University of Massachusetts Amherst
College of Information and Computer Sciences

 

 

COMPSCI 383

Artificial Intelligence

   Spring 2017

 

Kris[tina] Fedorenko, Richard (Rick) Freedman

 

Course Information Tentative Schedule

Course description: The Course explores key concepts of artificial intelligence, including problem solving, state-space representation, heuristic search techniques, game playing, knowledge representation, logical reasoning, automated planning, reasoning under uncertainty, decision theory and machine learning. We will examine how these concepts are applied in the context of several applications.

Lecture: Monday & Wednesday 8:00-9:15, ILC S220

Prerequisites: COMPSCI 220 (or COMPSCI 230) and COMPSCI 240

Credit: 3 units

Instructors:

Teaching assistants:

Textbook:

Grading: This semester, we will include team-based learning elements in place of having strictly lectures during class time. Thus participation and attendance will have a greater weight this semester.

Attendance Policy: Due to the course's lecture format and use of team-based activities, class attendance and participation are necessary for successfully understanding the material. However, it is understandable that unforeseen circumstances may occur that will not make it possible to attend every class. In such cases, the student must contact the instructors in advance (before the class) to inform and explain the upcoming absence. Make-up options will be available for such students to receive partial attendance/participation credit rather than a 0.

Policy for exams: If you have any special needs/circumstances pertaining to an exam, you must talk to the instructors before the exam (in advance).

Late policy: We will use an online tool called Gradescope for collecting and grading homework assignments. Programming portions should be submitted electronically via Moodle. 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 automatically 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 instructors 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 instructors 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, not the solution! All writing and coding must be done on your own. Sharing or copying solutions is unacceptable and could result in failure.

Accessing the web site: The URL of the class web site is " http://www-edlab.cs.umass.edu/cs383/". 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. You will receive a user id and password during the first week of classes.

Many of the materials created for this course are the intellectual property of the instructors. 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 instructors. 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.


© 2016 Shlomo Zilberstein, modified 2017 by Richard Freedman and Kristina Fedorenko with permission.