Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions
Name
Chen-2016-Leveraging possibilistic beliefs in.pdf
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309.07 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Chen, Jing
Micali, Silvio
Date Issued
October 2016
Journal
Games
Publisher
MDPI AG
Citation
Chen, Jing, and Silvio Micali. “Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions.” Games 7, no. 4 (October 26, 2016): 32.
Version
Final published version
Abstract
In unrestricted combinatorial auctions, we put forward a mechanism that guarantees a meaningful revenue benchmark based on the possibilistic beliefs that the players have about each other’s valuations. In essence, the mechanism guarantees, within a factor of two, the maximum revenue that the “best informed player” would be sure to obtain if he/she were to sell the goods to his/her opponents via take-it-or-leave-it offers. Our mechanism is probabilistic and of an extensive form. It relies on a new solution concept, for analyzing extensive-form games of incomplete information, which assumes only mutual belief of rationality. Moreover, our mechanism enjoys several novel properties with respect to privacy, computation and collusion.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/g7040032
