In conjunction with the Eighteenth ACM Conference on Economics and
Computation (EC'17), we solicit submissions for the Third Workshop on
Algorithmic Game Theory and Data Science, to be held on June 26, 2017
in Cambridge, Massachusetts.
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.
Papers from a rich set of experimental, empirical, and theoretical
perspectives are invited. Some questions at this interface that the
workshop will explore are:
- Can good mechanisms be learned by observing agent behavior in
response to other mechanisms?
- What is the sample complexity of mechanism design?
- How does mechanism design affect inference?
- How does inference affect mechanism design?
- Can tools from computer science and game theory be used to
contribute rigorous guarantees to interactive data analysis?
Submission deadline: May 10, 2017
Notification of acceptance: May 18, 2017
Workshop: June 26, 2017
ACM EC Conference: June 26-30, 2017
Submission instructions and more information at:
Jean Honorio, Purdue
Denis Nekipelov, U. of Virginia
Renato Paes Leme, Google Research
Yaron Singer, Harvard
Vasilis Syrgkanis, Microsoft Research
Elie Tamer, Harvard
For any question, please contact us at:
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