Nervous-system emulator for learning with a robot, and associated methods

A nervous-system emulator for learning with a robot, comprising a learning circuit configured to:

• control the robot with a plurality of lower-level reference signals such that the robot moves to an initial state;
• detect a perceptual signal from the robot while the robot is in the initial state;
• compare the perceptual signal to a top-level reference signal to generate a most-recent value of an error signal;
• compare the most-recent value of the error signal to a previous value of the error signal to generate an error-velocity value;
• and
• update each lower-level reference signal of the plurality of lower-level reference signals by:
• generating a next step size by (i) reducing a previous step size of the lower-level reference signal if the error-velocity value is less than zero or (ii) increasing the previous step size of the lower-level reference signal if the error-velocity value is greater than zero;
• generating a next step direction by (i) setting the next step direction equal to a previous step direction of the lower-level reference signal if the error-velocity value is less than zero or (ii) randomly selecting the next step direction if the error-velocity value is greater than zero;
• and
• adjusting the lower-level reference signal based on both the next step size and the next step direction;
• wherein the robot, after the lower-level reference signal is updated, moves to a subsequent state that is different from the initial state.