Optimality: From neural networks to universal grammar

被引:120
作者
Prince, A
Smolensky, P
机构
[1] RUTGERS STATE UNIV,RUTGERS CTR COGNIT SCI,NEW BRUNSWICK,NJ 08903
[2] JOHNS HOPKINS UNIV,DEPT COGNIT SCI,BALTIMORE,MD 21218
关键词
D O I
10.1126/science.275.5306.1604
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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?
引用
收藏
页码:1604 / 1610
页数:7
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