<p>A. The difference in velocity gains plotted against the difference in position gains of all subjects for the low control cost conditions (ellipses show the 95% confidence region). The color gradient indicates the values predicted by the simulations of a risk-sensitive optimal controller for different -values. B. as A. but for the high control cost conditions. C. Subjects' individual risk-parameters inferred from the experimental data of the high cost level versus inferred from the data of the low cost level (ellipses show 1 s.d.).</p
Many aspects of human motor behavior can be understood using optimality principles such as optimal f...
We investigate whether observers take into account their visual uncertainty in an optimal manner in ...
<p><b>A.</b> Plot of versus for each obstacle position and cost (grey level). Error bars are ±1 ...
<p>A. Results of the multilinear regression analysis of the low control cost conditions for subject ...
<p>A. Contribution of control cost to total cost for the high noise condition plotted against the lo...
<p>A) Distributions of the cursor position (left), cursor velocity (center) and center of pressure n...
<p>A.–C. Changes in motor command with position for a fixed velocity () for the low noise level (gre...
When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accura...
When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accura...
In motion simulation the inertial information generated by the motion platform is most of the times ...
<p>(A) Distribution of differences in reward probabilities between the actions of each trial. (B) In...
<p>The blue bar means the frequency counting number percentage of the investment proportion which li...
Many aspects of human motor behavior can be understood using optimality principles such as optimal f...
<p>The three columns correspond to the three levels of uncertainty of the target feedback (, and )....
In motion simulation the inertial information generated by the motion platform is most of the times ...
Many aspects of human motor behavior can be understood using optimality principles such as optimal f...
We investigate whether observers take into account their visual uncertainty in an optimal manner in ...
<p><b>A.</b> Plot of versus for each obstacle position and cost (grey level). Error bars are ±1 ...
<p>A. Results of the multilinear regression analysis of the low control cost conditions for subject ...
<p>A. Contribution of control cost to total cost for the high noise condition plotted against the lo...
<p>A) Distributions of the cursor position (left), cursor velocity (center) and center of pressure n...
<p>A.–C. Changes in motor command with position for a fixed velocity () for the low noise level (gre...
When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accura...
When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accura...
In motion simulation the inertial information generated by the motion platform is most of the times ...
<p>(A) Distribution of differences in reward probabilities between the actions of each trial. (B) In...
<p>The blue bar means the frequency counting number percentage of the investment proportion which li...
Many aspects of human motor behavior can be understood using optimality principles such as optimal f...
<p>The three columns correspond to the three levels of uncertainty of the target feedback (, and )....
In motion simulation the inertial information generated by the motion platform is most of the times ...
Many aspects of human motor behavior can be understood using optimality principles such as optimal f...
We investigate whether observers take into account their visual uncertainty in an optimal manner in ...
<p><b>A.</b> Plot of versus for each obstacle position and cost (grey level). Error bars are ±1 ...