AI CS 5300/6300 Course Information

This course will introduce the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis will be on the statistical and decision-theoretic modeling paradigm, with applications ranging from diagnosis to game-playing to robotics. This course is built around several multi-part programming projects, based on the game of Pacman.

Coursework will consist of two kinds of assignments. Programming projects will be in Python. Programming projects may be done in teams of two or three. (Because ugs and grads are graded on different scales, the teams should be uniformly all ugs or all grads.) Written homeworks will be in the form of mini-assignments given most weeks. You should be prepared to do regular work each week to keep up with the material and the assignments.

Prerequisites: CS 3505 (prior programming experience is expected; although we don't expect that you know Python, we do expect you to be able to pick it up rapidly). NOTE: This course has substantial elements of both programming and mathematics, because these elements are central to modern AI. Prerequisites also include CS 3130 Engineering Probability and Statistics and CS 4150 Algorithms.

Expectations: You are expected to come to class prepared by reading the assigned sections of the book ahead of time.

 Textbook

The official textbook for this course is:

Artificial Intelligence: A Modern Approach (Third Edition)
by Stuart Russell and Peter Norvig. Prentice Hall, 2009.

Be sure you have the Third Edition. It is BLUE, not GREEN or BURGUNDY: the other editions are not sufficient.

We will also occasionally have readings from:

Reinforcement Learning: An Introduction
by Richard S. Sutton and Andrew G. Barto. MIT Press, 1998.

This book is available online.


 Grading

Overall grades will be determined from: Homeworks must be turned in on paper before the start of class on the listed due date. Projects must be turned in electronically by midnight on the listed due date. Assignments may be turned in up to two days late. A penalty of 10% per day will be assessed. The weekend counts as one day. There is a moratorium on complaints about grading, etc., of one week.


 Course Policies

Cheating: Any assignment or exam that is handed in must be your own work. However, talking with one another to understand the material better is encouraged. Recognizing the distinction between cheating and cooperation is very important. If you copy someone else's solution, you are cheating. If you let someone else copy your solution, you are cheating. If someone dictates a solution to you, you are cheating. Everything you hand in must be in your own words, and based on your own understanding of the solution. If someone helps you understand the problem during a high-level discussion, you are not cheating. Any student who is caught cheating will be given an E in the course and referred to the University Student Behavior Committee. Please don't take that chance - if you're having trouble understanding the material, please let us know and we will be more than happy to help.

ADA: The University of Utah conforms to all standards of the Americans with Disabilities Act (ADA). If you wish to qualify for exemptions under this act, notify the Center for Disabled Students Services, 160 Union.

College guidelines: Document concerning adding, dropping, etc. here.