CPS 271 - SPRING 1999

CPS271
	Spring 1999		Numeric Artificial Intelligence

[ Background | Grading | Schedule | Projects ]

Background

We will cover some advanced topics in artificial intelligence from the "numeric" perspective: constraint satisfaction, combinatorial optimization, function approximation, probabilistic inference, and control. Topics will be mostly disjoint from those of CPS270, so students that have taken CPS270 are welcome to take this class as well.

Instructor

Michael L. Littman

Office: D209 LSRC
Phone: 660-6537
Email: mlittman@cs.duke.edu
Office hours: by request

Meeting Times

TTh 3:50-5:05pm D106

Textbook

Stuart Russell and Peter Norvig. (1995). Artificial Intelligence: A Modern Approach. Prentice-Hall, Englewood Cliffs, New Jersey. (book home page)

Prerequisites

I will assume that students are familiar with programming (any language), algorithm analysis (big O notation and the like at the level of CPS130), and simple calculus (partial derivatives).

Grading

Class grade will be based on:

written homework assignments (10%),
programming projects (30%),
two in-class exams (20% each), and
a final exam (20%).

Last modified: Tue Jan 12 13:04:37 EST 1999 by Michael Littman, mlittman@cs.duke.edu