Are Feedforward and Recurrent Networks Systematic? Analysis and Implications for a Connectionist Cognitive Architecture
Author:
Steven Phillips
DOI:
10.1080/095400998116549
Publication Frequency:
4 issues per year
Subjects:
Cognitive Artificial Intelligence.;
Cognitive Psychology;
Cognitive Science;
Computational Linguistic & Language Recognition;
Connectionism/Neural Nets;
Cybernetics;
Formats available:
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(English)
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Abstract
Human cognition is said to be systematic: cognitive ability generalizes to structurally related behaviours. The connectionist approach to cognitive theorizing has been strongly criticized for its failure to explain systematicity. Demonstrations of generalization notwithstanding, I show that two widely used networks (feedforward and recurrent) do not support systematicity under the condition of local input/output representations. For a connectionist explanation of systematicity, these results leave two choices: either (1) develop models capable of systematicity under local input/output representations or (2) justify the choice of similarity-based (non-local) component representations sufficient for systematicity.
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| Keywords: Systematicity; Architecture; Feedforward; Recurrent |
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