Letting structure emerge: connectionist and dynamical systems approaches to cognition

被引:233
作者
McClelland, James L. [1 ]
Botvinick, Matthew M. [2 ,3 ]
Noelle, David C. [4 ,5 ]
Plaut, David C. [6 ,7 ]
Rogers, Timothy T. [8 ]
Seidenberg, Mark S. [8 ]
Smith, Linda B. [9 ]
机构
[1] Stanford Univ, Dept Psychol, Stanford, CA 94305 USA
[2] Princeton Univ, Dept Psychol, Princeton, NJ 08504 USA
[3] Princeton Univ, Princeton Neurosci Inst, Princeton, NJ 08504 USA
[4] Sch Engn, Merced, CA 95343 USA
[5] Sch Social Sci Humanities & Arts, Merced, CA 95343 USA
[6] Carnegie Mellon Univ, Dept Psychol, Pittsburgh, PA 15213 USA
[7] Carnegie Mellon Univ, Ctr Neural Basis Cognit, Pittsburgh, PA 15213 USA
[8] Univ Wisconsin, Dept Psychol, Madison, WI 53706 USA
[9] Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN 47405 USA
关键词
SIMPLE RECURRENT NETWORKS; NOT-B ERROR; RECOGNITION MEMORY; SEMANTIC MEMORY; FIELD-THEORY; PAST-TENSE; MODEL; CONSTRAINTS; PRINCIPLES; MORPHOLOGY;
D O I
10.1016/j.tics.2010.06.002
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Connectionist and dynamical systems approaches explain human thought, language and behavior in terms of the emergent consequences of a large number of simple noncognitive processes. We view the entities that serve as the basis for structured probabilistic approaches as abstractions that are occasionally useful but often misleading: they have no real basis in the actual processes that give rise to linguistic and cognitive abilities or to the development of these abilities. Although structured probabilistic approaches can be useful in determining what would be optimal under certain assumptions, we propose that connectionist, dynamical systems, and related approaches, which focus on explaining the mechanisms that give rise to cognition, will be essential in achieving a full understanding of cognition and development.
引用
收藏
页码:348 / 356
页数:9
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