I-Cog: A computational framework for integrated cognition of higher cognitive abilities

Autor(en): Kühnberger, K.-U. 
Wandmacher, T.
Schwering, A.
Ovchinnikova, E.
Krumnack, U. 
Gust, H.
Geibel, P.
Stichwörter: Computational methods; Data reduction; Knowledge based systems, Analogical reasoning; Inconsistent data; Neurosymbolic interfaces, Artificial intelligence
Erscheinungsdatum: 2007
Herausgeber: Springer Verlag
Enthalten in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band: 4827 LNAI
Startseite: 203
Seitenende: 214
There are several challenges for AI models of higher cognitive abilities like the profusion of knowledge, different forms of reasoning, the gap between neuro-inspired approaches and conceptual representations, the problem of inconsistent data, and the manifold of computational paradigms. The I-Cog architecture - proposed as a step towards a solution for these problems - consists of a reasoning device based on analogical reasoning, a rewriting mechanism operating on the knowledge base, and a neuro-symbolic interface for robust learning from noisy data. I-Cog is intended as a framework for human-level intelligence (HLI). © Springer-Verlag Berlin Heidelberg 2007.
Conference of 6th Mexican International Conference on Artificial Intelligence, MICAI 2007 ; Conference Date: 4 November 2007 Through 10 November 2007; Conference Code:71204
ISBN: 9783540766308
ISSN: 03029743
DOI: 10.1007/978-3-540-76631-5_20
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-38149113932&doi=10.1007%2f978-3-540-76631-5_20&partnerID=40&md5=88c95dbfb10c89db2dfdabed72ab445f

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