CSci 4511w, Spring 2019: Syllabus

Time/Room: Tuesday and Thursday 4:00pm to 5:15pm in Amundson Hall B75
Dr. Maria Gini (gini at
office hours: Wed 10:30 to 11:30, Thursday 11:00 to 12:00 in Shepherd Lab 245 (612) 625-5582.
Address: 4-192 Keller, 200 Union St. SE, Mpls, MN 55455
TAs: Carter Blum , Wed 1:30-2:30pm and Fri 11:30-12:30 in Keller 2-209
Yan Luo , office hour Tue 9:30-10:30 in Keller 2-246
Myat Mo , office hour Tue 2:30-3:30pm in Keller 2-209
Nivetha Ramakrishnan , office hours Wed 2:00-3:00pm in Keller 2-246
Yingxue Zhou , office hours Mon 2:45-4:45pm in Keller 2-246

Textbook: Stuart Russell and Peter Norvig "Artificial Intelligence. A modern approach. 3rd Edition", Prentice-Hall, 2010. ISBN: 9780136042594 (Chapters 1-12). The software from the textbook is at You can also download the lisp software from and the python software from We will use it for some homeworks.

All class material will be posted in canvas and on the class page at We will use canvas to submit homework, for grades, and for the class forum.

Prerequisites: 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: This course provides a technical introduction to fundamental concepts of artificial intelligence (AI). Topics include: history of AI, agents, search (search spaces, uninformed/informed search, game playing, constraint satisfaction), planning, and knowledge representation (ontologies). 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:

  1. Readings: Approximatively 30 pages of reading/week from the texbook and occasionally other papers.
  2. Participation: There will be an in-class exercise every week when there is no exam. Participation will count for 12% of the grade.
  3. Assignments:
  4. Exams (open book and notes):
Grades will be assigned on the following scale: 93% or above yields an A, 90% an A-, 87% a B+, 83% a B, 80% a B-, 75% a C+, 65% a C, 60% a C-, 55% a D+, 50% a D, below 50% an F.

Tentative Class Schedule (subject to changes)
Date Ch Topics Assignments AIMA Slides
Week 1 -   Jan 22, 24 1-2 Intro, intelligent agents Chapter 2
Week 2 -   Jan 29, 31 3 Problem solving and search Chapter 3
Week 3 - Feb 5, 7 3-4 Search and heuristic search Homework 1 due (Thu Feb 7) Chapter 4.1-2
Week 4 - Feb 12, 14 4 Other search algorithms Writing 1 due (Thu Feb 14) Chapter 4
Week 5 - Feb 19, 21 5 Game playing Homework 2 due (Thu Feb 21) (Old) Chapter 6
Week 6 - Feb 26, 28 6 Constraint satisfaction. Writing 2 due (Thu Feb 28) (Old) Chapter 5
Week 7 - Mar 5, 7 First midterm exam (March 7)
Week 8 - Mar 12, 14 7 Propositional logic Homework 3 due (Thu Mar 14) Chapter 7
Week 9 - Mar 26, 28 8-9 First-order logic and resolution Writing 3 due (Thu Mar 28) Chapter 8
Week 10 - Apr 2, 4 9 Planning Homework 4 due (Thu Apr 4) Chapter 9
Week 11 - Apr 9, 11 10 Planning Second midterm exam (moved to Apr 16) (Old) Chapter 11
Week 12 - Apr 16, 18 Neural networks and deep learning Writing 4 due (Thu Apr 18)
Week 13 - Apr 23, 25 Neural networks and deep learning Extra homework 5 due (Thu Apr 25) Neural Nets
Week 14 - Apr 30, May 2 20 Knowledge representation Project report due (May 2)
Final exam: Thursday May 9, 4:00pm-6:00pm

Academic Integrity: All work submitted for the class must represent individual effort unless group work is explicitly allowed. 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 responsibility to protect your work from unauthorized access. Discussing answers to problems and copying solutions from others in homeworks or exams is considered cheating and grounds for failing the course. Any student caught cheating will receive an F as a class grade and the University policies will be followed (see

Copyright: © 2019 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.