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Acquiring minimalist grammars via constraint satisfaction

Author(s)
Indurkhya, Sagar
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Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Robert C. Berwick.
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M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
This thesis shows how to algorithmically construct a Minimalist Grammar lexicon that produces a specified set of MG derivations. This thesis introduces a mathematical structure, a Collection of Constraints, that captures the logical constraints, including those that arise as a consequence of the shortest move constraint, imposed upon the syntactic features of lexical items as they are merged together in a derivation produced by a given Minimalist Grammar lexicon. Methods are then developed that (a) map Minimalist Grammar lexicons to be Collections of Constraints, (b) map Collections of Constraints to Minimalist Grammar lexicons and (c) may combine two or more Collections of Constraints into a single Collection of Constraints. The thesis then demonstrates via a series of examples, framed as a simplified acquisition process, how these methods may be used together to iteratively construct a Minimalist Grammar lexicon starting from an empty Collection of Constraints and a sequence of Minimalist Grammar derivations, such that the constructed lexicon is able to generate the set of derivations.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 77-78).
 
Date issued
2015
URI
http://hdl.handle.net/1721.1/106114
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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