CS 5541 Course Syllabus
Artificial Intelligence
Fall, 2010

Course Information

Instructor:Rich Maclin
Office:315 Heller Hall
Lectures: 15:30-16:45 Tu,Th, HH 216
Lab: 19:00-19:50 W, 177 MWAH
Office Hours: 17:00-18:00 Wednesday, 14:00-15:00 Thursday and by appointment
Text: Russell and Norvig, Artificial Intelligence, 3rd Ed., Prentice Hall, ISBN 0136042597

Catalog Description

Principles and programming methods of artificial intelligence. Knowledge representation methods, state space search strategies, and use of logic for problem solving. Applications chosen from among expert systems, planning, natural language understanding, uncertainty reasoning, machine learning, and robotics. Lectures and labs will utilize suitable high-level languages (e.g., Python or Lisp).


Course Goals

This course introduces the field of artificial intelligence (AI). Students learn about AI methods in machine problem solving (a) through search and reasoning, (b) through learning algorithms (e.g., neural networks), and (c) through algorithms dependent on particular instructors (e.g., robotics related techniques). Students also use a new programming language Python and/or Lisp, and learn to think and write about the issues which dominate the field.

Examinations and Grades

Item Points Date and Time
Midterm Exam 1 175 points October 14 (Thursday), 15:30-16:45
Midterm Exam 2 175 points November 23 (Tuesday), 15:30-16:45
Final Exam 350 points December 17 (Friday), 14:00-15:55
Programming Assignments (3-5) 200 points TBA
Homework Assignments (5) 100 points TBA
Total 1000 points Grade based on total points

Grades are assigned on a percentage basis, and then an adjustment is applied based on a minimum effort requirement (see below). The grade percentage cutoffs are as follows:

These percentages may be lowered but will not be raised.

Minimum Effort Requirement: Students must turn in a minimal credible effort for EVERY assignment or their grade will be reduced one full letter grade (an A would become a B, an A- a B-, a B+ a C+, etc.). A turned-in assignment achieving at least 40% of the possible points (before late assignment penalties) will be considered a minimal credible effort (though this percentage may be revised downwards by the instructor as warranted). For example, if a program has a maximum possible 30 points, then a turned-in assignment achieving at least 12 points before late penalties would be considered a minimal credible effort.


Missed Classes

You are responsible for what goes on in class, including lecture material, handouts, and turning in assignments. If you are unable to attend class it is your responsibility to obtain copies of class notes and any materials distributed in class. You may turn in copies of assignments early or have other members of the class turn in an assignment for you.

Missed Exams

No exam will be given early. Exams can be made up only in the case of emergencies such as severe illness or death in the immediate family. You must contact me 24 hours in advance in order to arrange a makeup.


All assignments will be collected at the beginning of class on the due date. Late assignments will be penalized 20% of the grade for each working day the assignment is late.


Programming assignments must be your own work. You may discuss general ideas with other students, but should not discuss actual code with others. If you are having problems with an assignment, please come and see me or send me email.

Equal Opportunity

As instructor I shall make every attempt to treat all students equally, without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. I encourage you to talk to me about your concerns of equal opportunity in the classroom. To inquire further about the University's policy on equal opportunity, contact the Office of Equal Opportunity (6827) or (6849), 269-273 DAdB.

Students With Disabilities

It is the policy and practice of the University of Minnesota Duluth to create inclusive learning environments for all students, including students with disabilities.  If there are aspects of this course that result in barriers to your inclusion or your ability to meet course requirements – such as time limited exams, inaccessible web content, or the use of non-captioned videos – please notify the instructor as soon as possible.  You are also encouraged to contact the Office of Disability Resources to discuss and arrange reasonable accommodations.   Please call 218-726-6130 or visit the DR website at www.d.umn.edu/access for more information.