Foundations of Artificial Intelligence

CS 4700 - Spring 2019

Haym Hirsh (Instructor)

Contact Information: For all main course correspondance, please email fai-l@cornell.edu. This email contacts both Prof. Hirsh and graduate TAs. It will facilitate better (and hopefully quicker!) communication between you and the staff. If your issue is something you prefer to discuss only with Prof. Hirsh, his email is found on his website.

Office Hours: office hours will be posted on the Course Calendar and may be updated week-to-week; check the calendar before you attend!

Basics
Schedule & Calendar
Grading
Policies

Quick Links

• Schedule & Calendar Page
• Karma Seminars Page
• Technology Policy Page

• Prerequisites: CS2100/ENGRD2100, CS2800 (particularly probability and first-order logic), Calculus

• Lecture: Mondays, Wednesdays, and Fridays 1:25 - 2:15pm, Olin Hall 155

• Online discussion: We will be using Piazza for class discussions.

• Assignment submissions: Written assignments are submitted via Gradescope (Entry Code: 98EPKV) and programming-based assignments are submitted via CMS

• Textbook: Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, Draft 4th Edition. This edition is a working online draft and does not require you to buy the 3rd edition hardcopy. Follow this link to access it (NetID required). To submit feedback (and earn Karma Points!), go here.

• Enrollment information: If you are interested in this class and are not enrolled, please get on the waitlist.

• Faculty-Student Lunches: The CIS Dean's office sponsors weekly small group lunches with Prof. Hirsh and up to 9 students. To sign up for lunch with Prof. Hirsh, click here.

• Exam Locations: For the prelim, calculate the padded last two digits of your netID (e.g. abc6 becomes "60" and abc2021 becomes "21"). Students with digits 00-28 will take the prelim in Baker Laboratory 219. Students with digits 29-99 will take the prelim in Baker Laboratory 200.

Please follow this link for the schedule, which outlines topics and provides links to lecture slides, readings, and homeworks as well as the course calendar.

The course calendar will be updated with relevant course information that is not lecture or assignment specific, as appropriate. The calendar will also show office hours; specific timing may change week to week, so please check the calendar before you go to office hours. Please only attend office hours for 4700, although the calendar is also shared with the practicum.

• 15% +/- 3%: Homeworks
• Homeworks can be submitted up to 48 hours late for a 50% penalty. If you have extenuating circumstances, please contact the list serv; we will provide extensions when applicable for injuries, family emergencies, etc. on a case-by-case basis.
• All homeworks must be submitted through Gradescope. Sometimes assignments may additionally ask you to submit material elsewhere, such as a Google form. You have not submitted the assignment on time if you have not submitted in both places on time.
• Homeworks can be typeset, or scanned in versions of handwritten answers. Either way, use common sense – is it legible? Illegible homework may receive an automatic zero.
• Collaboration: Doing a homework problem typically involves two steps: (1) understanding the problem/figuring out the solution and (2) writing it up coherently. For the first step, we encourage you to discuss with your peers in the course to brainstorm ideas for how to get through homework. You are also allowed to use other online resources if you find something that's relevant. However, your solution must be written up completely on your own; you are not allowed to share digital or written notes or images of your work in any form with each other. Just like in research, your work must also include acknowledgements of all students with whom you collaborated (ideally, at the top of your first page). Both the physical or digital distribution of information about solutions and the failure to acknowledge collaborators are likely violations of academic integrity.
• The homeworks are designed to get you to exercise the concepts discussed in class in a deeper way than is possible in class. If you can’t independently manage to solve the homeworks by the time you’re done you won’t understand the material well (and will not do well on the exams). You should be confident that you really understand what you’re writing rather than copying down something you only partly understand.
• 40% +/- 3%: Prelim (19 March at 7:30pm)
• 45% +/- 3%: Final (13 May at 2:00pm)
• Karma points: Throughout the semester you will have opportunities to earn “karma points”. These are not counted in computing your overall score for the class, but will be used for students who are borderline between grades. Examples of ways to earn karma points include:
  • Answering questions and writing helpful posts on Piazza.
  • Attending AI seminars that may take place over the course of the semester. You will be asked to submit a list of seminars that you attended at the end of the semester. Link to seminars is here.
  • Providing helpful feedback for the authors on the chapters that we cover in class. You should submit your comments here.
  • Submitting a course evaluation at the end of the semester.
  • Students can also receive negative karma, for example by asking questions that have already been answered on Piazza or the course website.

Regrade Requests

Regrade requests must be submitted within seven days of grades being released via Gradescope.

Technology Policy

The technology policy for this course can be found here.

Academic Integrity

From Cornell's code of academic integrity:

Absolute integrity is expected of every Cornell student in all academic undertakings. Integrity entails a firm adherence to a set of values, and the values most essential to an academic community are grounded on the concept of honesty with respect to the intellectual efforts of oneself and others. Academic integrity is expected not only in formal coursework situations, but in all University relationships and interactions connected to the educational process, including the use of University resources. ... A Cornell student's submission of work for academic credit indicates that the work is the student's own. All outside assistance should be acknowledged, and the student's academic position truthfully reported at all times. In addition, Cornell students have a right to expect academic integrity from each of their peers.

Accommodations

This course complies with the Cornell University policy and equal access laws to ensure that students with disabilities can still participate fully in this course. Requests for academic accommodations should be made during the first three weeks of the semester, except for unusual circumstances, so arrangements can be made as soon as possible. Please do this by scanning your documentation letter and emailing it to fai-l@cornell.edu. Students are encouraged to register with Student Disability Services, as we may require verification of eligibility to provide appropriate accommodations.

Respect in Class

Everyone, the instructor, TAs, and students, must be respectful of everyone else in this class. All communication, in class and online, will be held to a high standard for thoughtfulness and inclusiveness: it may never target individuals or groups for harassment, and it may not exclude specific groups. That includes everything from outright animosity to the subtle ways we phrase things and even our timing.

If any of the communication in this class doesn't meet these standards, please don't escalate it by responding in kind. Instead, contact the instructor as early as possible; if for whatever reason you don't feel comfortable discussing something directly with the instructor please contact your advising office or the department chair.

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