[From Rick Marken (960608.1600)]
Martin Taylor (960608 1221) --
the initial and basic prediction from information theory is
that the better the control, the less information from the disturbance
will be found in the perceptual signal, and that's the result that
As I recall, you made that "basic prediction" after you saw the data; I
guess that's the kind of prediction you get to make when you have two
watches It's a pretty strange prediction, too, since it says that
the less information you have about the disturbance, the more precisely
you can reproduce it. Is that _really_ what you thought the information
theory prediction was, at first?
However, in the presence of good control, a good reproduction
of the disturbance waveform can be constructed from the perceptual
signal, which is not possible when control is attempted but poor.
Yes. And this was true because the "information" you used to reconstruct
the disturbance was the output of the control system; you didn't use the
perceptual signal because there is no information in the perceptual signal
about the disturbance. There can't be. The perceptual signal always
represents a mix of disturbance and output effects on the controlled
variable: p = o + d. There is no information about the disturbance in
perception, no matter how well or how badly the perceptual signal is
being controlled. The whole idea of information in perception is
completely inconsistent with the facts of closed loop behavior.
There is also no information about the disturbance in the output variable;
the output variable mirrors the _net_ effect of all disturbances to the
controlled variable. So the most you can learn about "the" disturbance
from the output variable is the net effect of what might be one or many
disturbances to the controlled variable. And even this "information"
hinges on you knowing two things that the control system itself could
not possibly know: 1) the disturbance function, h(), that determines the
effect of disturbance variables on the controlled variable and 2) the
feedback function, g(), that determines the effect of the control system's
own output variations on the controlled variable. That is,
p = g(o)+ h(d1, d2...dn).
You were able to determine d based on o when you knew that g() and h()
were 1.0 and there was only one distrubance variable so that p = o+d.
Then, given o you were able to find d (this reconstruction was more
accurate when control was very good becuase, in that case, p is essentially
a constant). Your reconstruction of d based on o was not done with
information theory; it was done with (simple) algebra.
If analysis of the information processing that is inevitable any time an
influence at one place has an effect at another can be helpful in
understanding control,then use it.
Information processing is _inevitable_ any time an influence at one place has
an effect at another?!?!? The earth influences the position of the moon and
vice versa; is information processing going on here? Is the earth getting
gravitational information from the moon? (I have the scary feeling that
you're going to say "yes").
So far, I accept that I have not demonstrated it [information theory] to be
useful to you, though I find it useful to me. I have no problem with that,
and I don't understand why you do.
I spent a lot of time a couple years ago trying to explain why I have
a problem with information theory. My main problem wih it is that it
points behavioral researchers down a blind alley. If you think that
the brain is processing information about events in the world you will
do research aimed determining how these events are processed. That is, you
don't do the kind of research that helps you understand the behavior of
living systems; research aimed determining the kinds of perceptual
variables (events) that people perceive and control.
One of the tough things for people getting into PCT is confronting the
fact that their old, beloved theories are not consistent with PCT. This
is particularly tough when those theories were what led people to PCT
in the first place. But the fact is that PCT is a whole new ballgame;
you can't play it well if you keep trying to throw in rules from other