[From Rick Marken (960710.1200)]
Bill Powers (960709.1030 MDT) --
One of my main reservations concerning all the talk about uncertainty and
noise in perception is simply that when I look around, I don't see a noisy
Hans Blom (960710) --
What you call "disturbance", I call "noise". For me, this translation is
Well, that certainly helps explain your inability (or unwillingness) to
understand PCT after all these years.
Please explain what you consider to be the difference between disturbance
Ok. Maybe it will be of interest to people who want to learn PCT. I think
it's a pretty important distinction.
The word "disturbance" refers to an environmental variable that influences
the state of a controlled variable (also in the environment). For example,
the controlled variable may be the distance between two chairs. Disturbances
that influence this variable include the positions of the two chairs (d1 and
d2). So the controlled variable is d1-d2. The perceptual representation of
this variable, p, is a function of d1-d2. So p = f(d1-d2).
Bill's point (as I understood it) was that perceptions (like the perception
of the distance between the two chairs) are not noisy; that is, they are not
like looking at an old, unrestored version of a movie. Perseptions (mine,
anyway) are clear and consistent -- not at all what I would call "noisy".
This is my experience with perception. It is obviously not Hans' experience,
which is unfortunate but it explains a lot;-).
Disturbances don't make perceptions noisy; disturbances are aspects of the
physical reality upon which we _assume_ our perceptions are based. The
assumption that perceptions are a noiseless representation of a physical
reality "out there" -- the one described by the current "stories" of physics
(see B. Gregory "Inventing Reality") seems very sound based on the success of
PCT models of behavior based on this assumption.
If there were noise in perception then, based on our understanding of neural
processes, it would be added during or after the perceptual function that
represents external reality as neural signals. So p = f(d1-d2) + error.
While we know that error is part of ony process that represents physical
variables as signals, error is not evident in experience (at least not in
mine or Bill's -- if he is to be believed;-))