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Ling, 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

Langley, Pat – Cognitive Science, 1985
Examines processes by which general but weak search methods are transformed into powerful, domain-specific search strategies by classifying types of heuristics learning that can occur and components that contribute to such learning. A learning system--SAGE.2--and its structure, behavior in different domains, and future directions are explored. (36…
Descriptors: Artificial Intelligence, Computer Software, Design, Heuristics