C. A. Rothkopf

This paper introduces a Bayesian inverse optimal control framework for continuous psychophysics that recovers perceptual thresholds and estimates action variability, internal costs, and subjective beliefs.

The paper shows that eye movement patterns change with implicit and explicit visual learning, correlating with knowledge acquisition.

The paper shows participants adjusted their button presses to slide pucks in accordance with Newtonian physics, incorporating perceptual uncertainty and motor variability.

This study shows humans can plan multiple eye movements, with behavior better explained by an ideal planner than an ideal observer in visual search tasks.