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Open AccessArticle

Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions

by Jing Chen 1,* and Silvio Micali 2
1
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794, USA
2
Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Paul Weirich
Games 2016, 7(4), 32; https://doi.org/10.3390/g7040032
Received: 9 August 2016 / Revised: 15 October 2016 / Accepted: 17 October 2016 / Published: 26 October 2016
(This article belongs to the Special Issue Epistemic Game Theory and Logic)
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. View Full-Text
Keywords: possibilistic beliefs; unrestricted combinatorial auctions; mutual belief of rationality; incomplete information; extensive-form games; distinguishable dominance possibilistic beliefs; unrestricted combinatorial auctions; mutual belief of rationality; incomplete information; extensive-form games; distinguishable dominance
MDPI and ACS Style

Chen, J.; Micali, S. Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions. Games 2016, 7, 32.

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