CSci 4511 section 02, Fall 2021: Syllabus


Time Monday and Wednesday, 1:00-2:15
Room online
Instructor Dr. Maria Gini (
office hours: TBA and by appointment
TAs Charles Broadbent
Benjamin Lilja
Trevor Winger

Class delivery

lectures will be delivered online at the class time. The lectures will be recorded and later posted on canvas. Every Wednesday we will do an in class exercise that will give one participation point. It has to be done during the class. The zoom link for the class is listed under Zoom in the left menu in canvas. Zoom links for office hours will be posted as soon as the office hours are finalized.


Stuart Russell and Peter Norvig, "Artificial Intelligence. A modern approach. 4th Edition" Pearson, 2020. (Chapters 1-12).


You are expected to have knowledge of basic computer science principles and programming; data structures (graphs and trees); and formal logic (propositional and predicate logic). Course Description: The course provides a technical introduction to artificial intelligence (AI). Topics include: agents, search (search spaces and algorithms, game playing, constraint satisfaction), planning, knowledge representation, and an introduction to neural networks. The course is suitable to gain a solid technical background and as a preparation for more advanced work in AI.

Work Load and Grading Policy

Readings: About 30 pages of reading/week from the textbook and occasionally other papers.

Course Requirements

  1. 4 written homeworks (each 6% of the grade -- total 24%). Homeworks will include problem solving and some programming problems. Homeworks are due on Friday at 6:00pm. Late homeworks will lose 10% of the maximum total points for each day they are late. Weekends do not count, so if you submit by 6:00pm on Monday you lose only 10%.
  2. one optional homework that will give extra credit (3% of the grade).
  3. 4 writing assignments (each 4% of the grade -- total 16%). The late homeworks rule applies also to writing assignments. You will be allowed to resubmit writing assignments to get a higher score. Points lost for being late will not be given back.
  4. an in-class exercise every week. Participation will count for 15% of the grade, 1% for each exercise. Done in class each Wednesday in small groups. Need to be submitted to canvas by the evening of Wednesday.
  5. one project (15% of the grade) on a topic of your choice. It can be done in groups of two or three.
Exams: two exams during the semester (30% total).
Look at the class schedule in canvas to see due dates for assignments and exam dates.

Grades will be assigned on the following scale:
93% or above yields an A, 90% to 92.99% an A-, 87% to 89.99% a B+, 83% to 86.99% a B, 80% to 82.99% a B-, 75% to 79.99% a C+, 65% to 74.99% a C, 60% to 64.99 a C-, 55% to 59.99% D+, 50% to 54.99% a D, below 50% an F.

Academic Integrity

All work submitted for this class must represent your own individual effort unless group work is explicitly allowed. Academic integrity and professional behaviors are expected from everyone in the class. You are free to discuss course material with classmates, TAs, and professor, but you should never misrepresent someone else's work as your own. It is your duty to protect your work from unauthorized access. Discussing answers and copying solutions from others in homeworks or exams is cheating and grounds for failing the course. Any student caught cheating will receive an F for the class and the University policies will be followed (see


It is University policy to provide, on a flexible and individualized basis, reasonable accommodations to students who have documented disability conditions (e.g., physical, learning, psychiatric, vision, hearing, or systemic) that may affect their ability to participate in course activities or to meet course requirements. Students with disabilities are encouraged to contact Disability Services for a confidential discussion of their individual need for academic accommodations. Disability Services is located in Suite 180 McNamara Alumni Center, 200 Oak Street. Staff can be reached by calling 612-626-1333 voice or TTY, or on the web at
Copyright: © 2021 by the Regents of the University of Minnesota
Department of Computer Science and Engineering. All rights reserved.
Comments to: Maria Gini
Changes and corrections are in red.