Econ 3810/Econ 6760/ CS 5846:
Course Policies and General Course Info

Time and Place:
Monday, Wednesday 9:40 - 10:55 AM, on this zoom link.

Joe Halpern,
Larry Blume,
Fikri Pitsuwan,
Shawn Ong,,
Oliver Richardson,

What the course is about:
The course introduces approaches to decision theory from computer science, economics, and game theory. It's intended for advanced undergraduates and graduates students in computer science, economics, mathematics, philosophy, and cognitive science. The course has several objectives, reflected in the topics on the reading list. First, we will cover basic decision theory, also known as ``rational choice theory''. Second, we will cover the limitations and problems with this theory, both as it applies to computers and to human agents. (The problems are not the same in all cases.) Issues to be discussed here include decision theory paradoxes revealed by experiments, cognitive limitations, and computational issues. Third, we will cover new research designed in response to these difficulties. Finally, we will examine the role of decision theory in ethical issues.

Having some mathematical sophistication is more important for this class than specific mathematical technique. The required technical background is the basic elements of probability theory --- random variables, expectations, and conditioning. This is typically covered in the first few weeks of a probability course. Roughly speaking, you should at least the material covered in the first 67 of the 95 slides (taken from CS 2800/2802). ``Mathematical sophistication'' means some experience reading and writing mathematical proofs. You will see a lot of proofs in the course, and will be required to do some for homework and for the prelim/exam. Students who have not had experience with writing mathematical proofs have had difficulty with the course in the past.

There will be one midterm, to be held roughly March 15, either in class or in the evening, and a final, given at the Cornell-scheduled time. We believe that doing homework regularly is the best way to learn the material, and the grading reflects that. Homework will be handed out every other week. Students taking Econ 6760 and CS 5846 will have extra problems. Homework, midterm, and exams will be weighted roughly as follows:

Late Homework Policy: Homework will due on Gradescope. To compute the final homework grade, we will drop your lowest homework grade.If you miss handing in an assignment (for emergency, illness, whatever), this will be the one dropped. Homework will be handed in via Gradescope. Please enroll in gradescope using entry code KYZV3G; the course is listed on Gradescope as CS 5846. You should do this even if you're taking the course as ECON 3810 or ECON 6760. (Do this right away; you won't be able to hand in homework until you do.)

Academic Integrity: It's OK to discuss the problems with others, but you MUST write up solutions on your own, and understand what you are writing. You may not copy any part of someone else's code or written homework. To do so is a violation of the Academic Integrity Code.

Text: The required text is Kreps' Notes on the Theory of Choice. You can get some useful background from Resnik's Choices: An Introduction to Decision Theory. Both are on reserve at the library. Various additional readings will also be handed out and posted.

Ed Discussion and Canvas:We'll be recording each class and posting the recording on Canvas. In addition, we'll be using Ed Disussion for course announcements and discussion (although some announcements will also be posted on the course web page). We're experimenting with this as an alternative to Piazza. Everyone enrolled in the course should be able to access the course webpage on Canvas (it's listed as ECON6760/ECON3810/CS5846). The Ed Discussion link is on the left, right under the home button. Feel free to post questions there and answer questions. We will try to monitor the discussion and answer questions. Please note: even you post something anonymously, we have been told that the course instructors will see your name (although other students won't).

Inclusiveness: You should expect and demand to be treated by your classmates and the course staff with respect. You belong here, and we are here to help you learn and enjoy this course. If any incident occurs that challenges this commitment to a supportive and inclusive environment, please let the instructors know so that the issue can be addressed.