<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

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

Technical Cognition, CTIT, University of Twente, P.O. Box 217, Enschede, 7500 AE, The Netherlands

IOP, Leiden University Leiden, 2333 AH, The Netherlands

Journal of Artificial General Intelligence

The ability to learn constructions may be important for the development of a self-organizing
architecture for artificial general intelligence. Constructions...

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

Online veröffentlicht: 04. Jan. 2013

Seitenbereich: 101 - 121

DOI: https://doi.org/10.2478/v10229-011-0019-z

Schlüsselwörter
Constructions, in situ representations, cognitive productivity, compositional structures, neuronal assemblies, neural blackboards

This content is open access.