Humans predict liquid dynamics using probabilistic simulation

Liquids can splash, squirt, gush, slosh, soak, drip, drain, trickle, pool, and be poured–complex behaviors that we can easily distinguish, imagine, describe, and, crucially, predict, despite tremendous diversity among different liquids’ material and dynamical characteristics. This proficiency suggests the brain has a sophisticated cognitive mechanism for reasoning about liquids, yet to date there has been little effort to study this mechanism quantitatively or describe it computationally. Here we find evidence that people’s reasoning about how liquids move is consistent with a computational cognitive model based on approximate probabilistic simulation. In a psychophysical experiment, participants predicted how different liquids would flow around solid obstacles, and their judgments agreed with those of a family of models in which volumes of liquid are represented as collections of interacting particles, within a dynamical fluid simulation. Our model explains people’s accuracy, and their predictions’ sensitivity to liquids of different viscosity. We also explored several models that did not involve simulation, and found they could not account for the experimental data as well. Our results are consistent with previous reports that people’s physical understanding of solid objects is based on simulation, but extends this thesis to the more complex and unexplored domain of reasoning about liquids.