Who: John P. Dickerson
How do we allocate food to food banks, children to schools, organs to patients, residents to hospitals, security forces to patrol routes, and credit to multiple authors of an open source project—all in the face of competing incentives affecting selfish participants? Can we fairly divide a house, furniture, cars, and the family dog between a divorcing couple? Is Oprah going to be our next president, and—if so—why? Can we design mechanisms for these problems that perform well in practice, are computationally tractable, and whose workings and results are understandable by humans?
This course will consist primarily of reading and discussing recent papers from folks in computer science, economics, operations research, operations management, and medicine; as such, there is no assigned textbook. Some recommended high-level or reference readings follow.
Title | Author(s) | Why? | Link |
---|---|---|---|
Algorithmic Game Theory | Nisan, Roughgarden, Tardos, & Vazirani | Very readable introduction to, and reference book for, game theory and mechanism design. | (It's free!) |
Who Gets What — and Why: The New Economics of Matchmaking and Market Design | Al Roth | Pop-sci coverage of fielded matching markets like NRMP, school choice, and kidney exchange, from somebody who won a Nobel Prize for his part in their design. | (Amazon) |
Handbook of Computational Social Choice | Brandt, Conitzer, Enriss, Lang, & Procaccia | Good and very recent overview of recent theory and practice in social choice. | (It's free! password: cam1CSC) |
Combinatorial Auctions | Cramton, Shoham, & Steinberg | Fairly recent and very readable overview of modern approaches to auction design. | (It's free!) |
Students enrolled in the course will complete a semester-long course project on something related to market and mechanism design. This project can be done individually or—preferably—in a small group, and can be entirely theoretical, entirely applied, or anything in between. The goal here is to create something that is either immediately publishable or will lead to a publishable piece of work in the future. Project proposals will be due in early March, with two classes at the end of the semester set aside for individual and group presentations, if the class is small enough to accommodate that. There will also be a brief (2-page) "project check-up" document due in early April, to ensure progress is being made. A whitepaper—formatted as a conference paper—will be due by the exam date for this course (Monday, May 14 at 8:00AM). Examples of projects from last year that developed into full papers:
Students will present during the semester (assuming roughly 30–40 students, this should be feasible). Presenting in class is just that—spending 30 or so minutes presenting to the class on the required reading for that day. Some classes will start with John lecturing for 30–45 minutes followed by one student, or will consist of two students lecturing. Students are also welcome to take the entire class, if they'd like. We'll also post the student presentation (either slides or notes) online. You'll be able to select a topic to lecture on, or you can sell me on your own.
Finally, many students expressed interest in this course counting toward MS/PhD qualifiers; with that in mind, students enrolled in the course will have a 24-hour take-home midterm and a 48-hour take-home final; the former will occur sometime in early April, and the latter will be taken at the student's discretion at any time after the final lecture and before (48 hours before) the exam date for this course (Monday, May 14 at 8:00AM).
Final grades will be calculated as:
This course is aimed at Ph.D. students, but should be accessible to M.Sc. and B.Sc. students with some degree of mathematical maturity and an interest in applied mechanism design. If in doubt, e-mail me: john@cs.umd.edu!
# | Date | Topic | Reading | Slides | Lecturer | Notes |
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1 | 1/25 | Introduction | Alvin E. Roth. The economist as engineer: Game theory, experimentation, and computation as tools for design economics. Econometrica, 2002. | pdf, pptx | Dickerson | |
2 | 1/30 | Intro to Game Theory | Chapters 1 and 2 of Algorithmic Game Theory. | pdf, pptx | Dickerson | |
3 | 2/1 | Intro to Mechanism Design | Chapters 9 and 10 of Algorithmic Game Theory. | pdf, pptx | Dickerson | Results from game played in class: ; link to corresponding NYTimes survey: |
