DocumentCode :
586553
Title :
Sticking to the Evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism
Author :
Bonawitz, E. ; Ullman, T. ; Gopnik, A. ; Tenenbaum, J.
Author_Institution :
Dept. of Psychol., Univ. of California, Berkeley, Berkeley, CA, USA
fYear :
2012
fDate :
7-9 Nov. 2012
Firstpage :
1
Lastpage :
6
Abstract :
An intuitive theory is a system of abstract concepts and laws relating those concepts that together provide a framework for explaining some domain of phenomena. Constructing an intuitive theory based on observing the world, as in building a scientific theory from data, confronts learners with a “chicken-and-egg” problem: the laws can only be expressed in terms of the theory´s core concepts, but these concepts are only meaningful in terms of the role they play in the theory´s laws; how is a learner to discover appropriate concepts and laws simultaneously, knowing neither to begin with? Even knowing the number of categories in a theory does not resolve this problem: without knowing how individuals should be sorted (which categories each belongs to), a the causal relationships between categories cannot be resolved. We explore how children can solve this chicken-and-egg problem in the domain of magnetism, drawing on perspectives from history of science, computational modeling, and behavioral experiments. We present preschoolers with a simplified magnet learning task and show how our empirical results can be explained as rational inferences within a Bayesian computational framework.
Keywords :
cognition; Bayesian computational framework; behavioral experiment; causal relationship; chicken-and-egg problem; cognitive development; computational modeling; intuitive theory; magnet learning task; magnetism; microtheory change; rational inference; science; Bayesian methods; Computational modeling; Data models; Image color analysis; Magnetic domains; Magnetic separation; Sorting; Cognitive Development; Models; Theory Change;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Development and Learning and Epigenetic Robotics (ICDL), 2012 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-4964-2
Electronic_ISBN :
978-1-4673-4963-5
Type :
conf
DOI :
10.1109/DevLrn.2012.6400815
Filename :
6400815
Link To Document :
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