Results 11 to 20 of about 445,002 (378)
, 2018 In almost any domain of endeavour, successes can be attained through skill, but also by dumb luck. An archer’s wildest shots occasionally hit the target. Against enormous odds, some fair lottery tickets happen to win. The same goes in the case of purely cognitive or intellectual endeavours.
Broncano-Berrocal, Fernando +1 more
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From Epistemic Expressivism to Epistemic Inferentialism [PDF]
, 2010 Abstract This chapter explains my reasons for endorsing an inferentialist rather than an expressivist form of nondescriptivism about epistemic discourse. Epistemic inferentialism is the view that epistemic claims mean what they do in virtue of the inferential responsibilities and entitlements one commits to in making them, rather than ...
Chrisman, Matthew
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A Gentle Introduction to Epistemic Planning: The DEL Approach [PDF]
, 2017 Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning.
Thomas Bolander
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Epistemic Abstainers, Epistemic Martyrs, and Epistemic Converts [PDF]
Logos & Episteme, 2010 An intuitive view regarding the epistemic significance of disagreement says that when epistemic peers disagree, they should suspend judgment. This abstemious view seems to embody a kind of detachment appropriate for rational beings; moreover, it seems to
Scott F. Aikin +3 more
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A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement [PDF]
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 Neural networks are ubiquitous in many tasks, but trusting their predictions is an open issue. Uncertainty quantification is required for many applications, and disentangled aleatoric and epistemic uncertainties are best.
Matias Valdenegro-Toro, Daniel Saromo
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Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures? [PDF]
Conference on Uncertainty in Artificial Intelligence, 2022 The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning.
Eyke Hüllermeier
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Where is knowledge from the global South? An account of epistemic justice for a global bioethics
Journal of Medical Ethics, 2023 The silencing of the epistemologies, theories, principles, values, concepts and experiences of the global South constitutes a particularly egregious epistemic injustice in bioethics.
Bridget Pratt, J. de Vries
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PLoS ONE, 2023 The construct of epistemic trust has received much consideration in recent psychological literature, even though mainly from a theoretical perspective.
M. Liotti +9 more
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Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods [PDF]
Machine-mediated learning, 2019 The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the statistical tradition, uncertainty has long been perceived as almost synonymous with standard probability
Eyke Hüllermeier, W. Waegeman
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