Third Workshop on Algorithmic Game Theory and Data Science, to be held June 26, 2017 in Cambridge, Massachusetts.
From the call:
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.