Richard S. Sutton
Professor and iCORE
chair
Department of Computing Science
University of Alberta
2-21 Athabasca Hall
Edmonton, Alberta
Canada T6G 2E8
office 3-13 Athabasca Hall 780-492-4584
cell 780-270-8139 fax 780-492-1111
email sutton@cs.ualberta.ca
or rich@richsutton.com
ichat/aol
name
rssutton@mac.com (do not use this for an email address)
This site is mirrored at http://incompleteideas.net/sutton
and http://www.cs.ualberta.ca/~sutton
- Research
- Brief biography, CV
- Publications
- Talks
- Reinforcement Learning: An
Introduction (textbook)
- RL FAQ - Frequently asked questions
about reinforcement learning
- my
schedule/calendar
- New photos, Photos, older photos
- CMPUT
609 - Reinforcement
Learning for Artificial Intelligence (Winter 2012)
- CMPUT
325 - Non-procedural Programming Languages (Fall 2006)
- CMPUT 607
- Reinforcement
Learning in Practice (Winter 2005)
- CMPUT
366 - Intelligent Systems (Introduction to AI)
- Incomplete Ideas (a sort of blog)
- Software
- Favorite causes: IJ,
Downsize DC, Technoserve, Drug Policy Alliance, AntiWar, Ron Paul, Not in Our Name
- Ron Paul for
President,
wouldn't that be wonderful
- Political ideas
I am seeking to identify general
computational
principles underlying what
we mean by intelligence and goal-directed behavior. I start with the
interaction between the intelligent agent and its environment.
Goals, choices, and
sources of information are all defined in terms of this interaction. In
some sense it is the
only thing that is real, and from it all our sense of the world is
created. How is this done? How can interaction lead to better behavior,
better perception, better models of the world? What
are the computational issues in doing this efficiently and in realtime?
These are the sort of
questions that I ask in trying to understand what it means to be
intelligent, to predict and
influence the world, to learn, perceive, act, and think.