When Domain-General Learning Fails and When It Succeeds: Identifying the Contribution of Domain Specificity

Abstract

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. We identify three components of any learning theory: the representations, the learner's data intake, and the learning algorithm. With these in mind, we model the acquisition of the English anaphoric pronoun one in order to identify necessary constraints for successful acquisition, and the nature of those constraints. Whereas previous modeling efforts have succeeded by using a domain-general learning algorithm that implicitly restricts the data intake to be a subset of the input, we show that the same kind of domain-general learning algorithm fails when it does not restrict the data intake. We argue that the necessary data intake restrictions are domain-specific in nature. Thus, while a domain-general algorithm can be quite powerful, a successful learner must also rely on domain-specific learning mechanisms when learning anaphoric one. Vast quantities of ink and hard feelings have been spilt and spawned on the nature of learning in humans and other animals. Are there domain-specific learning mechanisms or is learning the same across all domains? One of the most frequent battlegrounds in this debate is the case of human language learning. Is there a domain-specific language acquisition device or does language acquisition rely solely on domain-general learning mechanisms? We believe that the phrase " domain-specific learning " can be and has been interpreted in several distinct ways, leading to the illusion of incompatibility with domain-general learning. However, by examining these interpretations, we believe these two viewpoints can be successfully synthesized to explain language-learning phenomena. In the current paper, we bring this synthesis to the fore through a single, somewhat narrow, case study. There are three pieces to any learning theory. First, learners must have a way of representing the data to be learned from. In the domain of language …

Extracted Key Phrases

10 Figures and Tables

Cite this paper

@inproceedings{Pearl2009WhenDL, title={When Domain-General Learning Fails and When It Succeeds: Identifying the Contribution of Domain Specificity}, author={Lisa Pearl and Jeffrey Lidz}, year={2009} }