Announcements: Announcements will be posted on the course blog. Check it regularly, or subscribe to the RSS feed.
Overview: In this course, we will explore key concepts of artificial intelligence, such as state-space and heuristic search techniques, game playing, knowledge representation, automated planning, reasoning under uncertainty, decision theory and machine learning. We will examine how these concepts are applied in the context of several applications.
Prerequisites: An understanding of non-trivial programming (CMPSCI 220 or 230 with a C or better) is required. You must be able to program in a high-level programming language, such as Python or Java. You will also require the ability to reason under uncertainty (CMPSCI 240 with a C or better).
Instructor:
Marc Liberatore
Email: liberato@cs.umass.edu
Phone: 413-545-3061 (on campus: 5-3061)
Office: CS 356A (inside 356)
Office Hours: Monday 1500, Thursday 1600, and by appointment.
Class meetings: Integrative Learning Center N211 (not S211 on the same floor!), Tuesdays and Thursdays, 1000–1115
Class WWW site: http://www-edlab.cs.umass.edu/cs383/
We will make extensive use of the class website. All assignments are
posted (only) on this site.
Discussion forum: The course Moodle site has an open discussion forum that you are welcome to use. Please note that neither I nor the TA plan to be checking it frequently. If you have questions you want us to answer, please ask us in person or send us email.
Teaching assistant:
Patrick Pegus
Email: ppegusii@cs.umass.edu
Office (for TA hours): CS 207, cube 4
Office Hours: Tuesday 1400, Wednesday 1330.
Course materials:
- Textbook: Artificial Intelligence: A Modern Approach, 3rd edition, by Stuart Russell and Peter Norvig. The 2nd edition, especially used, is much cheaper! You may find it suffices if you can cross-reference the section numbers, etc., with the 3rd edition.
- Assigned readings from the text and the web will be linked to on the schedule.