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BUCKLE: A model of unobserved cause learning
2007
Psychological review
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 learning, BUCKLE (bidirectional unobserved cause learning) extends existing models of causal learning by dynamically inferring information about
doi:10.1037/0033-295x.114.3.657
pmid:17638500
pmcid:PMC2659393
fatcat:rzmnxehnmvf6fmy5wxpjcxs45a