# Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System

@article{Schultheis2021InverseOC, title={Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System}, author={Matthias Schultheis and Dominik Straub and Constantin A. Rothkopf}, journal={ArXiv}, year={2021}, volume={abs/2110.11130} }

Computational level explanations based on optimal feedback control with signaldependent noise have been able to account for a vast array of phenomena in human sensorimotor behavior. However, commonly a cost function needs to be assumed for a task and the optimality of human behavior is evaluated by comparing observed and predicted trajectories. Here, we introduce inverse optimal control with signaldependent noise, which allows inferring the cost function from observed behavior. To do so, we…

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Putting perception into action: Inverse optimal control for continuous psychophysics

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A computational analysis framework for continuous psychophysics based on Bayesian inverse optimal control is introduced and it is shown that this not only recovers the perceptual thresholds but additionally estimates subjects’ action variability, internal behavioral costs, and subjective beliefs about the experimental stimulus dynamics.

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