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Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
arXiv - CS - Computer Science and Game Theory Pub Date : 2020-11-15 , DOI: arxiv-2011.07476 Shengjia Zhao, Stefano Ermon
arXiv - CS - Computer Science and Game Theory Pub Date : 2020-11-15 , DOI: arxiv-2011.07476 Shengjia Zhao, Stefano Ermon
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.
中文翻译:
从错误预测中做出正确决策:替代个体校准的机制设计
决策者通常需要依赖不完美的概率预测。虽然通常可以获得平均性能指标,但很难评估单个预测和相应实用程序的质量。为了向决策者传达对个人预测的信心,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。虽然可以利用一种天真的方案来补偿决策者的预测错误,并且从长远来看可能不可持续,但我们提出了一种基于公平赌注和在线学习的机制,该机制可证明无法利用。我们演示了一个应用程序,展示了乘客如何根据航空公司估计的航班延误概率自信地优化个人旅行计划。
更新日期:2020-11-17
中文翻译:
从错误预测中做出正确决策:替代个体校准的机制设计
决策者通常需要依赖不完美的概率预测。虽然通常可以获得平均性能指标,但很难评估单个预测和相应实用程序的质量。为了向决策者传达对个人预测的信心,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。虽然可以利用一种天真的方案来补偿决策者的预测错误,并且从长远来看可能不可持续,但我们提出了一种基于公平赌注和在线学习的机制,该机制可证明无法利用。我们演示了一个应用程序,展示了乘客如何根据航空公司估计的航班延误概率自信地优化个人旅行计划。