Very good and timely observation. A study came out just a few a days ago in Nature Neuroscience showing that the brain tends to implement competing sensorimotor policies simultaneously (a sort of model averaging), at least at the beginning of a movement: Parallel specification of competing sensorimotor control policies for alternative action options.
(With this link you should be able to go through the paywall.)
By the way, this form of policy averaging is not wrong per se; it is wrong with respect to a given goal (aka loss function).
It’s not ideal if you want to reach the hotel (0-1 loss); it could be locally optimal (probably still not globally optimal, depending on your posterior), if you wanted to minimize the average (squared) distance from the hotel. Which is not what we usually want to do for hotels (if we are uncertain between building A and building B we are not just happy to stand in the middle), but it might be the right loss function in other cases.
Very good and timely observation. A study came out just a few a days ago in Nature Neuroscience showing that the brain tends to implement competing sensorimotor policies simultaneously (a sort of model averaging), at least at the beginning of a movement: Parallel specification of competing sensorimotor control policies for alternative action options. (With this link you should be able to go through the paywall.)
By the way, this form of policy averaging is not wrong per se; it is wrong with respect to a given goal (aka loss function). It’s not ideal if you want to reach the hotel (0-1 loss); it could be locally optimal (probably still not globally optimal, depending on your posterior), if you wanted to minimize the average (squared) distance from the hotel. Which is not what we usually want to do for hotels (if we are uncertain between building A and building B we are not just happy to stand in the middle), but it might be the right loss function in other cases.