Journal of Linguistics

Journal of Linguistics (2005), 41:3:513-569 Cambridge University Press
Copyright © 2005 Cambridge University Press
doi:10.1017/S0022226705003439

The Subset Principle in syntax: costs of compliance 1


JANET DEAN FODOR a1c1 and WILLIAM GREGORY SAKAS a2c2
a1 The Graduate Center, City University of New York
a2 Hunter College and The Graduate Center City University of New York

Article author query
fodor jd   [PubMed][Google Scholar] 
sakas wg   [PubMed][Google Scholar] 

Abstract

Following Hale & Reiss' paper on the Subset Principle (SP) in phonology, we draw attention here to some unsolved problems in the application of SP to syntax acquisition. While noting connections to formal results in computational linguistics, our focus is on how SP could be implemented in a way that is both linguistically well-grounded and psychologically feasible. We concentrate on incremental learning (with no memory for past inputs), which is now widely assumed in psycholinguistics. However, in investigating its interactions with SP, we uncover the rather startling fact that incremental learning and SP are incompatible, given other standard assumptions. We set out some ideas for ways in which they might be reconciled. Some seem more promising than others, but all appear to carry severe costs in terms of computational load, learning speed or memory resources. The penalty for disobeying SP has long been understood. In future language acquisition research it will be important to address the costs of obeying SP.

(Published Online November 15 2005)
(Received July 2 2004)
(Revised June 16 2005)


Correspondence:
c1 The Graduate Center, City University of New York, 365 5th Avenue, New York, NY 10016, U.S.A. E-mail: jfodor@gc.cuny.edu
c2 Department of Computer Science, Hunter College, North 1008, City University of New York, 695 Park Avenue, New York, NY 10021, U.S.A. E-mail: sakas@hunter.cuny.edu


Footnotes

1 For their helpful advice and feedback we are grateful to two JL referees, and the audience at the 2004 Midwest Computational Linguistics Colloquium at the University of Indiana. This research was supported in part by grants 65398-00-34, 66443-00-35 and 66680-00-35 from the Professional Staff Congress of the City University of New York.



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