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52Learning the Form of Causal Relationships Using Hierarchical Bayesian ModelsCognitive Science 34 (1): 113-147. 2010.
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69Non-Bayesian Inference: Causal Structure Trumps CorrelationCognitive Science 36 (7): 1178-1203. 2012.The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more probable when it was linked to evidence by a causal chain than when both variables shared a common cause; (b) predictive chains in which evidence is a cau…Read more
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2648An improved probabilistic account of counterfactual reasoningPsychological Review 122 (4): 700-734. 2015.When people want to identify the causes of an event, assign credit or blame, or learn from their mistakes, they often reflect on how things could have gone differently. In this kind of reasoning, one considers a counterfactual world in which some events are different from their real-world counterparts and considers what else would have changed. Researchers have recently proposed several probabilistic models that aim to capture how people do (or should) reason about counterfactuals. We present a …Read more
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18Corrigendum to “People learn other people’s preferences through inverse decision-making” [Cognition 168 (2017) 46–64]Cognition 175 (C): 201. 2018.
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30People learn other people’s preferences through inverse decision-makingCognition 168 (C): 46-64. 2017.
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