Abstract
Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and the representation of complex concepts.
Keywords
ConnectionismComputer scienceRepresentation (politics)Cognitive scienceExtension (predicate logic)Massively parallelCognitionArtificial intelligenceInformation processingTheoretical computer scienceArtificial neural networkPsychologyCognitive psychologyProgramming language
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Publication Info
- Year
- 1982
- Type
- article
- Volume
- 6
- Issue
- 3
- Pages
- 205-254
- Citations
- 1322
- Access
- Closed
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Cite This
Jerome A. Feldman,
D.H. Ballard
(1982).
Connectionist Models and Their Properties.
Cognitive Science
, 6
(3)
, 205-254.
https://doi.org/10.1207/s15516709cog0603_1
Identifiers
- DOI
- 10.1207/s15516709cog0603_1