AI Seminar
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  Tuesday, April 19th, 2005
  4:00 pm - 5:30 pm
  175 ATL (Large Conference Room)

  "Empirical Mechanism Design:
    Methods, with an Application to a Supply-Chain Scenario"
  Yevgeniy Vorobeychik
  Artificial Intelligence Laboratory
  University of Michigan

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Our proposed methods employ learning and search techniques to estimate
outcome features of interest as a function of mechanism parameter
settings. We illustrate our approach with a design task from a
supply-chain trading competition. Designers adopted several rule changes
in order to deter particular procurement behavior, but the measures
proved insufficient. Our empirical mechanism analysis models the relation
between a key design parameter and outcomes, confirming the observed
behavior and indicating that no reasonable parameter settings would have
been likely to achieve the desired effect.


(This is joint work with Michael Wellman)