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A Truthful Mechanism for the Generalized Assignment Problem
We propose a truthful-in-expectation, (1-1/e)-approximation mechanism for a strategic variant of the generalized assignment problem (GAP). In GAP, a set of items has to be optimally assigned to a set of bins without exceeding the capacity of any ...
Dynamics at the Boundary of Game Theory and Distributed Computing
We use ideas from distributed computing and game theory to study dynamic and decentralized environments in which computational nodes, or decision makers, interact strategically and with limited information. In such environments, which arise in many real-...
Envy-Free Pricing in Large Markets: Approximating Revenue and Welfare
We study the classic setting of envy-free pricing, in which a single seller chooses prices for its many items, with the goal of maximizing revenue once the items are allocated. Despite the large body of work addressing such settings, most versions of ...
A Geometric Perspective on Minimal Peer Prediction
Minimal peer prediction mechanisms truthfully elicit private information (e.g., opinions or experiences) from rational agents without the requirement that ground truth is eventually revealed. In this article, we use a geometric perspective to prove that ...