Economics and Computation

Computer Science (CS) students need to learn about more than just pure CS. With the advancement of electronic markets, game theory turns out to be relevant for CS in many real-life situations. Where before, the matching of residents to hospitals and of kidney donors to patients through a nation-wide program were the main successes on the border of algorithm design and economics, nowadays some background in both economics and computer science is necessary to fully understand auctions for on-line advertisement and wireless frequencies, incentives (user motivation) in file-sharing, recommender systems, reputation systems, and digital currencies, among others.
David Parkes (Harvard) and Sven Seuken (University of Zurich) have written a book covering a large number of such examples. The book discusses the required background for truly understanding these economic systems and the respective computational considerations at a level accessible to master students in CS. At the moment of writing, the book still has to be published (see http://economicsandcomputation.org), but we were fortunate enough to be allowed to use some chapters in a masters-level course in Delft.
The objectives of the course are that students become aware of when it makes sense to consider not only the algorithmic/computational aspects of a problem, but also possible strategic behavior, and that they know where to look for. To reach these objectives, students are asked to form pairs and select one of the chapters in the book to prepare a lecture for. They are also asked to write an extension to their chapter: which topic in the literature is related and relevant, but not included in the book?
In last semester’s run of the course the topics for the extensions were the following:
  • Ch 5: account for fairness in peer-to-peer file sharing
  • Ch 9: give bounds on (randomized) truthful mechanisms
  • Ch 10: estimate click-through rates in ad-auctions
  • Ch 11: special cases in winner determination of combinatorial auctions
  • Ch 12: many-to-one matching
  • Ch 15: aggregate search results in meta-search engines
  • Ch 22: strategic behavior in block-chain mining pools
The book authors wrote me they very much liked the of the setup of the course and were impressed with the resulting extensions. I’m happy we have some good students in Delft!

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