That still involves training it with no negative feedback error term for excess blocks (which would overwhelm a mere 0.1% uncertainty).
This is supposed to be a toy model of excessive simplicity. Do you have suggestions for improving it (for purposes of presenting to others)?
Maybe explain how it works when being configured, and then stops working when B gets a better model of the situation/​runs more trial-and-error trials?
Ok.
That still involves training it with no negative feedback error term for excess blocks (which would overwhelm a mere 0.1% uncertainty).
This is supposed to be a toy model of excessive simplicity. Do you have suggestions for improving it (for purposes of presenting to others)?
Maybe explain how it works when being configured, and then stops working when B gets a better model of the situation/​runs more trial-and-error trials?
Ok.