You do not need this text, but some of you may want it as a Scheme introduction and reference. This is an introductory Computer Science text which uses the Scheme programming language. I will be more or less following the order of presentation in this book as I introduce Scheme in class. This text also has the benefit of having numerous examples and exercises.
There are other sources of information on Scheme. In addition to the two books below, I will be putting together some course notes on Scheme, and there are also a few online resources. See the Scheme page for more information.
These books have a fairly high level presentation of the Scheme programming language. I think of them as more suitable for a programming languages class, so I did not make them optional texts for this class. However, some of you may prefer this presentation. I have a copy of both books if you are interested in looking at them.
Hardcopy of current handouts is generally available outside Prof. Huang's office (Amos Eaton 111). Most handouts will also appear here.
