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- W4240566009 abstract "Abstract Theory theory is heir to Piaget’s constructivism where everyday theories encompass general knowledge structures and are learned. Earlier chapters outline theory of mind’s structured knowledge; this chapter tackles theory learning. Theories—scientific and everyday theories—encompass a crucial interplay between two levels of analysis: theory versus data. Scientists form and revise scientific theories based on data; children construct and revise intuitive theories, focally theory of mind, as a result of experience. Recent advances in computational learning show that and how such causal learning can proceed. Probabilistic Bayesian learning and hierarchical Bayesian models are particularly relevant for theory theory and theory of mind. Notably, as the dynamics of these models proceed learning unfolds in characteristic progressions, just as Chapter 5 showed that theory-of-mind developments evidence characteristic conceptual progressions. This chapter utilizes insights from constructivist machine learning applied to research with children to demonstrate developmental learning of theory of mind." @default.
- W4240566009 created "2022-05-12" @default.
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- W4240566009 date "2014-11-06" @default.
- W4240566009 modified "2023-09-25" @default.
- W4240566009 title "Theory Theory" @default.
- W4240566009 doi "https://doi.org/10.1093/acprof:oso/9780199334919.003.0006" @default.
- W4240566009 hasPublicationYear "2014" @default.
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