Ph.D. Thesis, MIT, EECS Department. Honorable Mention of the George M. Sprowls Award (for best MIT doctoral theses in CS) and the SIGEcom Doctoral Dissertation Award runner-up, 2013.
A modern engineering system, e.g. the Internet, faces challenges from both the strategic behavior of its self-interested participants and the inherent computational intractability of large systems. Responding to this challenge, a new field, Algorithmic Mechanism Design, has emerged. One of the most fundamental problems in this field is How to optimize revenue in an auction? In his seminal paper [Mye81], Myerson gives a partial solution to this problem by providing a revenue-optimal auction for a seller who is looking to sell a single item to muLtiple bidders. Extending this auction to simultaneously selling multiple heterogeneous items has been one of the central open problems in Mathematical Economics. We provide such an extension that is also computationally efficient. Our solution proposes a novel framework for mechanism design by reducing mechanism design problems (where one optimizes an objective function on "rational inputs" ) to algorithm design problems (where one optimizes an objective function on "honest inputs"). Our reduction is generic and provides a framework for many other mechanism design problems.