The Acquisition of Syntactic Knowledge (Artificial Intelligence Ser.)

Berwick, Robert C.

ISBN 10: 0262022265 / ISBN 13: 9780262022262

Published by M I T Press, Cambridge, MA, U.S.A., 1985

About this Item

Seller Inventory # 7743

Bibliographic Details

• Title: The Acquisition of Syntactic Knowledge (Artificial Intelligence Ser.)
• Publisher: M I T Press, Cambridge, MA, U.S.A.
• Publication Date: 1985
• Language: English
• ISBN 10: 0262022265
• ISBN 13: 9780262022262
• Binding: Hard Cover
• Condition: Near Fine
• Dust Jacket Condition: Very Good
• Seller catalogs:
  • Science, Math, Natural History

About this title

Synopsis

This landmark work in computational linguistics is of great importance both theoretically and practically because it shows that much of English grammar can be learned by a simple program. The Acquisition of Syntactic Knowledge investigates the central questions of human and machine cognition: How do people learn language? How can we get a machine to learn language? It first presents an explicit computational model of language acquisition which can actually learn rules of English syntax given a sequence of grammatical, but otherwise unprepared, sentences. It shows that natural languages are designed to be easily learned and easily processed-an exciting breakthrough from the point of view of artificial intelligence and the design of expert systems because it shows how extensive knowledge might be acquired automatically, without outside intervention. Computationally, the book demonstrates how constraints that may be reasonably assumed to aid sentence processing also aid language acquisition. Chapters in the book's second part apply computational methods to the general problem of developmental growth, particularly the thorny problem of the interaction between innate genetic endowment and environmental input, with the intent of uncovering the constraints on the acquisition of syntactic knowledge. A number of "mini-theories" of learning are incorporated in this study of syntax with results that should appeal to a wide range of scholarly interests. These include how lexical categories, phonological rule systems, and phrase structure rules are learned; the role of semantic-syntactic interaction in language acquisition; how a "parameter setting" model may be formalized as a learning procedure; how multiple constraints (from syntax, thematic knowledge, or phrase structure) interact to aid acquisition; how transformational-type rules may be learned; and, the role of lexical ambiguity in language acquisition.

The Acquisition of Syntactic Knowledge is sixteenth in the Artificial Intelligence Series, edited by Patrick Winston and Michael Brady.

About the Author

Robert C. Berwick is Professor of Computational Linguistics and Computer Science and Engineering, in the Laboratory for Information and Decision Systems and the Institute for Data, Systems, and Society at MIT and the author of Computational Complexity and Natural Language and The Acquisition of Syntactic Knowledge, both published by the MIT Press.