The University of Iowa
CS:4420 Artificial Intelligence
Syllabus
Course Description and Goals
The overall goal of this course is to introduce students to a number of topics and techniques in Artificial Intelligence (AI). Students should be prepared to put in considerable time and effort into reading to become familiar with these topics, and into programming to gain experience with these techniques. At the end of the semester, students should have the knowledge required to identify areas they would like to investigate in more depth in related courses. This knowledge includes:
- an introduction to the basic assumptions behind artificial intelligence problem solving;
- exposure to a broad range of AI topics;
- practice translating artificial intelligence concepts into working programs;
- a basic tool-kit of AI algorithms, techniques and representation methods that can be applied to a wide variety of problems.
Lectures
Tue and Thu, 11:00 am - 12:15 pm, 110 MLH
Staff & Office Hours
Instructor
Prof. Cesare Tinelli
1410 SC
(319) 335-0735
cesare-tinelli ^ @ ^ uiowa.edu
Office hours: Mon 3:00 pm - 4:00 pm, Wed 11:00 am - 12:30 pm, Thu 2:00 pm - 3:00 pm and by appointment.
Teaching Assistants
Jeffrey Hajewski
101N MLH
jeffrey-hajewski ^ @ ^ uiowa.edu
Office hours: Tue 9:30 am - 10:30 am, Fri 10:30 am - 12:30 pm, and by appointment.
Prerequisites
CS:3330 with a minimum grade of C-.
Web Sites
Most of the information about the class, including handouts and assignments, will be available from the class web site:
We will also use Piazza, a class discussion service highly catered to getting students help fast and efficiently from classmates as well as the teaching staff:
We will use ICON for homework submissions and grade posting.
Students are expected to check both the class web site and the Piazza discussion board on a regular basis (at least every other day) for announcements regarding the course.
Textbook and Readings
The required textbook is
|
Artificial Intelligence: A Modern Approach (Third edition) by Stuart Russell and Peter Norvig, 2010 |
Additional reading materials will be made available on the course web site as needed.
Topics Outline
The topics that will be covered in the course are outlined below. This outline is tentative and will be adjusted as necessary during the course of the semester. The readings refer to the textbook.
| Topic | Readings |
|---|---|
| Introduction | Chap. 1 |
| Intelligent Agents | Chap. 2 |
| Problem Solving and Search | Chap. 3, 4, 6 |
| Knowledge Representation, Reasoning and Planning | Chap. 7-11 |
| Logical Inference | Chap. 9 |
| Uncertain Knowledge and Reasoning | Chap. 13-15 |
| Learning | Chap. 18, 20, 21 |
Computer Accounts and Software
You may need to use your account on the CS lab machines which will have a working installation of software tools we will use in the course. Instructions on how to access those machines, on-site or remotely, and use the installed software will be provided on the course website.
Although you are welcome to use your own computer for course work, you are responsible for installing any necessary software. We cannot guarantee assistance for any problems with your own installation.
Homework Assignments
Several small written assignments and programming assignments will be given, covering the material from the text and the lectures. All assignments will be collected and graded. They are to be done individually.
Programming assignments will be in OCaml, a modern functional programming language. A few lectures will be spent on the notable features of OCaml and functional programming. However, students are expected to have enough knowledge and practice of programming languages to be able to learn the rest on their own. Pointers to OCaml manuals, handouts and tutorials will be provided on the course web site.
Project
There will be a course project to be done in teams of two-three people consisting in developing an AI application from a list provided by the instructor. Team members will be asked to submit a confidential evaluation of how well they and their teammates performed as team members. Each evaluation will be be incorporated into an individual calculation of the project grade.
Exams
There will be two midterm exams and no final exam. The midterms will be held during class time respectively on February 26 and April 23, 2019.
Grading
The weighting of items in course grade determination will be the following:
| Item | Weight |
|---|---|
| Class attendance and participation | 10% |
| Course Project | 25% |
| Homework | 25% |
| Midterm Exam I | 20% |
| Midterm Exam II | 20% |
The following cutoffs will be used to determine letter grades. In the ranges below, x stands for your total score at the end of the semester. Final scores near a cutoff will be individually considered for the next higher grade. Plus (+) and minus (-) grades will also be given; their cutoffs will be determined at the end of the semester.
| Score | Grade |
|---|---|
| 88 <= x < 100 | A |
| 75 <= x < 88 |
B |
| 60 <= x < 75 | C |
| 50 <= x < 60 | D |
| 00 <= x < 50 | F |
Grades are not curved in this course. It is theoretically possible for everyone in the class to get an A (or an F). Your final grade depends only on your own final score and not on that of others.
Academic Excellence and Workload
The University of Iowa expects students to set high academic standards for themselves and work hard towards achieving them. You can achieve true academic excellence only through dedicated work. An average workload of 6 hours a week besides class attendance should be considered the norm for this course. More effort might be needed depending on your background, predisposition and academic ambition.
Cheating
Academic dishonesty will not be tolerated. In particular, under no circumstances should you pass off someone else's work as your own. This also applies to code or other material that you might find on the Internet.
Homework Assignments:
Sharing solutions of graded homework assignments between students or copying someone else's work,
including posted solutions from previous editions of the course, is not allowed.
Doing that will result in a zero on the assignment
and a report to the CS department's chair and the college.
Students are allowed and encouraged to discuss with other students concepts and ideas that relate to the class and the homework assignments. However, it is important to ensure that these discussions do not lead to the actual exchange of written material.
Course Project: The same policies for homework assignments also apply to the course project but extended to project teams. In addition, all members of a team are responsible for the submitted team work and will be disciplined equally in case of academic dishonesty.
Midterm Exams:
The midterms are individual tests.
Once given the test, each student must be complete it without any help, of any kind, from others. Evidence of external help or of copying or sharing solutions of exam questions may lead to a fail grade. The students involved will be reported to the Department and the College.
If you are unclear about what constitutes academic dishonesty it is your responsibility to contact the instructors or consult the CLAS policy (online version).
Be aware that repeated academic dishonesty offenses lead to suspension or expulsion from the University.
General Course Policies
Communicating with the Instructors:
We welcome questions related to the course.
Students are strongly encouraged to post their class-related questions on Piazza (publicly or privately, as appropriate) rather than emailing questions to the teaching staff.
Questions sent by email will receive lower priority.
We will try to answer all questions posted on Piazza by the end of the following day.
We will occasionally send email announcements to all students in the class.
Recall that you are responsible for all official correspondence sent to your Hawkmail address
(see the general College Policies below).
Assigned Readings: Students are expected to study all the material assigned as required readings, even if that material is not explicitly discussed in class or in the homework assignments.
Additional Readings and Discussions: Students are encouraged to go over any specifically suggested readings and consult any relevant materials beyond those provided on the course's web site. They are also encouraged to discuss the course topics with their classmates. It is a genuinely helpful learning activity having to formulate one's own thoughts about the material well enough to express them to others.
Attendance: Students are expected to attend all classes. Their knowledge and grade depend on it. They are responsible for all announcements and material covered during class even if they did not attend. Up to 5 absences are allowed for any reason.
Extra Credit: No extra-credit assignments or tests will be given on an individual basis (although they may be given to the whole class).
Make-up Exams: Make-up exams will be offered only if there is a serious, documented reason for not being able to take a scheduled exam, and if the request is made at least a week before the exam.
Regrading: Students thinking a graded assignment or test has been misgraded and deserves a regrading are invited to let the instructor know. The instructor welcomes and will give full consideration to all well motivated regrading requests.