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Proceedings of the Annual Meeting of the Cognitive Science Society
Modeling how intuitive physics concepts are learned from experience is an important challenge for cognitive science. We describe a simulation that can learn intuitive causal models from a corpus of multimodal stimuli, consisting of sketches and text. The simulation uses analogical generalization and statistical tests over qualitative representations it constructs from the stimuli to learn abstract models. We show that the explanations the simulation provides for a new situation are consistentfatcat:5mjgn7sbdjavxgmoizn4wugayq