Topics covered will include search, first-order logic, knowledge representation, planning, probabilistic reasoning, decision theory, learning, and (as time permits) discussion of problems in natural language, & vision. These topics will be covered at the graduate level. In addition, a number of seminal research articles from the primary literature will be reviewed. Prerequisites are a basic understanding of computer science concepts (data structures, complexity, Boolean logic), and the ability to program in a modern programming language such as Java, Lisp, or C++.
Required text: Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig, Prentice Hall, 1995.
Another good text: Artificial Intelligence (second
edition), by Elaine Rich and Kevin Knight, McGraw Hill, 1991.
(This text is more appropriate for the undergraduate, and could be used to catch up on basic concepts that may be covered very quickly in class.)
Finally, I do emphasize writing skills more than one might expect for an ICS class (note the description of the reaction papers, below). You may want to get a text to help you write technical material clearly and correctly. I strongly recommend Lyn Dupre's Bugs in Writing. This is available from amazon.com.
This class will include 15 lectures, one midterm and one final exam, four reaction papers of articles from the primary literature, and one final project. The final project must be a programming project, but will not be graded based on programming style or choice of language. The final project must include both a written report, and a 10-15 minute live demonstration session.
For all details, see the web pages below. Like all good web sites, this information will be updated over time. Changes will be announced in class and via email lists. Keep an eye on these pages!