Reference : Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural Symbolic Com...
Scientific journals : Article
Engineering, computing & technology : Computer science
Reasoning in Non-probabilistic Uncertainty: Logic Programming and Neural Symbolic Computing as Examples
Besold, Tarek mailto [University of Bremen > Digital Media Lab]
Garcez, Artur d'Avila mailto [City, University of London > Department of Computer Science]
Stenning, Keith mailto [University of Edinburgh > School of Informatics]
van der Torre, Leon mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
van Lambalgen, Michiel mailto [University of Amsterdam > Faculty of Humanities > Logic and Language]
Minds and Machines
[en] Uncertainty in reasoning ; Interpretation ; Logic programming ; Dynamic norms ; Neural-symbolic integration
[en] This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty (and even more, that there are kinds of uncertainty which are for principled reasons not addressable with probabilistic means); and to provide evidence that logic-based methods can well support reasoning with uncertainty. For the latter claim, two paradigmatic examples are presented: logic programming with Kleene semantics for modelling reasoning from information in a discourse, to an interpretation of the state of affairs of the intended model, and a neural-symbolic implementation of input/output logic for dealing with uncertainty in dynamic normative contexts.

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