UC San Diego

Our days are filled with instances of reasoning about the physics of the world, from simple tasks such as stacking dishes in a way that keeps them stable, to life-and-death decisions such as not crossing the street because we presume an oncoming car would hit us if we did. Yet the process we use to make inferences about physical events is not well understood. Here I argue that these interactions are based on a rich, approximately accurate simulation of physical events, but we must account for uncertainty about the current properties of objects in the world. In this thesis I investigate the structure of this simulation process and how it relates to other facets of cognition, including (1) demonstrating that the principles underlying interactions with the world are based on accurate physics, even if our explanations of those same principles are idiosyncratic and erroneous, (2) mapping out the types of uncertainty that this process accounts for, and demonstrating that the simulations themselves are therefore stochastic, and (3) explaining how physical predictions are updated over time due to changing evidence from evolving simulations. This provides a framework for understanding how people form and update representations of both the current and future state of the world based on rich, structured, probabilistic reasoning.