000 | 04177nam a2200529 i 4500 | ||
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001 | 6267371 | ||
003 | IEEE | ||
005 | 20220712204644.0 | ||
006 | m o d | ||
007 | cr |n||||||||| | ||
008 | 151223s1985 maua ob 001 eng d | ||
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_a9780262268394 _qebook |
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020 |
_z0585368910 _qelectronic |
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020 |
_z9780585368917 _qelectronic |
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020 |
_z0262268396 _qelectronic |
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020 |
_z9780262022262 _qprint |
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035 | _a(CaBNVSL)mat06267371 | ||
035 | _a(IDAMS)0b000064818b4375 | ||
040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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050 | 4 |
_aQ335 _b.B48 1985eb |
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100 | 1 |
_aBerwick, Robert C., _eauthor. _921632 |
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245 | 1 | 4 |
_aThe acquisition of syntactic knowledge / _cRobert C. Berwick. |
264 | 1 |
_aCambridge, Massachusetts : _bMIT Press, _cc1985. |
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264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[1985] |
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300 |
_a1 PDF (xii, 368 pages) : _billustrations. |
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_atext _2rdacontent |
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_aelectronic _2isbdmedia |
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_aonline resource _2rdacarrier |
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490 | 1 | _aThe MIT Press series in artificial intelligence | |
504 | _aIncludes bibliographical references (p. [343]-353) and index. | ||
506 | 1 | _aRestricted to subscribers or individual electronic text purchasers. | |
520 | _aThis 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. | ||
530 | _aAlso available in print. | ||
538 | _aMode of access: World Wide Web | ||
588 | _aDescription based on PDF viewed 12/23/2015. | ||
650 | 0 |
_aLearning _xMathematical models. _922082 |
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650 | 0 |
_aLanguage acquisition. _922403 |
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650 | 0 |
_aComputational linguistics. _96146 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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655 | 0 |
_aElectronic books. _93294 |
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710 | 2 |
_aIEEE Xplore (Online Service), _edistributor. _922404 |
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710 | 2 |
_aMIT Press, _epublisher. _922405 |
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776 | 0 | 8 |
_iPrint version _z9780262022262 |
830 | 0 |
_aMIT Press series in artificial intelligence. _921636 |
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856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267371 |
942 | _cEBK | ||
999 |
_c73026 _d73026 |