This course provides an introduction to the field of artificial intelligence. The major topics covered will include reasoning and representation, search, constraint satisfaction problems, planning, logic, reasoning under uncertainty, and planning under uncertainty.


See below for the late policy.


TR 2:00-3:20 online; see Canvas. First class: Thursday September 10.


Instructor: David Poole, Office hours TBA.

Teaching Assistants:

Structure of the Course

There will be 3 hours of in-class interaction per week.

We will use Canvas for discussions, clicker registration and to view grades. All other content will be here.


We will use the following textbook:

Note that the complete text is online. So you don't need to buy it unless you would prefer the hard copy.



The course assessment will be based on assignments, in-class participation, and exams. Assignments will be a mix of traditional assignments, and applying what is being covered in class to your vertical domain.

The breakdown of marks is tentatively:

There are no late penalties for late assignments. However, we will only accept assignments up to the time solutions are posted or they are discussed in class, after which no credit will be given. The solution will not be posted before the due time. (This means deciding whether to keep working or submit the current version is a problem of decision making under uncertainty.)

Academic integrity is essential for a university to function. Plagiarism and cheating will be treated seriously. The work you hand in must be your own, except where you have explicitly cited the source. If in doubt, put other's words in quotations and cite the source. See UBC Regulation on Academic Misconduct. The penalties are severe.

Last updated: 2020-09-13, David Poole