Probabilistic Reasoning in AI (COMP-526)

Winter 2008


General Information

Where: Trottier 0060.

When: Monday, Wednesday, Friday, 10:35-11:25am.

What: One of the primary goals of AI is the design, control and analysis of agents or systems that behave appropriately in a variety of circumstances. Good decision making often requires the existence of knowledge or beliefs about the agent's environment, as well as about its own abilities to observe and change the environment, and about its own goals and preferences. In this course we will examine computational approaches for modeling uncertainty and for solving decision problems. We will focus mainly on probabilistic models of reasoning, and on sequential decision making.

The course is intended for advanced undergraduate students and for graduate students, and will provide an introduction to the on-going research in the field of reasoning under uncertainty, which has been very active during the last decade. For details, see the syllabus and tentative schedule.


Doina Precup
School of Computer Science
Office: McConnell 111N

Office Hours: Monday 11:30-12:00 and 5:00-6:00 and Friday 2:30-3:30. Note that office hours may be cancelled on some days, so check Doina's calendar beforehand. Meetings at other times are available by appointment only

Phone: (514) 398-6443
E-mail: dprecup at cs dot mcgill dot ca

Teaching assistant

Pablo Samuel Castro
Office Hours: Tuesday 3:30-5:30, McConnell 111 (not the same as Doina's office!)
E-mail: pcastr at cs dot mcgill dot ca


  1. Lecture notes are available on the schedule web page.
  2. The class material is based on selected chapters from the following textbooks: The relevant portions will be indicated on the schedule web page as needed.
  3. Other materials (e.g. additional research papers) will be posted on the schedule web page as needed.

Last modified: Thu Jan 3 11:45:19 EST 2008