This is an introduction course to artificial intelligence covering fundamental topics in problem solving, heuristic search, knowledge representation, inference, planning, probabilistic reasoning, learning, and natural-language processing.
There will be assigned readings from "Artificial Intelligence: A Modern Approach (3rd Edition)" by Stuart Russell and Peter Norvig. There is a copy on reserve at the library as well.
There will be 1000 points distributed thoughout the course via homeworks, quizzes and projects. There will be no extra credit points.
Important: Contact your instructor, if you have any concerns about your performance in the class.
There will be at least 12 weekly homeworks (through Mimir). The homeworks are intended to be straightforward if you have done the projects and attended the lectures. Only your top 10 homework scores will count toward your final grade; all others will be dropped. The counted scores will each be worth 40 points for a total of 40% of your final grade. Homeworks are always due the Thursday after they are assigned at 10pm. Not submitting your homework on time may result in zero points for that assignment.
There will be multiple projects over the course of the semester, each contributing in total 300 points (30%) to your final grade. Each project will be due at 10pm on the due date. Projects will have two late days each, with a 10% grade penalty for each day late.
Most assignments must be implemented in Python and we strongly recommend that you refresh your Python knowledge if you haven't used the language recently.
During lecture, there will frequently be quizzes each worth 20 points with the top 15 quizzes contributing to your grade (in a similar manner to homeworks). Quizzes in total will account for 300 points (30%) of your final grade. Quizzes are always open book and open note, but no electronics are allowed during the quiz. The duration of the quiz will be at the discretion of the instructor. We guarantee that there will be at least 17 quizzes.
There will be no final exam. There may be a lecture during the final exam timeslot, but it will only cover optional content and would be entirely voluntary attendance.
Those who participate in class provide us with another source of information as to how well they are learning the material, and how much effort they are putting into the course. We can use this information to help counterbalance a difficulty with exams or projects. Let's have an active class! Class participation will never harm your grade; always ask any questions you may have about the material. We strongly encourage students to ask and answer each others questions on Piazza. Although there aren't points associated with participation in this class, providing helpful answers on Piazza or giving constructive criticism on the class can improve your grade. Once initial grades are assigned, participation can boost grades up one step (that is, one-half letter grade or 0.5 on a 4-point scale). If your grade is borderline, we may consider your participation to sway our decision to your advantage.
As a Spartan, I will strive to uphold values of the highest ethical standard. I will practice honesty in my work, foster honesty in my peers, and take pride in knowing that honor in ownership is worth more than grades. I will carry these values beyond my time as a student at Michigan State University, continuing the endeavor to build personal integrity in all that I do.
Plagiarism (unsourced use of other's intellectual property) is not allowed. However, citing and using other's works is generally fine (please ask if uncertain) as long as the material wasn't made specifically for solving assignments for this class. Additionally, the use of material from previous semesters and code from other students in the class are instances of academic dishonesty. Intellectual (non-code) collaboration with other students in the class is allowed, but each student should write (and not share) their own code. If a student submits code that they don't understand, such is also an act of academic dishonesty.
Because a goal of this course is to teach professionalism, any academic dishonesty will be viewed as evidence that this goal has not been achieved, and will be grounds for receiving a final grade of 0.0. Examples of academic dishonesty include (but are not limited to):
See Academic Dishonesty and Attribution for more details.
Depending on circumstances, we may require a code audit of your work, where you meet with an instructor and explain how your code works and how you came up with it.
If their occur unfortunate circumstances that would lead you to have unexpected absences, MSU has a Grief Absence Policy. You need to contact the Associate Dean, and we will make every effort to aid you in continuing the class after we recieve confirmation from the administration.
According to the university, the grade of "incomplete" is reserved for "exceptional cases, where an unanticipated event beyond one's control interferes with a student's completion of course requirements."
Requests for regrading can go in either direction; we are often generous when we first grade something, so please be sure that we did make a mistake before you submit your request. On the other hand, our goal is for you to understand the course material, so we will always be willing to explain to you any portion that you are stuck on. All requests for regrades must come within one week of the return of the graded item. Thereafter, no requests will be considered.
Michigan State University is committed to providing equal opprotunity for participation in all programs, services and activities. Requests for acommodations by persons with disabilities may be made by contacting the Resource Center for Persons with Disabilities at 517-884-RCPD. Once your eligibility for an accommodation has been determined, you will be issued a verified individual services accommodation ("VISA") form. Please present this form to me at the start of the term and/or two weeks prior to the accommodation date (exam, project, etc.). Requests received after this date will be honored whenever possible.
The goal of this class is for you to learn. If you find that anything is coming in your way of that goal, please talk with us about it. We plan to keep the class flexible to the learning styles that seem to work best for the students, so feedback is always appreciated.