Abstract
Abstract : This paper focuses on the nature of representations in connectionist models. It addresses two issues: Can connectionist models develop representations which possess internal structure and which provide the basis for productive and systematic behavior; and Can representations which are fundamentally context-sensitive support grammatical behavior which appears to be abstract and general? Results from two simulations are reported.. The simulations address problems in the distinction between type and token, the representation of lexical categories, and the representation of grammatical structure. The results suggest that connectionist representations can indeed possess internal structure and enable systematic behavior, and that a mechanism which is sensitive to context is capable of capturing generalizations of varying degrees of abstractness.
Keywords
ConnectionismRepresentation (politics)Context (archaeology)Computer scienceSecurity tokenArtificial intelligenceCognitive scienceNatural language processingArtificial neural networkPsychology
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Publication Info
- Year
- 1989
- Type
- report
- Citations
- 179
- Access
- Closed
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Cite This
Jeffrey L. Elman
(1989).
Representation and Structure in Connectionist Models.
.
https://doi.org/10.21236/ada259504
Identifiers
- DOI
- 10.21236/ada259504