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Luhmann, Christian C.; Ahn, Woo-kyoung – Psychological Review, 2007
Dealing with alternative causes is necessary to avoid making inaccurate causal inferences from covariation data. However, information about alternative causes is frequently unavailable, rendering them unobserved. The current article reviews the way in which current learning models deal, or could deal, with unobserved causes. A new model of causal…
Descriptors: Inferences, Learning Processes, Probability, Models

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