Approximate Revenue Maximization in Interdependent Value Settings

  title={Approximate Revenue Maximization in Interdependent Value Settings},
  author={Shuchi Chawla and Hui Fu and Anna R. Karlin},
We study revenue maximization in settings where agents' values are interdependent: each agent receives a signal drawn from a correlated distribution and agents' values are functions of all of the signals. We introduce a variant of the generalized VCG auction with reserve prices and random admission, and show that this auction gives a constant approximation to the optimal expected revenue in matroid environments. Our results do not require any assumptions on the signal distributions, however… CONTINUE READING
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