An Approximate Representation of Objects Underlies Physical Reasoning

People make fast and reasonable predictions about the physical behavior of everyday objects. To do so, people may use principled mental shortcuts, such as object simplification, similar to models developed by engineers for real-time physical simulations. We hypothesize that people use simplified object approximations for tracking and action (the body representation), as opposed to fine-grained forms for visual recognition (the shape representation). We used three classic psychophysical tasks (causality perception, time-to-collision, and change detection) in novel settings that dissociate body and shape. People's behavior across tasks indicates that they rely on coarse bodies for physical reasoning, which lies between convex hulls and fine-grained shapes. Our empirical and computational findings shed light on basic representations people use to understand everyday dynamics, and how these representations differ from those used for recognition.Public Significance StatementPeople interact with objects in the world in real-time, which requires mental shortcuts in physical reasoning. We propose that a key physical mental shortcut is the simplification of fine-grained shapes into coarser bodies. Such simplified bodies explain novel results across several psychophysical tasks, including judgments of causality, time-to-collision, and change detection.