4 | 2/6 | — | — | — | — | John is at AAAI; lecture might be cancelled ... |
5 | 2/8 | Intro to Mechanism Design, Continued | — | pdf, pptx | Dickerson | |
6 | 2/13 | Primer in Combinatorial Optimization | Cornuéjols, Trick, and Saltzman. A Tutorial on Integer Programming. 1995. | pdf, pptx | Dickerson | |
7 | 2/15 | Primer in Combinatorial Optimization, Continued | — | pdf, pptx | Dickerson | |
8 | 2/20 | Security Games | Kiekintveld et al. Computing optimal randomized resource allocations for massive security games. AAMAS, 2009. | pdf, pptx | Dickerson | |
9 | 2/22 | Green Security Games | pdf1, pptx1, pdf2, pptx2 | Suraj Nair, Brook Stacy | USC website | |
10 | 2/27 | Green Security Games, & Stochastic Optimization Primer | pdf1, pdf2, pptx2 | Christiana Sabett, Mehdi Dadfarnia |
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11 | 3/1 | National Residency Matching Program | Roth and Peranson. The Redesign of the Matching Market for American Physicians: Some Engineering Aspects of Economic Design. American Economic Review, 1999. | pdf, pptx | Dickerson | We'll spend time discussing project ideas in class today. |
12 | 3/6 | Organ Exchange: Matching Theory | pdf, pptx | Dickerson | ||
13 | 3/8 | Organ Exchange: Batch Optimization | pdf1, pptx1, pdf2, pptx2 | Alireza Farhadi, Dickerson | ||
14 | 3/13 | Organ Exchange: Dynamic Optimization | Dickerson and Sandholm. FutureMatch: Combining Human Value Judgments and Machine Learning to Match in Dynamic Environments. AAAI, 2015. | pdf1, pptx1, pdf2, pptx2 | Dickerson, Ashton Webster | |
15 | 3/15 | Health Care and Wall Street | Montazerhodjat, Weinstock, and Lo. Buying cures versus renting health: Financing health care with consumer loans. Science Translational Medicine, 2016. | pdf1, pptx1, pdf2, pptx2 | Shravan Srinivasan, Ryan Eckenrod | |
– | 3/20 | Spring Break | — | — | — | |
– | 3/22 | Spring Break | — | — | — | |
16 | 3/27 | Allocation of Food to Food Banks | pdf1, pptx1, | Dickerson, Jacob Rasiel, Kevin Bock | Slate article about the Prendergast paper | |
17 | 3/29 | Combinatorial Assignment Problems |
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pdf1, pptx1, pdf2 | Dickerson, Janit Anjaria | Wharton's Course Match website |
18 | 4/3 | Incentive Auctions & Spectrum Repacking | pdf1, pptx1, pdf2, pdf3 | Dickerson, Sankha Guria, Allen Leis | Priceonomics blog post | |
19 | 4/5 | Fair Division: Theory, & Externalities | Chapters 11 and 12 of the Handbook for Computational Social Choice. (password: cam1CSC) | pdf1, pptx1, pdf2, key2 | Rangfu Hu, Hamed Saleh Mohammadabad | TENTATIVE: 24-hour take-home midterm out today |
20 | 4/10 | Fair Division: Practice, & Dynamics | Kurokawa, Procaccia, and Shah. Leximin Allocations in the Real World. EC, 2015. | Leonidas Tsepenekas, Mohammad Ghiasi | Spliddit website | |
21 | 4/12 | Gerrymandering | pdf1, pdf2, pptx2 | Brian Ondov, Julian Vanecek | Washington Post opinion piece: link | |
22 | 4/17 | Submodular Optimization & Influence Maximization | Kempe, Kleinberg, and Tardos. Maximizing the Spread of Influence through a Social Network. KDD, 2003. | pdf1, pdf2, pptx2 | Nathaniel Grammel, Hanuma Maddali | Submodularity website: link |
23 | 4/19 | Selfish Routing & Price of Anarchy | Roughgarden and Tardos. How Bad Is Selfish Routing. JACM, 2002. | pdf1, pdf2, pptx2 | Yogesh Balaji, Dantong Ji | Course project checkups due over the weekend! |
24 | 4/24 | Voting | Chapter 2 of the Handbook for Computational Social Choice. (password: cam1CSC) | pdf1, pdf2 | Frank Pike, Ivan Petrov | |
25 | 4/26 | Prediction Markets & Ethics | pdf1, pptx1, slides.com | Dickerson, Denis Peskov | The Wolves of K Street | |
26 | 5/1 | School Choice | pdf1, pdf2 | Willem Wyndham, Aya Ismail | ||
27 | 5/3 | Fairness, Accountability, and Transparency in Machine Learning (FATML) |
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pdf1, pptx1, pdf2, pptx2 | Ben Knisely, Nirat Saini | FATML workshops and resources; annual Conference on Fairness, Accountability, and Transparency (FAT*) |
28 | 5/8 | Fairness, Accountability, and Transparency in Machine Learning (FATML) | pdf1, pdf2 | Yigitcan Kaya, Michael Curry | ||
29 | 5/10 | Game Theory & Conversation, & Course Wrap-up | pdf1, pdf2, pptx2 | Samuel Barham, Dickerson | Accompanying discussion notes for Sam's lecture: pdf link | |
Final | 5/14 | Final exam | 48-hour take-home final must be turned in by this date at 8:00AM |