从错误的预测中做出正确的决定：一种替代个体校准的机制设计
Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
摘要：
决策者往往需要依赖不完美的概率预测。虽然平均性能指标通常是可用的，但很难评估单个预测和相应实用程序的质量。为了向决策者传达个人预测的信心，我们提出了一种补偿机制，确保预测效用与实际应计效用相匹配。虽然可以利用一个天真的计划来补偿决策者的预测错误，但从长远来看可能是不可持续的，我们提出了一种基于公平赌注和在线学习的机制，可以证明这是不能利用的。我们展示了一个应用程序，显示乘客如何自信地优化个人旅行计划的基础上，由航空公司估计的航班延误概率。
英文摘要：
Decision makers often need to rely on imperfect probabilistic forecasts. While average performance metrics are typically available, it is difficult to assess the quality of individual forecasts and the corresponding utilities. To convey confidence about individual predictions to decision-makers, we propose a compensation mechanism ensuring that the forecasted utility matches the actually accrued utility. While a naive scheme to compensate decision-makers for prediction errors can be exploited and might not be sustainable in the long run, we propose a mechanism based on fair bets and online learning that provably cannot be exploited. We demonstrate an application showing how passengers could confidently optimize individual travel plans based on flight delay probabilities estimated by an airline.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
