Class Lectures: Tuesdays and Thursdays 10:30-11:50am
in 4623 Wean Hall
This course is targeted at graduate students who want to learn about
and perform current-day research
in artificial intelligence---the discipline of designing intelligent
Techniques from probability, statistics, game theory, algorithms,
operations research and optimal control are increasingly important
tools for improving the intelligence and autonomy of machines,
whether those machines are robots surveying Antarctica, schedulers
moving billions of dollars of inventory, spacecraft deciding which
experiments to perform, or vehicles negotiating for lanes on the
freeway. This AI course is a review of a selected set of these tools.
The course will cover the ideas underlying these tools, their
implementation, and how to use them or extend them in your research.
Students entering the class should have a pre-existing working
knowledge of linear algebra, calculus, algorithms and data structures,
and basic knowledge of computational complexity though the class
has been designed to allow students with a strong numerate background
to catch up and fully participate.
Students should also be able to program in C, C++, or Java.
- Class announcements will be broadcasted using a group email list:
- For changes (incl. additions or removal) to your membership in the
course list, please make changes directly via the
list administration page.
- Class Participation (10%)
- Homeworks (4-5 assignments 45%)
- Final project (25%)
- "Mid"-term exam: 4/9 (20%)
Since this is a graduate class, we expect students to want to
learn and not google for answers. The purpose of problem sets in this
class is to help you think about the material, not just give us the
right answers. If
you happen to use any material other than that in the text book or from the lectures, it must be acknowledged clearly
with a citation on the submitted solution.
Homeworks will be done individually: each student must hand in their
own answers. In addition, each student must write their own code in
the programming part of the assignment. It is acceptable, however, for
students to collaborate in figuring out answers and helping each other
solve the problems. We will be assuming that, as participants in a
graduate course, you will be taking the responsibility to make sure
you personally understand the solution to any work arising from such
collaboration. In preparing your own writeup, you should not refer to
any written materials from a joint study session. You also must
indicate on each homework with whom you collaborated.
Late Homework Policy
Homeworks are due at the begining of class, unless otherwise specified.
Students will be allowed 3 total late days without penalty for the entire
semester. For instance, you may be late by 1 day on three different
homeworks or late by 3 days on one homework. Each late day
corresponds to 24 hours or part thereof. These late days are intended to
account for all situations that would ordinarily require special arrangements:
medical problems, conference trips, holidays, etc. So, do not simply use
all of your late days on the first assignment and then ask for more if
you need to go to a conference later. It is your responsibility to make
arrangements for turning the assignment in late, and not all turn-in times
may be available: e.g., do not expect to find us in our offices on a
Sunday at 9:30AM. Once those days are used,
you will be penalized according to the policy below:
Homework is worth full credit at the beginning of class on the due date.
- It is worth up to 75% for 24 more hours.
- It is worth up to 50% for the next 24 hours.
- It is worth 0% after that.
You must turn in all of the homeworks, even if for zero credit,
in order to pass the course.
Turn in all late homework assignments to Michelle (Wean Hall 4619) or Marilyn
(Wean Hall 7106)
Homework Regrading Policy
If you feel that we have made an error in grading your homework,
please turn in your homework with a written explanation to Michelle or Marilyn, and
we will consider your request. Please note that regrading of a
homework may cause your grade to go up or down.
Project proposal due date 2/24 (0% of project grade)
Graded milestone 1 due date 4/14 (10% of project grade)
Graded milestone 2 due date 4/28 (15% of project grade)
Poster session date TBD during exam period (35%
of project grade)
Paper due date TBD during exam period (40% of project grade)
Note to people outside CMU
Feel free to use the slides and materials
available online here. If you use our slides, an appropriate
attribution is requested.
Please email the instructors with any corrections or