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Exploring Deep Uncertainty Approaches for Application in Life Cycle Engineering

机译：探索深度不确定性方法在生命周期工程中的应用

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Uncertainty assessment and management, as well as the associated decision making are increasingly important in a variety of scientific fields. While uncertainty analysis has a long tradition, meeting sustainable development goals through long-term Life Cycle Engineering (LCE) decision making demands addressing Deep Uncertainty (DU). DU characterizes situations where there is no agreement on exact causal structures, let alone probabilities. In this case traditional, probability based approaches cannot produce reliable results, as there is a lack of information and experts are unlikely to agree upon probabilities. Due to the nature of LCE, this paper argues that methods to better cope with DU can make a significant contribution to the management of LCE. We introduce a set of methods that use computational experiments to analyze DU and have been successfully applied in other fields. We describe Robust Decision Making (RDM) as the most promising approach for addressing DU challenges in LCE. We then illustrate the difference between applying traditional risk management approaches and RDM through an example, complemented with the interview findings from a company using RDM. We conclude with a discussion on future research directions.
机译：不确定性评估和管理以及相关的决策在各种科学领域中变得越来越重要。尽管不确定性分析具有悠久的历史，但通过长期生命周期工程（LCE）决策制定需求来解决深层不确定性（DU）来实现可持续发展目标。 DU的特征是在确切的因果结构上没有达成共识，更不用说概率了。在这种情况下，传统的基于概率的方法无法产生可靠的结果，因为缺少信息，专家不太可能就概率达成共识。由于LCE的性质，本文认为更好地应对DU的方法可以对LCE的管理做出重大贡献。我们介绍了一组使用计算实验来分析DU的方法，这些方法已成功应用于其他领域。我们将稳健决策（RDM）描述为解决LCE中DU挑战的最有前途的方法。然后，我们通过一个例子来说明应用传统风险管理方法与RDM之间的区别，并辅以一家使用RDM的公司的采访结果。最后，我们讨论了未来的研究方向。

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