The goal of Artificial Intelligence is to build software systems that
behave "intelligently". By this, we mean that the computer systems
"do the right thing" in complex environments--that they act optimally
given the limited information and computational resources available.
This course provides an introduction to artificial intelligence. We
will first study the core topics of knowledge representation,
reasoning, and learning, all from the perspective of probabilistic
methods. Then we will cover several of the "subject areas" of
artificial intelligence where these probabilistic methods are applied
including Natural Language Processing, Perception (primarily vision),
and Robotics.
Prerequisites: CS325; CS381; experience programming in Java
Registration Information: 4 Units. MWF 12:00 Nash 206. CRN 12475
Instructor: Thomas
G. Dietterich
Teaching Assistant: Hongli Deng