CSE 573, 24au: Introduction to AI

Mon and Wed, 1:30-2:50 in ECE 003

Schedule

(subject to change)

Wk. Dates Lecture slides Reading (optional reading)
1 Sep 25 Introduction; Agents R&N, 1,2,3.1
2 Sep 30; Oct 2 Search; Informed Search R&N 3.2-end, 5.1-5.2; Search tool
3 Oct 7,9 Informed Search (cont.); Adversarial Search R&N 5.3-5.5, (4)
4 Oct 14, 16 ExpectiMax; Markov Decision Processes (MDPs) R&N 17.1-17.3, (S&B 4.3-4.4)
5 Oct 21, 33 Reinforcement Learning R&N 22.1-22.5, (S&B 5.1-5.5)
6 Oct 28, 30 RL (cont.); Uncertainty R&N 12, 13.1-13.3 (MIT notes), R&N 15.1-15.3
7 Nov 4, 6 Hidden Markov Models R&N 15.1-15.3
8 Nov 13 (Nov 11 holiday) Bayesian Networks (BNs) R&N 14.1-14.3
9 Nov 18, 20 BN (cont); Inference in BNs R&N 14.4-14.5
10 Nov 25 (Nov 27 canceled) BN Inference (cont) R&N 18.1-18.2; 20.1-20.2
11 Dec 2, 4 Machine Learning R&N 18.1-18.2; 20.1-20.2

Communication and Office Hours

The staff is available to help you in a number of different ways. Please consider asking any questions first on the Ed forum, so that others can also benefit from the shared responses. We will try to schedule office hours to accommodate students' schedules and will offer some office hours virtually. If you're still not able to make this time, please reach out to us on Ed.

We also have office hours in a number of different times and locations.

Assignments

Programming Projects

Individual assignments graded on correctness and due by 11:59pm on the day listed. Worth 33% of grade total.

Projects (PR) Total Points Due
0: Warm-up N/A Not graded
1: Search 25 Fri, Oct 18
2: Multi-Agent Search 25 Wed, Oct 30
3: Reinforcement Learning 25 Wed, Nov 13
4: Inference and Filtering 25 Wed, Nov 27

Written Assignment

We will have one written assignment / takehome exam that will be due Th Dec 5th. Worth 33% of grade total. You may handwrite and scan the homework if you would like, but the answers must be clearly visible (i.e., pencil may not work).

Homeworks (HW) Due
Written Assignment Thu, Dec 5

Final Project

We will also have a final project that can incorporate aspects of your research or do a small project of your own design that is related to course content. More details on the project are avialable here. Note two dues dates:
  • Project Proposal Due Fri Nov 16. Send Luke a short email or Ed post describing your proposed project as soon as you have an idea, but definitely before the end of day on Friday, Nov. 16th. Please come to office hours, or contact us if you need help deciding on a topic.
  • Project Report Due Thu Dec 12. Your write up should be about 4 pages maximum (not including references) in Camera-ready NeurIPS format. You may have unlimited appendices for clarifications, however, your main content should appear in the 4-page limit.
Projects can be done in a group of one to two students. We encourage you to work on projects that are close to your interests.

Policies

Submitting

  • All work will be turned in electronically.
  • Assignments should be done individually unless otherwise specified. You may discuss the subject matter with other students in the class, but all final answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course, pertinent to the Allen School's policy on academic misconduct.
  • Each student has six penalty-free late days for the whole quarter. Consecutive days off (weekends or holidays) count as one late day. Other than that, any late submission will be penalized at 20 percent of the submitted grade per day (weekends count as one day). (This should incentive you to attempt the assignments even if you submit them quite late).
  • The maximum late days that can be used per assignment is four.
  • You must link pages to questions for written assignments submitted to gradescope. You will lose 0.25 points off the assignment if you do not do so. (For guidance watch this video on how to do this.)

COVID

Please stay home if you're ill. Lectures are recorded and most office hours are held remotely. If one of the course staff becomes ill we will move the appropriate events online. Consult the UW policies for more information.

Grade

  • Your grade is is divided equally between the written assignments (33%), programmaing assigments (33%), and final project (34%). I will also add up to 5% extra credit for students who actively participate in class or help others on the Ed discussion board.

Textbooks

Discussion Board

Please use Ed (link coming soon!) for course related questions.

Lectures

Lecture slides will be posted on this site before the relevant day. We will alert the class if any major changes are made to correct errors, etc after posting.

Inclusion

We welcome students from all backgrounds and adhere to the Allen School’s Inclusiveness Statement. If anything related to the course makes you feel unwelcome in any way, let the instructor know.

Accommodation

We are eager to provide necessary accommodations.

For disability accommodations, please see the UW resources.

For religious accommodations, please see the UW resources.

We recognize that our students come from varied backgrounds and can have widely-varying circumstances. If you have any unforeseen or extenuating circumstance that arise during the course, please do not hesitate to contact the instructor to discuss your situation. The sooner we are made aware, the more easily these situations can be resolved. Extenuating circumstances may include:

  • Work-school balance
  • Familial responsibilities
  • Unexpected travel
  • Paper deadlines
  • ... or anything else beyond your control which may negatively impact your performance in the class