Perspectives of Neuro-Symbolic Integration - Extended Abstract - Extended A

Autor(en): Kühnberger, Kai-Uwe 
Gust, Helmar
Geibel, Peter
Herausgeber: De Raedt, L.
Hammer, B.
Hitzler, P.
Maass, W.
Stichwörter: Extended abstracts; First order; First order logic; First-Order Logic; Formal logic; Integration; Neural learning; Neuro-Symbolic Integration; Sub-symbolic; Sub-symbolic approach; Symbolic integration; Symbolic level; Topos Theory
Erscheinungsdatum: 2008
Herausgeber: Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Journal: Dagstuhl Seminar Proceedings
Volumen: 8041
Zusammenfassung: 
There is an obvious tension between symbolic and subsymbolic theories, because both show complementary strengths and weaknesses in corresponding applications and underlying methodologies. The resulting gap in the foundations and the applicability of these approaches is theoretically unsatisfactory and practically undesirable. We sketch a theory that bridges this gap between symbolic and subsymbolic approaches by the introduction of a Topos-based semi-symbolic level used for coding logical first-order expressions in a homogeneous framework. This semi-symbolic level can be used for neural learning of logical firstorder theories. Besides a presentation of the general idea of the framework, we sketch some challenges and important open problems for future research with respect to the presented approach and the field of neurosymbolic integration, in general. © 2008 Dagstuhl Seminar Proceedings. All rights reserved.
Beschreibung: 
Cited by: 0; Conference name: Recurrent Neural Networks - Models, Capacities, and Applications 2008; Conference date: 20 January 2008 through 25 January 2008; Conference code: 178484
ISSN: 1862-4405
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174822262&partnerID=40&md5=b72c42f03429a737148ec1f06addb2b1

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