Derives cost-adjusted bounds on the reward-penalty ratio for incentive compatibility and individual rationality in binary aggregation without verification, maps feasible regions, and states a conditional all-conforming Nash equilibrium.
A technical survey on statistical modelling and design methods for crowdsourcing quality control.Artificial Intelligence, 287:103351, 2020
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A Tunable Incentive Mechanism for Binary Aggregation Without Verification
Derives cost-adjusted bounds on the reward-penalty ratio for incentive compatibility and individual rationality in binary aggregation without verification, maps feasible regions, and states a conditional all-conforming Nash equilibrium.