Leveraging Possibilistic Beliefs in Unrestricted Combinatorial Auctions

Jing Chen and Silvio Micali
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Jing Chen: Department of Computer Science, Stony Brook University, Stony Brook, NY 11794, USA
Silvio Micali: Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA

Games, 2016, vol. 7, issue 4, 1-19

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.

Keywords: possibilistic beliefs; unrestricted combinatorial auctions; mutual belief of rationality; incomplete information; extensive-form games; distinguishable dominance (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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