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The Theory Theory 2.0: Probabilistic Models and Cognitive Development
Author(s) -
Gopnik Alison
Publication year - 2011
Publication title -
child development perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3
H-Index - 71
eISSN - 1750-8606
pISSN - 1750-8592
DOI - 10.1111/j.1750-8606.2011.00179.x
Subject(s) - psychological nativism , connectionism , cognitive science , representation (politics) , probabilistic logic , inference , statistical inference , bayesian inference , mental representation , psychology , bayesian probability , computer science , empiricism , epistemology , artificial intelligence , cognitive psychology , cognition , mathematics , philosophy , artificial neural network , statistics , archaeology , immigration , neuroscience , politics , political science , law , history
— N. S. Newcombe’s (2011) account of neoconstructivism opposes nativism to everything else—connectionist and dynamic systems theories, information processing theories, the “theory theory,” statistical learning, and Bayesian inference. But there is an alternative split that is equally important and that carves up the theoretical territory rather differently. This is a contrast between representational and nonrepresentational accounts of development. Whereas almost all nativist approaches are representational, among empiricists there is an important divide between those who, like nativists, embrace representation and those who deny it. “Probabilistic model” approaches, which include but are not limited to Bayesian learning, provide a developmental account that allows both representation and learning.