Mapping across domains without feedback: A neural network model of transfer of implicit knowledge
Exposure to exemplars of an artificial grammar allows subjects to decide subsequently whether a novel sequence does or does not belong to the same grammar , If subjects are exposed to exemplars of an artificial grammar in one domain (e.g. sequences of tones differing in pitch), subjects can later classify novel sequences in another domain (e.g. sequences of letters). This paper introduces a version of the Simple Recurrent Network (SRN) that can also transfer its knowledge of artificial grammars across domains without feedback. The performance of the model is sensitive to at least some of the same variables that affect subjects’ performance in ways not predicted by other theories.
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