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LEADER 00000cam 2200685Li 4500
001 47009246
003 OCoLC
005 20161209100108.6
006 m o d
007 cr cn|||||||||
008 010430s1985 maua ob 001 0 eng d
019 608989758|a827012745|a957385703
020 0585368910|q(electronic bk.)
020 9780585368917|q(electronic bk.)
020 0262268396|q(electronic bk.)
020 9780262268394|q(electronic bk.)
020 |z0262022265
020 |z9780262022262
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|z(OCoLC)957385703
040 N$T|beng|epn|erda|cN$T|dOCL|dOCLCQ|dYDXCP|dOCLCQ|dIEEEE
|dOCLCF|dOCLCE|dOCLCO|dOCLCQ|dYDX|dHRM|dOCLCQ
042 dlr
049 MAIN
050 4 Q335|b.B48 1985eb
072 7 LAN|x009040|2bisacsh
082 04 401.9|219
100 1 Berwick, Robert C.|0http://id.loc.gov/authorities/names/
n82133549
245 14 The acquisition of syntactic knowledge /|cRobert C.
Berwick.
264 1 Cambridge, Mass. :|bMIT Press,|c[1985]
264 4 |c©1985
300 1 online resource (xii, 368 pages) :|billustrations.
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
340 |gpolychrome|2rdacc|0http://rdaregistry.info/termList/
RDAColourContent/1003
347 text file|2rdaft|0http://rdaregistry.info/termList/
fileType/1002
490 1 The MIT Press series in artificial intelligence
504 Includes bibliographical references (pages 343-353) and
index.
505 0 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.
506 |3Use copy|fRestrictions unspecified|2star|5MiAaHDL
520 3 "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."
533 Electronic reproduction.|b[S.l.] :|cHathiTrust Digital
Library,|d2010.|5MiAaHDL
538 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.|uhttp://purl.oclc.org/DLF/benchrepro0212
|5MiAaHDL
583 1 digitized|c2010|hHathiTrust Digital Library|lcommitted to
preserve|2pda|5MiAaHDL
583 1 digitized|c2010|hHathiTrust Digital Library|lcommitted to
preserve|2pda|5MiAaHDL
588 0 Print version record.
650 0 Artificial intelligence.|0http://id.loc.gov/authorities/
subjects/sh85008180
650 0 Computational linguistics.|0http://id.loc.gov/authorities/
subjects/sh85077224
650 0 Language acquisition.|0http://id.loc.gov/authorities/
subjects/sh85074511
650 0 Learning|xMathematical models.|0http://id.loc.gov/
authorities/subjects/sh85075522
653 Computational linguistics|aGrammatical aspects
655 4 Electronic books.
776 08 |iPrint version:|aBerwick, Robert C.|tAcquisition of
syntactic knowledge.|dCambridge, Mass. : MIT Press, ©1985
|z0262022265|w(DLC) 85011460|w(OCoLC)12104043
830 0 MIT Press series in artificial intelligence.|0http://
id.loc.gov/authorities/names/n42016678
956 40 |uhttp://proxy.opal-libraries.org/login?url=http://
search.ebscohost.com/login.aspx?direct=true&scope=site&
db=nlebk&AN=48982|zView online
990 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America|c2016-12-09|yMaster record
variable field(s) change: 505 - Master record encoding
level change
990 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America|c2016-09-02|yMaster record
variable field(s) change: 505, 650
990 eBooks on EBSCOhost|bEBSCO eBook Subscription Academic
Collection - North America|c2016-04-08|yMaster record
variable field(s) change: 245
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