Incentives for Truthful Information Elicitation of Continuous Signals

We consider settings where a collective intelligence is formed by aggregating information contributed from many independent agents, such as product reviews, community sensing, or opinion polls. We propose a novel mechanism that elicits both private signals and beliefs. The mechanism extends the previous versions of the Bayesian Truth Serum (the original BTS, the RBTS, and the multi-valued BTS), by allowing small populations and non-binary private signals, while not requiring additional assumptions on the belief updating process. For priors that are sufficiently smooth, such as Gaussians, the mechanism allows signals to be continuous.


Published in:
Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14), 770-776
Presented at:
The 28th AAAI Conference on Artificial Intelligence (AAAI'14)
Year:
2014
Laboratories:




 Record created 2016-02-09, last modified 2018-03-17

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