Mechanism Design via Optimal Transport
Name
Daskalakis_Mechanism design.pdf
Size
284.34 KB
Format
Adobe PDF
Checksum (MD5)
f2ccad7bbd45f8857c8f7dbfcbee2b77
Author(s)
Daskalakis, Konstantinos
Deckelbaum, Alan
Tzamos, Christos
Date Issued
June 2013
Journal
Proceedings of the Fourteenth ACM Conference on Electronic Commerce
Publisher
Association for Computing Machinery (ACM)
Citation
Constantinos Daskalakis, Alan Deckelbaum, and Christos Tzamos. 2013. Mechanism design via optimal transport. In Proceedings of the fourteenth ACM conference on Electronic commerce (EC '13). ACM, New York, NY, USA, 269-286.
Version
Original manuscript
Abstract
Optimal mechanisms have been provided in quite general multi-item settings [Cai et al. 2012b, as long as each bidder's type distribution is given explicitly by listing every type in the support along with its associated probability. In the implicit setting, e.g. when the bidders have additive valuations with independent and/or continuous values for the items, these results do not apply, and it was recently shown that exact revenue optimization is intractable, even when there is only one bidder [Daskalakis et al. 2013]. Even for item distributions with special structure, optimal mechanisms have been surprisingly rare [Manelli and Vincent 2006] and the problem is challenging even in the two-item case [Hart and Nisan 2012]. In this paper, we provide a framework for designing optimal mechanisms using optimal transport theory and duality theory. We instantiate our framework to obtain conditions under which only pricing the grand bundle is optimal in multi-item settings (complementing the work of [Manelli and Vincent 2006]), as well as to characterize optimal two-item mechanisms. We use our results to derive closed-form descriptions of the optimal mechanism in several two-item settings, exhibiting also a setting where a continuum of lotteries is necessary for revenue optimization but a closed-form representation of the mechanism can still be found efficiently using our framework.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/2482540.2482593
