Bayesian Optimal Auctions via Multi- to Single-agent Reduction

Abstract

We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good (furthermore, it allows an agent's budget and risk preference to be known only privately to the agent). These are the main challenge areas for auction theory. A single-agent problem is to optimize a given objective subject to a constraint on the maximum probability with which each type is allocated, a.k.a., an allocation rule. Our approach is a reduction from multi-agent mechanism design problem to collection of single-agent problems. We focus on maximizing revenue, but our results can be applied to other objectives (e.g., welfare).

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Document Details

Document Type
Technical Report
Publication Date
Mar 23, 2012
Accession Number
ADA592725

Entities

People

  • Azarakhsh
  • Hu Fu
  • Jason Hartline
  • Malekian
  • Nima Haghpanah
  • Saeed Alaei

Organizations

  • Cornell University

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  • Materials and Manufacturing Processes

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  • Economics

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  • AI & ML
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