Modeling human-level intelligence by integrated cognition in a hybrid architecture

Autor(en): Kühnberger, K.-U. 
Wandmacher, T.
Schwering, A.
Ovchinnikova, E.
Krumnack, U. 
Gust, H.
Geibel, P.
Stichwörter: Analogical reasoning; Cognitive ability; Computational paradigm; Hybrid architectures; Inconsistent data; Knowledge base; Modular system; Robust learning, Knowledge based systems, Artificial intelligence
Erscheinungsdatum: 2007
Enthalten in: CEUR Workshop Proceedings
Band: 277
Zusammenfassung: 
Various forms of reasoning, the profusion of knowledge, the gap between neuro-inspired approaches and conceptual representations, the problem of inconsistent data input, and the manifold of computational paradigms for solutions of these problems challenge AI models for higher cognitive abilities. We propose the I-Cog architecture as a step towards a solution for these problems. I-Cog is a modular system that is composed of a reasoning device based on analogical reasoning, a rewriting mechanism for the ontological knowledge base, and a neuro-symbolic interface for robust learning from noisy and inconsistent data.
Beschreibung: 
Conference of Foundations of Artificial Intelligence, FAInt 2007 - Workshop at KI 2007 ; Conference Date: 10 September 2007 Through 10 September 2007; Conference Code:99871
ISSN: 16130073
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84885008993&partnerID=40&md5=dca8841ec7d964432d0ed54cc811f2f7

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