Many systems have components that are controlled by people (as in the Internet) or are people themselves (as in an auction). Engineering such systems becomes more challenging, since each user may try to game them to his own advantage. This is even more true as the size of the system grows but the resources of the designer do not. How should one go about designing such systems? In particular,
-how can we successfully predict the impact of strategic behavior on a system's performance?
-how do we design a system so that its performance is robust to strategic manipulations?
-what fraction of the optimal performance can we guarantee?
Headed by Professors Daskalakis and Micali, the Economics and Computation group tackles these questions through an interdisciplinary approach that brings together tools from economics, game theory, algorithms, computational complexity, and cryptography. Examples of this line of research include the complexity of Nash equilibrium, optimal multi-item auctions, and rational proofs.