This course provides an introductory survey of concepts and techniques in artificial intelligence. We will cover methods for search, classification, reasoning, and machine learning. We will also look at applications including core AI (games, planning), robotics, computer vision, and natural language understanding.
This course assumes that you have taken data structures (CS 225) and therefore, by transitivity, Discrete Structures and Calculus I. A probability and/or statistics course (e.g. CS 361) is strongly recommended.
Lectures are 9-9:50 MWF in 1002 ECE. Videos should be available (see tab above).
The textbook is Russell and Norvig, Artificial Intelligence: A Modern Approach, third edition. The bookstore has the hardbound (aka US) edition. The paperback version on Amazon (aka the international edition) should also be fine. There is a copy on reserve in Grainger library.
You will also need references for Python, which we will use to write the MPs. A good place to start is the the Python Tutorial (also available in hardcopy form).
As long as we have enough seats, it's ok for non-registered students to sit in on lectures. You can (obviously) also do MPs on your own. However, non-registered students may not take the exams or submit work (e.g. MPs) for grading.
We will not let students add the class after add date (10 day of classes). After that date, do not attend and do work in the hope that a free seat may appear.
The gradebook will be stored on moodle. We'll use piazza for electronic discussions. If you have some reason why you don't want to let piazza know your illinois.edu, contact Margaret for help registering under an alternate email address.
Details of electronic MP submission are still TBD. (This will probably use moodle.) github).
We will probably be using gradescope to grade exams.
There will be about 7 MPs, 2 in-class midterms, and a final. Students taking the course for 4sh will also have to do a literature review paper. Longer/harder MPs may be given more weight in computing your homework average. Some bonus credit may be available on the MPs, but your grade on any individual MP may not exceed 110%.
Grading Formula (3sh)
Grading Formula (4sh)
The translation into letter grades will be at least as generous as the standard high school scale (e.g. 70% is a C-, 80% is a B-, 90% is an A-). Any necessary curving may be done differently for the 3sh and 4sh students.
Regrade requests must be submitted within a week after the grade and feedback comments have been released. Course staff reserves the right to regrade not only the items questioned by the student, but also the entire assignment or test. This may result in your overall score actually going down!
You are encouraged to discuss assignments with other students, both to share high-level understanding of the design (e.g. how is a perceptron supposed to work?) or basic utilities (e.g. how do I open a file in Python?). Howver, coding and writing of reports/papers must be done individually or by a team submitting as a group. You are also encouraged to conduct this discussion online, but do not post code on the class discussion group.
You may look for tips, copy code, or use packages, from external sources. However, this must be explicitly acknowledged in your report and your code comments. Be aware that these MPs are intended to be built largely from scratch, so your grade will be reduced if these external aides make the assignment significantly easier.
It is an academic integrity offense to deliberately or negligently copy from other students (outside your team), assist other students in copying from you, or use external sources without acknowledgement. It is also an academic integrity offense if your written report significantly misrepresents what your code actually does. See the student code for other types of actions that would be considered violations.
The standard penalty for an academic integrity violation is a zero on the assignment or exam in question. (This assumes an action of some significance rather than a minor technical mistake or misunderstanding.) A second offense will cause you to fail the entire course.
Assignments submitted as a team must include a statement about who was responsible for which parts of the work. It is in your interest to make sure these statements are accurate, because they will help us determine responsibility if we find an academic integrity violation. If we can determine that some members of a team were not involved, they will be graded as if their teammate had not plagiarised their part.
If your teammate is not doing their share, you have worries about their honesty, you don't agree with the submitted statement about division of work, or your team has become disfunctional in some other way, please contact the instructor promptly.
We expect that you can arrange your work so that minor problems (e.g. a short virus, planned travel) do not stop you from meeting the deadlines. We will make special arrangements for serious extenuating circumstances and minor ones that are awkwardly timed (e.g. virus or travel on the day of an exam). However, you must inform the instructor and respond to rescheduling emails in a timely manner. The meaning of "timely" depends on the circumstances. For example, planned travel should be reported a couple weeks in advance, but there might be unavoidable delays informing us about a serious injury.
For major and extended problems, we expect you to be in contact with the Dean of Students office. They can help document the problem, help you stay in contact with instructors, and determine if you need accommodations such as incompletes.
Makeup exams will be held at the class time, during the week following the regular sitting. I.e. you'll need to use the lecture videos to get caught up. Details will be circulated when you inform us about your reason for missing the exam. Ad-hoc makeup times will be arranged only in rare cases (e.g. extended illness).
If you miss the regular sitting of an exam without a good excuse, contact the instructor about the makeup exam. Your exam score will be reduced by one letter grade (10%).