The acquisition of syntactic knowledge /

"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:...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Berwick, Robert C.
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cambridge, Mass. : MIT Press, �1985.
Σειρά:MIT Press series in artificial intelligence.
Θέματα:
Διαθέσιμο Online:http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=48982
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100 1 |a Berwick, Robert C. 
245 1 4 |a The acquisition of syntactic knowledge /  |c Robert C. Berwick. 
260 |a Cambridge, Mass. :  |b MIT Press,  |c �1985. 
300 |a 1 online resource (xii, 368 pages) :  |b illustrations. 
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490 1 |a The MIT Press series in artificial intelligence 
504 |a Includes bibliographical references (pages 343-353) and index. 
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533 |a Electronic reproduction.  |b [S.l.] :  |c HathiTrust Digital Library,  |d 2010.  |5 MiAaHDL 
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505 0 |a 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. 
520 3 |a "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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650 0 |a Artificial intelligence. 
650 0 |a Computational linguistics. 
650 0 |a Language acquisition. 
650 0 |a Learning  |x Mathematical models. 
650 6 |a Intelligence artificielle. 
650 6 |a Linguistique informatique. 
650 6 |a Langage  |x Acquisition. 
650 6 |a Apprentissage  |x Mod�eles math�ematiques. 
650 7 |a LANGUAGE ARTS & DISCIPLINES  |x Linguistics  |x Psycholinguistics.  |2 bisacsh 
650 7 |a Intelligence artificielle.  |2 eclas 
650 7 |a Grammaire.  |2 eclas 
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650 7 |a Computational linguistics.  |2 fast  |0 (OCoLC)fst00871998 
650 7 |a Language acquisition.  |2 fast  |0 (OCoLC)fst00992119 
650 7 |a Learning  |x Mathematical models.  |2 fast  |0 (OCoLC)fst00994836 
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650 1 7 |a Computers.  |2 gtt 
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