Kay-Yut Chen, Leslie R. Fine, Bernardo A. Huberman
HP Laboratories
Palo Alto, CA 94304
Abstract
We present a novel methodology for identifying public knowledge and
eliminating the biases it creates when aggregating information in small group
settings. A two-stage mechanism consisting of an information market and
a coordination game is used to reveal and adjust for individuals' public
information. A nonlinear aggregation of their decisions then allows for
the calculation of the probability of the future outcome of an uncertain
event, which can then be compared to both the objective probability of its
occurrence and the performance of the market as a whole. Experiments
show that this nonlinear aggregation mechanism outperforms both the imperfect
market and the best of the participants.
Full paper: publicinfo.pdf
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