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Peer reviewedLing, Charles X.; Marinov, Marin – Cognitive Science, 1994
Challenges Smolensky's theory that human intuitive/nonconscious cognitive processes can only be accurately explained in terms of subsymbolic computations in artificial neural networks. Symbolic learning models of two cognitive tasks involving nonconscious acquisition of information are presented: learning production rules and artificial finite…
Descriptors: Grammar, Intuition, Learning Processes, Mathematical Formulas
Stone, Matthew – Cognitive Science, 2004
I show how a conversational process that takes simple, intuitively meaningful steps may be understood as a sophisticated computation that derives the richly detailed, complex representations implicit in our knowledge of language. To develop the account, I argue that natural language is structured in a way that lets us formalize grammatical…
Descriptors: Language Usage, Semantics, Intuition, Grammar

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