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Realizing the Now-or-Never bottleneck and Chunk-and-Pass processing with Item-Order-Rank working memories and masking field chunking networks

Published online by Cambridge University Press:  02 June 2016

Stephen Grossberg*
Affiliation:
Center for Adaptive Systems, Boston University, Boston, MA 02215. steve@bu.eduhttp://cns.bu.edu/~steve

Abstract

Christiansen & Chater's (C&C's) key goals for a language system have been realized by neural models for short-term storage of linguistic items in an Item-Order-Rank working memory, which inputs to Masking Fields that rapidly learn to categorize, or chunk, variable-length linguistic sequences, and choose the contextually most predictive list chunks while linguistic inputs are stored in the working memory.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2016 

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