Recordings in canvas.
(subject to change)
|Wk.||Dates||Lecture slides||Reading (optional reading)|
|1||Sep 28,30||Introduction; Agents||R&N, 1,2,3.1|
|2||Oct 3,5,7||Search; Informed Search||R&N 3.2-end, 5.1-5.2; Search tool|
|3||Oct 10, 12, 14||Informed Search (cont.); Adversarial Search||R&N 5.3-5.5, (4)|
|4||Oct 17, 19, 21||ExpectiMax; Markov Decision Processes (MDPs)||R&N 17.1-17.3, (S&B 4.3-4.4)|
|5||Oct 24, 26, 28||MDPs (cont.); Reinforcement Learning||R&N 22.1-22.5, (S&B 5.1-5.5)|
|6||Oct 31, Nov 2, 4||RL(cont.); Uncertainty||R&N 12, 13.1-13.3 (MIT notes), R&N 15.1-15.3|
|7||Nov 7, 9||Hidden Markov Models||R&N 15.1-15.3|
|8||Nov 14, 16, 18||HMMs (cont.); Bayesian Networks (BNs)||R&N 14.1-14.3|
|9||Nov 21||Bayesian Networks (BNs) (cont.)||R&N 14.1-14.3|
|10||Nov 28, 30, Dec 2||Inference in BNs||R&N 14.4-14.5|
|11||Dec 5, 7, 9||Machine Learning||R&N 18.1-18.2; 20.1-20.2|
If you have any additional feedback you would like to share, please use this anonymous feedback form.
We also have office hours in a number of different times and locations. All times are Pacific. Please use this queue.
Individual assignments graded on correctness and due by 10pm on the day listed. Worth 50% of grade total. Make sure your answers are selected and visible when you submit them.
|Homeworks (HW)||Total Points||Due|
|2: Advanced Search||30||10/28/22|
|3: Markov Decision Processes||30||11/10/22|
|4: RL and HMMs||30||11/22/22|
Individual assignments graded on correctness and due by 10pm on the day listed. Worth 50% of grade total.
|Projects (PR)||Total Points||Due|
|0: Warm-up||N/A||Not graded|
|2: Multi-Agent Search||25||11/03/22|
|3: Reinforcement Learning||25||11/17/22|
|4: Inference and Filtering||25|
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.
Please use Ed for course related questions.
Lecture slides will be posted on this site before the relevant day. These are subject to revision of types typographic, syntactic, and semantic. We will alert the class if any major changes are made.
Lecture videos should upload to canvas automatically.
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.
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: