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Games 2016, 7(4), 32; doi:10.3390/g7040032

Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions

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
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)
View Full-Text   |   Download PDF [309 KB, uploaded 26 October 2016]

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. 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
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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

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