Artificial Intelligence (CPS 570), Fall 2017
WF 10:05-11:20, LSRC D106
Conitzer (please call me Vince).
Intelligence: A Modern Approach, Stuart Russell and Peter Norvig.
comfortable programming in a general-purpose programming language
some knowledge of algorithmic concepts such as running times of algorithms;
having some rough idea of what NP-hard means
some familiarity with probability (we will go over this
from the beginning but we will cover the basics only briefly)
not scared of mathematics, some background in discrete mathematics, able to
do simple mathematical proofs
If you do not have a standard undergraduate computer science background,
the course may still be appropriate for you, but talk to me first.
Well-prepared undergraduates are certainly welcome.
You do not need to have taken an undergraduate AI course (though of
course it will help if you have).
Midterm exams: 30%
Final exam: 30%
For the homework assignments, you may discuss them with another person, but
you should do your own writeup, programming, etc. This also means that you
should not take extremely detailed notes during your meeting with the other
person; if you can't remember what you talked about, you probably didn't
really understand it...
I have not taught this course for a while so we
will be flexible with the schedule. Each topic will probably take a number
of lectures to finish.
Sometimes, a book chapter will include more information than what we
cover in class; in those cases, for the purpose of exams, you are only
responsible for what we covered in class.
For your convenience there are links to chapters that are available
online (which would be useful if you have an old edition of the book; the
chapter correspondence is here).