The Third Workshop on Algorithmic Game Theory and Data Science will be held in conjunction with the Eighteenth ACM Conference on Economics and Computation (EC'17) on June 26, 2017 in Cambridge, Massachusetts.

Synopsis: Computer systems have become the primary mediator of social and economic interactions, enabling transactions at ever-increasing scale. Mechanism design when done on a large scale needs to be a data-driven enterprise. It seeks to optimize some objective with respect to a huge underlying population that the mechanism designer does not have direct access to. Instead, the mechanism designer typically will have access to sampled behavior from that population (e.g. bid histories, or purchase decisions). This means that, on the one hand, mechanism designers will need to bring to bear data-driven methodology from statistical learning theory, econometrics, and revealed preference theory. On the other hand, strategic settings pose new challenges in data science, and approaches for learning and inference need to be adapted to account for strategization. The goal of this workshop is to frame the agenda for research at the interface of algorithms, game theory, and data science.

The workshop will bring together researchers and practitioners from academia and industry to discuss the burgeoning development in the intersection of Algorithmic Game Theory and Data Science.