15-780 Graduate Artificial Intelligence Spring 2009

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 decision-making machines. 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.

Prerequisites

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.

Mailing Lists

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.

Textbook

Textbook: Artificial Intelligence: A Modern Approach (2nd ed.), Russell and Norvig.

Grading

Class Participation (10%)
Homeworks (4-5 assignments 45%)
Final project (25%)
"Mid"-term exam: 4/9 (20%)

Homework Policy

Important Note: 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.

Collaboration Policy

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.

Final Project

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 improvements.