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Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox

Published online by Cambridge University Press:  01 January 2022

Abstract

Children acquire complex concepts like dog earlier than simple concepts like brown, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it is easier to infer the meaning of complex concepts than that of simple concepts.

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Copyright © The Philosophy of Science Association

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Footnotes

We are particularly grateful for the valuable comments of two anonymous reviewers. Earlier versions of this article were presented at the Salzburg Conference for Young Analytic Philosophy 2015, the German Society for Analytic Philosophy GAP.9 conference, and the Conceptual Spaces at Work 2016 conference. We would like to thank the participants at these events for their helpful feedback. Special thanks to the members of the Emmy Noether Research Group, From Perception to Belief and Back Again, and the graduate students in the Philosophy Department at Ruhr-University Bochum who gave critical feedback on an earlier draft of this article. In addition, we want to thank Ben Young for proofreading the manuscript. Research on this article has been generously supported by an Emmy Noether Grant from the German Research Council (BR 5210/1-1).

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