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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 singular bin. In the strategic variant of the...
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-world settings, the participants act as...
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 minimal peer prediction mechanisms are...
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 this problem have resisted good approximation...
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