Deep Learning (DL) methods have been transforming computer vision with innovative adaptations to other domains including climate change. For DL to pervade Science and Engineering (S&E) applications where risk management is a core component, wellcharacterized uncertainty estimates must accompany predictions. However, S&E observations and model-simulations often follow heavily skewed distribution...

A concept we call Total Uncertainty will be used to illustrate how we combine both aleatoric (reducible) and epistemic (non-reducible) uncertainties in a given problem to assess the confidence an analyst can have in his/her decisions. In illustrating the utility of our concept of total uncertainty we hypothesize that all uncertainty, including our metric of TU, should scale between two extreme ...

The paper discusses the role of uncertainty in decision making involving spatially distributed systems. It focuses on engineering structures, but draws on experience with other distributed systems. Uncertainty is divided into measurable (aleatoric), modelling (epistemic) and surprisal (ontological), and the primary emphasis is on the latter. All three are involved in decision making, and the pr...

Epistemic uncertainty is a huge area of scholarship. It has captured the minds of scholars in psychology and many domain-specific studies of reasoning and problem solving. What does it mean to resolve uncertainty? This chapter explores the idea that resolution of uncertainty in complex science and engineering fields frequently ends with approximations rather than precise answers. The chapter be...

Nowadays, the need to treat both epistemic and aleatory uncertainty in a unified framework is well recognized [1]. One method to do so is to mix probabilistic convolution (for aleatory uncertainty) and fuzzy calculus (for epistemic uncertainty). Existing propositions either concern simple models [2] or are computationally very costly [3] (a luxury not always affordable, especially in nuclear sa...

In risk analysis, the treatment of the epistemic uncertainty associated to the probability of occurrence of an event is fundamental. Traditionally, probabilistic distributions have been used to characterize the epistemic uncertainty due to imprecise knowledge of the parameters in risk models. On the other hand, it has been argued that in certain instances such uncertainty may be best accounted ...

Flood disaster mitigation strategies should be based on a comprehensive assessment of the flood risk combined with a thorough investigation of the uncertainties associated with the risk assessment procedure. Within the ‘German Research Network of Natural Disasters’ (DFNK) the working group ‘Flood Risk Analysis’ investigated the flood process chain from precipitation, runoff generation and conce...

We propose some variants of a multi-modal logic of joint action, preference and knowledge that support reasoning about epistemic games in strategic form. The first part of the paper deals with games with complete information. We first provide syntactic proofs of some theorems that are well-known in the area of interactive epistemology and that specify some sufficient epistemic conditions of equ...