Summer Graduate School
|Location:||MSRI: Simons Auditorium, Atrium|
Have you ever thought how to use math to:
- sell online ad slots in real time?
- allocate resources during the COVID-19 pandemic?
- resettle refugees?
- auction wireless spectrum to companies?
- ensure fairness in markets?
We shall discuss these topics and many others in the upcoming MSRI Summer Graduate School on Mathematics and Computer Science of Market and Mechanism Design!
The school will provide the mathematical and theoretical computer science toolbox that forms the foundation of market and mechanism design - two of the burning research areas of the 21st century.
Market and mechanism design are beautiful examples of how deep mathematical theory can lead to improved design of real-world marketplaces and auctions. We shall consider the algorithmic, complexity, economic and societal aspects of these topics.
The school will consist of an introductory and an advanced course in each of the two topics: mechanism design and market design. In the morning hours there will be lectures and in the afternoons there will be recitation sessions. Teaching assistants will present problems and then guide the students through problem sets that will encourage deeper thought and discussion of the materials. The students will work in groups and prepare projects on state-of-the-art problems in mechanism and market design of their own choice. They will present the projects during the final days of the school, and short project summaries will appear in a writeup summarizing the school.
Students are required to have basic familiarity with game theory, algorithms and probability. Possible references are:
- Karlin and Peres, Game Theory Alive, Chapters 2 and 5.
- Vazirani, Approximation Algorithms, Chapters 1 and 8.
- Krishna, Auction Theory, Appendices A-C.
- Eilon Solan, Michael Maschler, and Shmuel Zamir, Game Theory, Chapters 4-5 (and 9 as a bonus).
- von Stengel, Game Theory Basics, Chapter 3.
For eligibility and how to apply, see the Summer Graduate Schools homepage
algorithmic game theory