Simulation as an engine of physical scene understanding
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Edited by Richard M. Shiffrin, Indiana University, Bloomington, IN, and approved September 20, 2013 (received for review April 8, 2013)

Abstract
In a glance, we can perceive whether a stack of dishes will topple, a branch will support a child’s weight, a grocery bag is poorly packed and liable to tear or crush its contents, or a tool is firmly attached to a table or free to be lifted. Such rapid physical inferences are central to how people interact with the world and with each other, yet their computational underpinnings are poorly understood. We propose a model based on an “intuitive physics engine,” a cognitive mechanism similar to computer engines that simulate rich physics in video games and graphics, but that uses approximate, probabilistic simulations to make robust and fast inferences in complex natural scenes where crucial information is unobserved. This single model fits data from five distinct psychophysical tasks, captures several illusions and biases, and explains core aspects of human mental models and common-sense reasoning that are instrumental to how humans understand their everyday world.
Footnotes
- ↵1To whom correspondence should be addressed. E-mail: pbatt{at}mit.edu.
Author contributions: P.W.B., J.B.H., and J.B.T. designed research; P.W.B. and J.B.H. performed research; P.W.B. and J.B.H. analyzed data; and P.W.B. and J.B.T. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1306572110/-/DCSupplemental.
Freely available online through the PNAS open access option.
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