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最优性:从神经网络到普遍语法。

Optimality: from neural networks to universal grammar.

作者信息

Prince A, Smolensky P

机构信息

Department of Linguistics and Rutgers Center for Cognitive Science, Rutgers University, 18 Seminary Place, New Brunswick, NJ 08903, USA.

出版信息

Science. 1997 Mar 14;275(5306):1604-10. doi: 10.1126/science.275.5306.1604.

Abstract

Can concepts from the theory of neural computation contribute to formal theories of the mind? Recent research has explored the implications of one principle of neural computation, optimization, for the theory of grammar. Optimization over symbolic linguistic structures provides the core of a new grammatical architecture, optimality theory. The proposition that grammaticality equals optimality sheds light on a wide range of phenomena, from the gulf between production and comprehension in child language, to language learnability, to the fundamental questions of linguistic theory: What is it that the grammars of all languages share, and how may they differ?

摘要

神经计算理论中的概念能否有助于构建心智的形式理论?最近的研究探讨了神经计算的一个原则——优化,对语法理论的影响。对符号语言结构进行优化,构成了一种新的语法架构——最优性理论的核心。语法性等同于最优性这一命题,为一系列现象提供了新的解释,从儿童语言中语言生成与理解之间的差异,到语言的可学习性,再到语言学理论的基本问题:所有语言的语法有哪些共同之处,又有哪些不同?

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