University of Massachusetts Amherst
College of Information and Computer Sciences




Artificial Intelligence

 Spring 2020


Shlomo Zilberstein


Course Information


Coronavirus Update: UMass Amherst has suspended all in-person classes until the end of the semester. Effective Monday, March 23, COMPSCI 683 will resume as an online class. We will continue to use Piazza for all course-related communications. Please check the announcements on Piazza regarding future lectures and office hours.  

Course description: In-depth introduction to Artificial Intelligence focusing on techniques that allow intelligent systems to reason effectively with uncertain information and cope limited computational resources. Topics include: problem-solving using search, heuristic search techniques, constraint satisfaction, local search, abstraction and hierarchical search, resource-bounded search techniques, principles of knowledge representation and reasoning, logical inference, reasoning under uncertainty, belief networks, decision theoretic reasoning, planning under uncertainty using Markov decision processes, multi-agent planning, and computational models of bounded rationality.

Lectures: Tuesday & Thursday 10:00-11:15 in LGRT 123

Credit: 3 units


Teaching assistants:


Recorded Lectures:


Policy for exams: If you have any special needs/circumstances pertaining to an exam, you must talk to the instructor before the exam.

Late policy: We will use an online tool called gradescope for collecting and grading homework assignments. Programming portions should be submitted electronically via the EDLAB. Assignments are to be turned in by 11:59 PM on the due date (the same deadline applies to programming assignments; we will verify that no file was modified after the deadline). Gradescope will automaticaly disable turning in homework after the deadline. No exception will be made. If you cannot meet a deadline, you need to discuss that with the intructor in advance and make alternate arrangements for turning in your work.

Regrade policy: Graded homework assignments will be returned via gradescope. If you think a grading error was made, you must file a regrade request using gradescope within one week of when the graded work was released. For any other work or exam that is not handled via gradescope, you must talk to the TA or the instructor within a week of when it was handed back.

Academic honesty policy: You are encouraged to discuss the course material with your classmates. You may also discuss homework assignments, but only in order to get a better understanding of the questions. All writing and coding must be done on your own. Sharing or copying solutions is unacceptable and could result in failure. If in doubt about a particular collaboration, ask for permission in advance.

Accessing the web site: The web site address is "". You can use your favorite internet browser to access the material, but some documents are protected by password. Only students who are enrolled in the class are authorized to use the material. The userid and password will be provided in class.

Many of the materials created for this course are the intellectual property of the instructor. This includes, but is not limited to, the syllabus, lectures and course notes. Except to the extent not protected by copyright law, any use, distribution or sale of such materials requires the permission of the instructor. Please be aware that it is a violation of university policy to reproduce, for distribution or sale, class lectures or class notes, unless copyright has been explicitly waived by the faculty member.

© 2020 Shlomo Zilberstein.