Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called “confidence approach” to tackle decision-making under severe uncertainty with multiple models, and illustrate the approach with a case study: insurance pricing using hurricane models. The confidence approach has important consequences for this case and offers a powerful framework for a wide class of problems. We end by discussing different ways in which model ensembles can feed information into the approach, appropriate to different collections of models.

中文翻译：

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使用模型集成做出自信的决策

许多政策决定都从科学模型的集合中获取输入。此类决策面临着重大且往往知之甚少的不确定性。我们重新设计了所谓的“置信度方法”，以使用多种模型来解决严重不确定性下的决策问题，并通过案例研究说明该方法：使用飓风模型的保险定价。置信方法对此案例具有重要意义，并为各种问题提供了强大的框架。我们最后讨论模型集成可以将信息提供给方法的不同方式，适用于不同的模型集合。