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Learning structured systems from imp...

Goldowsky, Boris Neill.

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Learning structured systems from imperfect information.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Learning structured systems from imperfect information./
作者:	Goldowsky, Boris Neill.
面頁冊數:	64 p.
附註:	Source: Dissertation Abstracts International, Volume: 56-05, Section: B, page: 2910.
Contained By:	Dissertation Abstracts International56-05B.
標題:	Language, Linguistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9530388

Learning structured systems from imperfect information.
Goldowsky, Boris Neill.

Learning structured systems from imperfect information. - 64 p.

Source: Dissertation Abstracts International, Volume: 56-05, Section: B, page: 2910.

Thesis (Ph.D.)--University of Rochester, 1995.

A critical way in which language acquisition has been said to differ from other learning is in the results of inconsistent input. In language acquisition, it is common for the data available to the learner to be imperfect, but this has little effect on children's learning--they force the system to be regular by extracting or creating rules. In other domains, however, such as probability-learning experiments, people are said to be faithful to the probabilistic structure of the data to which they are exposed. This leads to the assumption that language must be learned by different mechanisms.Subjects--Topical Terms:

1018079
Language, Linguistics.

Learning structured systems from imperfect information.
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100 1 $a Goldowsky, Boris Neill. $3 1294194
245 1 0 $a Learning structured systems from imperfect information.
300 $a 64 p.
500 $a Source: Dissertation Abstracts International, Volume: 56-05, Section: B, page: 2910.
500 $a Supervisor: Elissa Newport.
502 $a Thesis (Ph.D.)--University of Rochester, 1995.
520 $a A critical way in which language acquisition has been said to differ from other learning is in the results of inconsistent input. In language acquisition, it is common for the data available to the learner to be imperfect, but this has little effect on children's learning--they force the system to be regular by extracting or creating rules. In other domains, however, such as probability-learning experiments, people are said to be faithful to the probabilistic structure of the data to which they are exposed. This leads to the assumption that language must be learned by different mechanisms.
520 $a However, previous studies may have confounded the effect of linguistic vs. non-linguistic tasks with the complexity or structure of the learning problem, or with the age of the learners studied. Following Newport's Less is More hypothesis, we suggest that the structure of the system being learned interacts with the capabilities and constraints of the learner to create the different learning patterns, independent of the domain.
520 $a This dissertation describes three experiments, which use a new paradigm for presenting multidimensional structured systems. The subjects are to learn a mapping relation between objects and actions by watching observation trials which exemplify the regularities but also contain exceptions. Adults and 7-year-old children are tested on various systems which vary in complexity and quality of data, and their learning is evaluated by prediction and generalization tests.
520 $a While adults turn out to be better at learning the details of the systems, children demonstrate a tendency to respond according to a consistent pattern, inventing one if necessary. This is parallel to some phenomena of language acquisition, suggesting that language may be learned by the same mechanisms that support the learning of other complex systems.
590 $a School code: 0188.
650 4 $a Language, Linguistics. $3 1018079
650 4 $a Psychology, Developmental. $3 1017557
650 4 $a Psychology, Experimental. $3 517106
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710 2 0 $a University of Rochester. $3 515736
773 0 $t Dissertation Abstracts International $g 56-05B.
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791 $a Ph.D.
792 $a 1995
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