The acquisition of syntactic knowledge / Robert C. Berwick.
Τύπος υλικού: ΚείμενοΣειρά: MIT Press series in artificial intelligenceΛεπτομέρειες δημοσίευσης: Cambridge, Mass. : MIT Press, �1985.Περιγραφή: 1 online resource (xii, 368 pages) : illustrationsΤύπος περιεχομένου:- text
- computer
- online resource
- 0585368910
- 9780585368917
- 0262268396
- 9780262268394
- Artificial intelligence
- Computational linguistics
- Language acquisition
- Learning -- Mathematical models
- Intelligence artificielle
- Linguistique informatique
- Langage -- Acquisition
- Apprentissage -- Mod�eles math�ematiques
- LANGUAGE ARTS & DISCIPLINES -- Linguistics -- Psycholinguistics
- Intelligence artificielle
- Grammaire
- Artificial intelligence
- Computational linguistics
- Language acquisition
- Learning -- Mathematical models
- Taalverwerving
- Computers
- Syntax
- Spracherwerb
- Datenverarbeitung
- Computersimulation
- K�unstliche Intelligenz
- Computational linguistics Grammatical aspects
- 401.9 19
- Q335 .B48 1985eb
- 54.72
- 17.01
- 17.46
- digitized 2010 committed to preserve
Includes bibliographical references (pages 343-353) and index.
Print version record.
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Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. MiAaHDL
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digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL
pt. 1. The computer model. Computation and language acquisition ; The acquisition model ; Learning phrase structure ; Learning transformations -- pt. 2. A theory of acquisition. Acquisition complexity ; Learning theory: applications ; Locality principles and acquisition.
"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. Robert Berwick is an assistant professor in the Department of Electrical Engineering and Computer Science at MIT. The Acquisition of Syntactic Knowledge is sixteenth in the Artificial Intelligence Series, edited by Patrick Winston and Michael Brady."
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