From Tom Bourbon [931109.1125]
[Martin Taylor 931109 11:00]
(Rick Marken 931108.2100)
I tested Tom's idea this evening using my three level spreadsheet
hierarchy (I had to change it a bit to get the actual states of
the controlled variables when the systems went "open loop').
I put individual systems into open loop mode by turning on the
"imagination" connection for the system. This takes perception out
of the loop and pegs the output at its current level; so the control
system is blindly generating a constant output. The result of taking
out one or two lower level systems depends on a number of things.
If the disturbance variations are slow, there is surprisingly
little effect on higher order control systems if two or even
three low level systems go "open loop". This lack of effect on higher
level control lasts for quite some time, but eventually, of course,
higher level control is lost.
Rick, dies this "quite some time" allow for the very large slowing factors
that you use in the spreadsheet model? In other words, are you asserting
that the high-level ECSs could have lost control much more rapidly than
they did, given the parameters that were set in the spreadsheet?
Wouldn't that always be the case, in any hierarchical control system? Are
you imagining a significance that you did not state, Martin?
As I understand the spreadsheet model, each perceptual signal is a defined
fuinction of all its input variables. If some of the input variables
don't correspond to "reality", the perceptual signal ought to be giving
the wrong answer, and the error ought to be causing the wrong output to
be generated. This is different from the situation Tom was describing,
in which one information source can be used when another, that usually
provides better information about the same CEV, has been disrupted.
Martin, my reading of Rick's simulation has him using higher-order
perceptual functions in the way I imagined. Those functions do not give a
"wrong" output, just an output. Imagine an "angle-detector" cell in the
visual cortex. It gives virtually the same output across many
transformations of the proximal stimulus pattern on the retina. Under many
cases when the retinal pattern is other than the maximally effective one,
the cortical cell shows a near-maximal response. That is not a "wrong"
In his simulations, Rick found the upper level in the hierarchical-parallel
model continued to control, using the available lower level loops. He found
what I suspected.
Am I misunderstanding what the spreadsheet does?
Or am I, Rick?
[Martin Taylor 931108 19:40]
(Tom Bourbon 931108.1005)
They (and I) were not talking about *modelling* control, but about
Fine. But the discussion initiated by Hans was about control by organisms
(including Hans). So was my reply. You say Lang and Ham were talking about
designing optimal, engineered control systems. That is often a different
subject, as it was in this instance.
I thought Hans was talking about how humans might be controlling. Humans
having evolved over some considerable time as control systems, it occurred
to me that Nature might have discovered good systems, if humans could find
I would be the last to argue that Nature has not "discovered" all of the
tricks employed by control engineers. I even think engineers are part of
Nature, along with the rest of our species. But I intend to go as far as I
can, given the limits on my abilities, to determine the extent to which
Nature can be modeled as though it had opted for the simple, rather than
the ingenious. (But I DO think a simple PCT loop, in hierarchical-parallel
systems, is pretty ingenious!) I want to see how far we can go using as our
model the simplest PCT loop, then that loop in a hierarchical-parallel
system. The fact that our species has devised other ingenious processes is
interesting, but most of the instances presented as evidence that those
processes are at work in living control systems seem to be of the "if we
build them, they are us" variety.
You wouldn't see the feedforward in your tracking studies (much), because
the feedback does a good job. But try the sawtooth tracking studies with
irregular blanking of the target, and see what happens. Will the feedback
only models still account for 99% of the variance? (This might be worth
trying in the sleep experiment).
I've tried the triangular tracking studies with the screen going blank after
the initial run-in period. For one minute, I "track" blind, with no
disturbance. I have tracked that triangular path many hundreds of times,
during more than nine years. In a recent bout in which I performed the task
sixteen times in succession, each time blanking the screen after the run-in
period, the mean correlation between my achieved handle positions (1800
of them during each run) and the ideal ones was -0.003 (S.D. = .118, range =
.390 to -.223). It is not easy to _quantitatively_ reproduce the same
pattern of movements for even one minute. _Qualitatively_, I always did
"almost the same thing." But as Bill Powers has pointed out during this
round of discussion, we must look very closely at all alleged examples of
actions that repeat identically, as in the allegedly ballistic actions that
some people want to call examples of feedforward. For the 16 runs I just
summarized, *any* incorrectly timed reversal of the direction of my hand
movements led to disastrous consequences quantitatively, but not so,
qualitatively. I suspect that the "sort of correct" patterns I created
without vision are a lot like the "sort of the same" movements produced by
"deafferented" animals -- and like people walking trough darkened, but
Yes, Avery, your option (b) was what I had in mind.
No problems here. My base assumption is always that one uses whatever
information one can. That includes all kinds of sensory input as well
as remembered and deduced information about "how the world works." There's
Then do you still think the higher level perceptual functions in a
hierarchical-parallel control system (as in hierarchical-parallel perceptual
control theory -- HPPCT :-)) give the wrong signal when some of their
contributing lower-level perceptual signals are missing? Aren't perceptual
signals "about" their accompanying perceptual functions, rather than about
Much of the current
round of discussion about feedback-feedforward seems to hinge on the idea
that something special must happen that (at least some of the time) allows a
person to walk successfully through a familiar but now darkened room.
No. It is that the same things that allow it are happening normally.
That is what I said, and what Rick simulated.
. . . One
uses the best information that is at hand. If you have direct perception of
the current situation, that's usually the best you can get. But it isn't
Direct perception of the current situation. I'm not sure what that is. If
you mean simply, "current perceptions," I agree that's *always* the best you
The revised Lang-Ham model *might* be *useful* under some conditions, but I
don't think it will prove *necessary* when *part of* the feedback signal is
This is a direct cue to get back into the "information in perception"
discussion. I don't want that tar-baby in my hands right now. But it
I don't know what you mean. Is it that you see a cue there, even though I
had no such topic in mind? If you don't want to grab the tar baby, that's
fine by me -- I never placed one on the path. All I was saying was that
feedforward is not *necessarily* involved when we control in the absence of
part of our normal complement of perceptual signals. My remarks did not
rule out the possibility that feedforward might be used, sometimes,
somewhere. It is just that no example offerred during this round
of discussion (playing tennis, driving on ice or sand, playing chess,
walking to the john in the dark, etc.) *requires* that we abandon the
attempt to use a feedback PCT model and that we incorporate feedforward.
Down with all-or-none thinking!
Have you seen any of that around here?
Br'er Bear (aka Tom)