CS 5300 / 6300 -- Introduction to Artificial Intelligence
School of Computing
University of Utah

Tuesday, Thursday, 12:25pm - 1:45pm, MEB 2325

3 credits
Basic methods of artificial intelligence, including search, logic, dealing with uncertainty, and learning. Introduction to natural language processing, computer vision, and robotics.
Instructor: 
William B. Thompson
3446 MEB
(801) 585-3302

office hours: after class and by arrangement

TA: Scott Alfeld

Text: Stuart Russel and Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd edition, Prentice Hall, 2002. The text book web page contains many useful links.

Prerequisites:  Good knowledge of basic data structures (lists, queues, trees, graphs, etc.) and reasonable familiarity with how to search these data structures. Coding skills in C or C++ sufficient to write programs of moderate size and complexity involving implementation and use of such data structures. While CS 3505 is listed as a formal prerequisite for the class, it is not in fact necessary to have taken or be taking CS 3505 in order to have the necessary background for CS 5300/6300. Based on what is currently covered in the lower division CS classes, CS 2420 and CS 3500 would be better choices for background material.

Communications:
Class schedule and notes:

Class syllabus, including links to the lecture notes. Lecture slides from Stuart Russell's AI course at Berkeley are also available. If you print copies of the Russell slides, consider using the *-6pp.pdf versions, which have six slides to a page and so will save lots of paper.

Assignments:

Requirements for all assignments.  Read this before you start on any of the assignments!

Assignment #1, due noon, February 12, 2008.
Assignment #2, due noon, March 13, 2008. note changed date!
Assignment #3, due noon, April 8, 2008.

In determining the final grade, exams and assignments will be weighted as follows:
All of the assignments, taken together   50%
midterm exam 20%
final exam 30%

Old exams

Misc. links:

College of Engineering guidelines on appeals, add-drop, and course withdrawal procedures.

AI on the web.

AI demos and projects.

Academic Integrity (aka Don't Cheat!)

Working with others is a good way to learn many complex skills such as programming. In a course like this, however, assignments serve both as learning exercises and as a mechanism to evaluate your performance in the course and it would be unfair to others in the class to base one student's grade on work actually done by someone else.
 
While collaboration with other class members is acceptable in understanding problems or software tools, work turned in for a grade must be your own. You will be given a failing grade for the course if you either turn in material clearly based on work that is not your own or you knowingly supply code or other information to another student that appears as part of his/her submitted material. Turning in code dowloaded from the Web is explicitly disallowed without prior approval from the instructor.  Note that the failing grade is for the full course, not just the particular assignment involved. Note also that you will fail the course if you knowingly supply code or other information to another student, even if you turn in original work for yourself.

When taking a quiz or exam, you must work completely independently of everyone else. Any collaboration here, of course, is cheating.

Turning in work that is not your own is cheating, as is helping someone else to turn in work not their own.  This is a serious violation of academic standards.  Students violating this standard will be failed from the class on the first offense.

Please read The University of Utah Student Code (Sections I-B-2 and V-B in particular) for a detailed description on the University policy on cheating.

Anyone submitting assignments for credit in this class must provide a signed form indicating that they have read and understood this policy.

Students with Disabilities

The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities.  If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD).  CDS will work with you and the instructor to make arrangements for accommodations.
 
All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services.