This article addresses the question whether epistemic emotions (such as surprise, curiosity, uncertainty, and feelings of knowing) are in any sense inherently metacognitive. The paper begins with some critical discussion of a recent suggestion made by Joelle Proust, that these emotions might be implicitly or procedurally metacognitive. It then explores the theoretical resources that are needed ...

 The evaluation of uncertainties according to the „„Guide to the Expression of Uncertainty in Measurement‟‟ is presented in this study based on a novel Fuzzy-randomvariables approach. Whereas the classically proposed methods like Monte Carlo techniques treat all uncertainties as having a random nature, the fuzzy technique distinguishes between aleatoric and epistemic uncertainties. The aleator...

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...

Design optimization can lead to structures, which are susceptible to even small uncertainties especially in terms of stability. Stability against buckling is a response, which is critical to structural integrity. The consideration of uncertainty is vital to understanding the behavior of the real structure as uncertainties are unavoidable. In this study fuzzy models for imprecise material and lo...

This article presents a unifying framework to uncertainty quantification for systems subject to several design requirements that depend polynomially on both aleatory and epistemic uncertainties. This methodology, which is based on the Bernstein expansions of polynomials, enables calculating bounding intervals for the range of means, variances and failure probabilities of response metrics corres...

We consider a model for the risk-based design of a flood protection dike, and use probability distributions to represent aleatory uncertainty and possibility distributions to describe the epistemic uncertainty associated to the poorly known parameters of such probability distributions. A hybrid method is introduced to hierarchically propagate the two types of uncertainty, and the results are co...

An approach to the conversion of regulatory requirements into a conceptual and computational structure that permits meaningful uncertainty and sensitivity analyses is descibed. This approach is predicated on the description of the desired analysis in terms of three basic entities: (i) a probability space characterizing aleatory uncertainty, (ii) a probability space characterizing epistemic unce...

Argumentation can be modelled at an abstract level using an argument graph (i.e. a directed graph where each node denotes an argument and each arc denotes an attack by one argument on another). Since argumentation involves uncertainty, it is potentially valuable to consider how this can quantified in argument graphs. In this talk, we will consider two probabilistic approaches for modeling uncer...

The ability to monitor epistemic uncertainty is critical for selfdirected learning. However, we still know little about young children’s ability to detect uncertainty in their mental representations. Here we asked whether a spontaneous information gathering behavior – social referencing – is driven by uncertainty during early childhood. Children ages 2-5 completed a word-learning task in which ...

The literature on knowledge, belief, and uncertainty in artificial intelligence is divided into two broad classes. In epistemic logic (Hintikka 1961, Halpern & Fagin & Moses & Vardi 1995), belief revision theory (Alchourrón & Gärdenfors & Makinson 1985, Gärdenfors 1988, Rott 2001), and nonmonotonic reasoning (Kraus & Lehmann & Magidor 1990, Makinson 2005) qualitative approaches are used to repr...