CSC 665: Artificial Intelligence
San Francisco State University, Fall 2023
Instructor: Tyler Dae Devlin (tddevlin@sfsu.edu)
Time: 11:00 AM to 12:15 PM, Tuesdays and Thursdays
Location: EP 101
Office hours: Tuesdays 10 – 11 am and Thursdays 12:15 – 1 pm, TH 434
Course description: This course surveys some of the main techniques that have been developed over the past ~70 years in an attempt to create “artificial intelligence.” Topics include search, game playing, logic, constraint satisfactions problems, probabilistic graphical models, machine learning, and deep learning.
Optional textbook: Artificial Intelligence: A Modern Approach, Stuart Russell & Peter Norvig, 4th edition.
Grading: The final grade will be based on the following components:
- 60% homework assignments (6 assignments worth 10% each)
- 20% midterm exams (2 exams worth 10% each)
- 20% final exam
- 2% participation (extra credit)
Letter grades will be assigned according to the following cutoffs:
| [93, 100] | A |
| [90, 93) | A- |
| [87, 90) | B+ |
| [83, 87) | B |
| [80, 83) | B- |
| [77, 80) | C+ |
| [73, 77) | C |
| [70, 73) | C- |
| [67, 70) | D+ |
| [63, 67) | D |
| [60, 63) | D- |
| [0, 60) | F |
The left endpoint of any of these intervals may be lowered at the end of the semester, but the right endpoints will not be increased.
Late work: All homeworks are due at 11:59 pm on Mondays and should be submitted via Canvas. Late submissions will be assessed a 10% penalty per day after the due date, up to a maximum of 5 days late. Each student is granted one late waiver which can be used to exempt any homework assignment from the late penalty; the late deadline in this case is still 5 days after the normal due date (i.e. 11:59 pm on the Saturday of the same week).
Other details: See the syllabus for the complete list of course policies.