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  1. Understanding the Representational Mind.Josef Perner - 1991 - Cambridge: MIT Press.
    A model of writing in cognitive development, Understanding the Representational Mind synthesizes the burgeoning literature on the child’s theory of mind to provide an integrated account of children’s understanding of representational and mental processes, which is crucial in their acquisition of our commonsense psychology. Perner describes experimental work on children’s acquisition of a theory of mind and representation, offers a theoretical account of this acquisition, and gives examples of how the increased sophistication in children’s theory of mind improves their understanding (...)
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  • From covariation to causation: A causal power theory.Patricia W. Cheng - 1997 - Psychological Review 104 (2):367-405.
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  • Origins of knowledge.Elizabeth S. Spelke, Karen Breinlinger, Janet Macomber & Kristen Jacobson - 1992 - Psychological Review 99 (4):605-632.
    Experiments with young infants provide evidence for early-developing capacities to represent physical objects and to reason about object motion. Early physical reasoning accords with 2 constraints at the center of mature physical conceptions: continuity and solidity. It fails to accord with 2 constraints that may be peripheral to mature conceptions: gravity and inertia. These experiments suggest that cognition develops concurrently with perception and action and that development leads to the enrichment of conceptions around an unchanging core. The experiments challenge claims (...)
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  • Children and adults as intuitive scientists.Deanna Kuhn - 1989 - Psychological Review 96 (4):674-689.
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  • Insides and Essences: Early Understandings of the Non- Obvious.Susan A. Gelman & Henry M. Wellman - 1991 - Cognition 38 (3):213-244.
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  • Causal status effect in children's categorization.Woo-Kyoung Ahn, Susan A. Gelman, Jennifer A. Amsterlaw, Jill Hohenstein & Charles W. Kalish - 2000 - Cognition 76 (2):B35-B43.
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  • The role of covariation versus mechanism information in causal attribution.Woo-Kyoung Ahn, Charles W. Kalish, Douglas L. Medin & Susan A. Gelman - 1995 - Cognition 54 (3):299-352.
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  • Inferring causal networks from observations and interventions.Mark Steyvers, Joshua B. Tenenbaum, Eric-Jan Wagenmakers & Ben Blum - 2003 - Cognitive Science 27 (3):453-489.
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  • The Origin of the Idea of Chance in Children.J. Piaget & B. Inhelder - 1976 - British Journal of Educational Studies 24 (3):279-280.
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  • A theory of attention: Variations in the associability of stimuli with reinforcement.N. J. Mackintosh - 1975 - Psychological Review 82 (4):276-298.
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  • A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.Alison Gopnik, Clark Glymour, Laura Schulz, Tamar Kushnir & David Danks - 2004 - Psychological Review 111 (1):3-32.
    We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...)
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  • Covariation in natural causal induction.Patricia W. Cheng & Laura R. Novick - 1992 - Psychological Review 99 (2):365-382.
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  • A note on measurement of contingency between two binary variables in judgment tasks.Lorraine G. Allan - 1980 - Bulletin of the Psychonomic Society 15 (3):147-149.
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  • Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  • Word, Thought and Deed: The Role of Object Categories in Children's Inductive Inferences and Exploratory Play.Laura Schulz, Standing E., R. Holly, Elizabeth Bonawitz & B. - 2008 - Developmental Psychology 44:1266-1276.
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  • Words, Thoughts, and Theories.Alison Gopnik & Andrew N. Meltzoff - 1999 - Mind 108 (430):395-398.
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  • Causal Learning Mechanisms in Very Young Children: Two-, Three-, and Four-Year-Olds Infer Causal Relations From Patterns of Variation and Covariation.Clark Glymour, Alison Gopnik, David M. Sobel & Laura E. Schulz - unknown
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  • Equilibria of the Rescorla-Wagner Model.David Danks - unknown
    The Rescorla–Wagner model has been a leading theory of animal causal induction for nearly 30 years, and human causal induction for the past 15 years. Recent theories 367) have provided alternative explanations of how people draw causal conclusions from covariational data. However, theoretical attempts to compare the Rescorla–Wagner model with more recent models have been hampered by the fact that the Rescorla–Wagner model is an algorithmic theory, while the more recent theories are all computational. This paper provides a detailed derivation (...)
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  • Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.J. Pearl, F. Bacchus, P. Spirtes, C. Glymour & R. Scheines - 1988 - Synthese 104 (1):161-176.
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  • Causal maps and Bayes nets: A cognitive and computational account of theory-formation.Alison Gopnik & Clark Glymour - 2002 - In Peter Carruthers, Stephen Stich & Michael Siegal (eds.), The Cognitive Basis of Science. New York: Cambridge University Press. pp. 117--132.
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  • Children's Use of Sample Size and Diversity Information within Basic-Level Categories.Grant Gutheil & Susan A. Gelman - 1997 - Journal of Experimental Child Psychology 64:159-174.
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