Mechanism Design via Consensus Estimates, Cross Checking, and Profit Extraction
AbstractThere is only one technique for prior-free optimal mechanism design that generalizes beyond the structurally benevolent setting of digital goods. This technique uses random sampling to estimate the distribution of agent values and then employs the Bayesian optimal mechanism for this estimated distribution on the remaining players. Though quite general, even for digital goods, this random sampling auction has a complicated analysis and is known to be suboptimal. To overcome these issues we generalize the consensus technique from Goldberg and Hartline (2003) to structurally rich environments that include, e.g., single-minded combinatorial auctions.
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Bibliographic InfoPaper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number 1538.
Date of creation: 24 Aug 2011
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Postal: Center for Mathematical Studies in Economics and Management Science, Northwestern University, 580 Jacobs Center, 2001 Sheridan Road, Evanston, IL 60208-2014
Web page: http://www.kellogg.northwestern.edu/research/math/
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-09-05 (All new papers)
- NEP-CDM-2011-09-05 (Collective Decision-Making)
- NEP-GTH-2011-09-05 (Game Theory)
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