Topics in Algorithmic Game Theory
This course examines topics in game theory from a computer scientist's perspective. Through the lens of computation, this course will focus on the design and analysis of systems involving self-interested agents, investigating how strategic behavior should influence algorithm design, which game-theoretic solution concepts are practical to implement, and the ramifications of conflicts of interest between system designers and participating agents. Topics include: auctions and mechanism design, equilibria, and learning.
- What is game theory?
- What is mechanism design?
- What is auction theory?
- Simple auctions
- Awesome auctions
- EPIC auctions
- Bidding strategies
- Prediction markets
- Combinatorial auctions
- Computational advertising
Students will be assigned likely weekly exercises, amounting to about 5 hours of written work per week, as well as that which is necessary to comprehend the week’s lecture materials, which will vary across students.
Students will also be required to attend one 2 hour lab each week, where they will work collaboratively on written and programming exercises.
There will also be programming assignments, to be completed in small groups, in which students build AI agents that trade autonomously in simulations of various real-world market domains, ranging from ad auctions and exchanges to prediction markets.
The course will culminate in a final project.
Grades will be determined as follows: weekly exercises (30%); programming assignments (30%); labs, in-class activities, and participation (15%); final project (25%) [subject to change].
For weekly exercises, which are to be turned in electronically, students will be granted three free late days, which can be applied, as needed, over the course of the semester. For homeworks due Tuesday night, late days only apply until 2:59 PM the next day (Wednesday) and cannot be stacked. Homeworks turned in after 2:59 PM on Wednesday will not be accepted. This is because we would like to review the homework during class. In the unfortunate circumstance that these three free late days are all used up, late day penalties will apply: -10% within 24 hours, and -25% within 48. No assignments will be accepted electronically more than 48 hours beyond their due date.
For programming assignments, which are to be graded interactively (meaning students have a set time at which they will be meeting a TA), the following late penalties always apply: if the student is late by 10 minutes or less, -10%; 10 to 20 minutes, -20%; more than 20 minutes counts as a "no show", for which the penalty is -50%. This same penalty schedule applies recursively to rescheduled interactive gradings following a no show. Last-minute email requests to reschedule interactive gradings must be sent to the relevant grader(s) and to the head TAs at least 2 hours prior to the scheduled meeting time to avoid any penalties.
For group projects that are graded interactively, if some members show up for the grading session while others do not, grading will proceed, and those who do not appear will receive a grade of 0 for that portion of the assignment, while those who appear late will be penalized according to the aforementioned penalty schedule.
Extensions may be granted by the professor in extreme circumstances. If you are ill, please do not ask for an extension without a note from health services.
Students are encouraged to collaborate with their peers in CSCI1951k.
When working on assignments, students may consult one another; but are then required to list the names of all students with whom they discussed an assignment on their submitted work. Unnatural similarities among students' submissions with other students whose names are not listed will be forwarded to the Dean of the College's office for review, to assess whether or not there has been a violation of Brown's Academic Code.
If you have any questions about this policy, please ask the course staff for clarification. Not understanding our policy is not grounds for not abiding by it.
Diversity and Inclusion
The computer science department is committed to diversity and inclusion, and strives to create a climate conducive to the success of women, students of color, students of all (or no) sexual orientations, and any other students who feel marginalized for any reason.
If you feel you have been been mistreated by another student, or by any of the course staff, please feel free to reach out to one of the CS department's Diversity and Inclusion Student Advocates, or to Professor Greenwald or Professor Cetintemel (the CS department chair). We, the CS department, take all complaints seriously.
If you feel you have any disabilities that could affect your performance in the course, please contact SEAS, and ask them to contact the course staff. We will support accommodations recommended by SEAS.