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Title
Imprecise Uncertain Reasoning : A Distributional Approach
AuthorKleiter, Gernot D.
Published in
Frontiers in Psychology, Lausanne, 2018, Vol. 9, Issue article number 2051, page 1-16
PublishedLausanne : Frontiers, 2018
LanguageEnglish
Document typeJournal Article
Keywords (EN)uncertain reasoning / judgment under uncertainty / probability logic / imprecise probability / second-order distributions / coherence
ISSN1664-1078
URNurn:nbn:at:at-ubs:3-10403 Persistent Identifier (URN)
DOI10.3389/fpsyg.2018.02051 
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 The work is publicly available
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Imprecise Uncertain Reasoning [2.27 mb]
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Abstract (English)

The contribution proposes to model imprecise and uncertain reasoning by a mental probability logic that is based on probability distributions. It shows how distributions are combined with logical operators and how distributions propagate in inference rules. It discusses a series of examples like the Linda task, the suppression task, Doherty's pseudodiagnosticity task, and some of the deductive reasoning tasks of Rips. It demonstrates how to update distributions by soft evidence and how to represent correlated risks. The probabilities inferred from different logical inference forms may be so similar that it will be impossible to distinguish them empirically in a psychological study. Second-order distributions allow to obtain the probability distribution of being coherent. The maximum probability of being coherent is a second-order criterion of rationality. Technically the contribution relies on beta distributions, copulas, vines, and stochastic simulation.

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CC-BY-License (4.0)Creative Commons Attribution 4.0 International License