2023
DOI: 10.31234/osf.io/br2vz
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Learning what matters: Causal abstraction in human inference

Abstract: What shape do people's mental models take? We hypothesize that people build causal models that are suited to the task at hand. These models abstract away information to represent what matters. To test this idea empirically, we presented participants with causal learning paradigms where some features were outcome-relevant and others weren't. In Experiment 1, participants had to learn what objects of different shape and color made a machine turn on. In Experiment 2, they had to predict whether blocks sliding dow… Show more

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