The effects of object motion observations on physical prediction
- Moyuru Yamada, Fujitsu Laboratories Ltd., Kanagawa, Japan
- Kevin Smith, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Josh Tenenbaum, Brain and Cognitive Sciences, MIT, Cambridge, Massachusetts, United States
AbstractPeople use knowledge about physical objects to predict and plan their actions, but this knowledge about objects can be directly perceived or simply inferred. In this experiment, participants chose the direction to shoot computerized cannons to hit targets. These cannons differed in how fast they shot the cannonball, but participants could learn this information either from observing the full trajectory of a prior shot, or just observing the outcome. While the cannonball’s initial speed can be determined from the end state alone, additional information in the full trajectory might improve these estimates. We find that performance is only worse in the end-state trials if these trials were tried first; if participants judged the full trajectory trials first, their performance did not decline on the end-state trials. We explore this order effect using a model of noisy physical inference that assumes learning from prior trial blocks.