Incentives for Subjective Evaluations with Private Beliefs

The modern web critically depends on aggregation of information from self-interested agents, for example opinion polls, product ratings, or crowdsourcing. We consider a setting where multiple objects (questions, products, tasks) are evaluated by a group of agents. We first construct a minimal peer prediction mechanism that elicits honest evaluations from a homogeneous population of agents with different private beliefs. Second, we show that it is impossible to strictly elicit honest evaluations from a heterogeneous group of agents with different private beliefs. Nevertheless, we provide a modified version of a divergence-based Bayesian Truth Serum that incentivizes agents to report consistently, making truthful reporting a weak equilibrium of the mechanism.


Published in:
Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15), 1014-1020
Presented at:
The 29th AAAI Conference on Artificial Intelligence (AAAI'15)
Year:
2015
Laboratories:




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

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