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Towards a constructivist methodology: learning constructions by integrating in situ representations and productivity

Journal of Artificial General Intelligence's Cover Image
Journal of Artificial General Intelligence
Self-Programming and Constructivist Methodologies for AGI, Editors: Kristinn R. Thórisson, Eric Nivel and Ricardo Sanz
À propos de cet article

The ability to learn constructions may be important for the development of a self-organizing architecture for artificial general intelligence. Constructions are structural relations between more specific or more abstract conceptual representations. They can be derived from the processes of alignment, collocations and distributed equivalences. An architecture that integrates in situ grounded representations with cognitive productivity is ideally suited to learn constructions. This paper described such an architecture, based on neuronal assembly structures and neuronal ’blackboards’ for grounded compositional representations. The paper outlines how constructions could be learned in such an architecture and how the architecture could eventually develop into an autonomous self-organizing architecture for artificial general intelligence.

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Sujets de la revue:
Computer Sciences, Artificial Intelligence