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This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession of a few general and uniform principles. The paper also provides a unifying thread to a variety of recent approaches to natural language comprehension. We conclude with a brief discussion of how Artificial Intelligence may have a radical impact on education if the principles which it utilizes to explore the representation and use of knowledge are made available to the student to use in his own learning experiences.
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Goldstein et al. (Sat,) studied this question.
synapsesocial.com/papers/6a18febdacdd6f4dc9d30f22 — DOI: https://doi.org/10.1207/s15516709cog0101_5
Ira Goldstein
Albany State University
Seymour Papert
University of Geneva
Cognitive Science
Massachusetts Institute of Technology
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