Course Description and Pre-requisities
COMP 440 is a foundational course in artificial intelligence, the discpline of
designing intelligent agents. We will learn to design and analyze agents that
do the right thing in the face of limited computational resources and limited
information. The main questions we will study are: how agents decide what to
do, and how they can learn from experience. We will use tools from computer
science, probability theory, neuroscience, psychology, control theory and game
theory to design and analyze agents that plan and learn in task
environments. Along the way, we will cover interesting examples of intelligent
agents including poker playing programs, bots for various games (e.g. WoW),
DS1, the spacecraft that performed an autonomous flyby of Comet Borrely in
2001; Stanley, the Stanford robot car that won the Darpa Grand Challenge in
2005; Mapquest and how it calculates driving directions; face and handwriting
recognizers; Fedex package delivery planners; airline fare prediction sites;
fraud detectors in financial transactions, systems that learn signaling and
regulatory networks in cancer from high-throughput biological data, and more!
The course assumes familiarity with discrete mathematics (COMP 280) and a
facility with algorithms as well as with programming (COMP 210 and COMP
212). COMP 314 is highly recommended. COMP 440 can be taken as part
of a general education in computer science, as a grounding for future research
in AI, or to gain familiarity with recent AI methods for application in other
fields.
Texts and Reading Material
The course textbook is
Artificial Intelligence: A Modern Approach
2nd edition, by Stuart Russell and Peter Norvig published by Prentice
Hall. The textbook is required.
Last modified: 8 August 2007 by
Devika Subramanian
devika@rice.edu