Feedforward yet again

[From Bill Powers (2009.12.28.1530 MST)]

Martin Taylor 2009.12.28.10.50 --

MT to Rick: Let's suppose that what you had proposed was what you say here. Some planning system knew that the disturbance would be a sine wave, and moreover knew that it would have a particular frequency, phase, and amplitude. Wouldn't all the arguments made in the Powers and Bourbon paper "Models and their Worlds" apply? To avoid the Powers-Bourbon problem of blind planning, this hypothetical higher-level system would actually have to be three scalar control systems, one controlling for the sine-wave's frequency, one for its phase, and one for its amplitude. The outputs of these control systems would have to be numbers corresponding to a sine wave that should be generated by the output of the lower control system -- the one tracking the target. Somewhere there would have to be a function generator that took these three outputs and generated the sine wave reference signal for the tracking controller.

BP: This is way too complicated. What's needed, as you suggest, is an oscillator in the output function that can produce a repetitive on-off pattern at a variable frequency (what others have called a "central pattern generator", but simpler than that). The oscillator has to be adjustable in two dimensions: frequency and amplitude. Phase will take care of itself.

This suggests something like a voltage-controlled oscillator and a variable gain in the output function. The frequency comparison is done with a multiplier circuit that outputs the output signal waveform times the perceptual signal waveform. The product is smoothed, and is used to drive the voltage-controlled oscillator, with a positive voltage increasing the output frequency and a negative voltage decreasing it. Anti-aliasing may be needed, but isn't complicated. A second system can compare peak voltages and adjust the output magnitude accordingly, for the other dimension of control. Phase errors are automatically corrected by slight increases and decreases in the oscillator frequency.

MT: Yes, that would be feedback all the way. But it's very complicated, and it's not at all clear why a system that would be useful only for tracking sine waves would have evolved in a biological system.

It wouldn't be limited to comparing sine waves, and it isn't complicated. Tjhe frequency and phase of any repetitive pattern can be controlled if the output function is organized to produce it. Sine-wave frequencies can be controlled even if the multiplication is with a square-wave with a variable frequency. I have toyed for a long time with the idea of putting this sort of circuit into the "event" level to create repetitive events. Never tried any actual models, although I have built a number of control systems using the principle of phase-locked loops.

MT: As Bill points out [From Bill Powers (2009.12.26.0300 MDT)] in his mission to define "feedforward" out of existence, all we are ever doing is controlling current perceptions. If those perceptions involve using the derivative of a value to predict its future course, that future course is a current perception, too.

That's too complex an interpretation of rate feedback. If you control the variable x + k*(dx/dt), k becomes the damping factor in the control system, slowing the changes in output as k increases (NOT SPEEDING THEM UP). See Demo 5-1 in LCS3 to see the effect of increasing the gain of the rate-sensitive level Rick describes. You can vary that gain with a slider and see the effects, which are non-intuitive.

I'm not trying to redefine feedforward out of existence -- only to show that it is a lot less effective than is commonly assumed, and in most cases (all cases I have modeled) adds very little to the quality of control. The reason people so often assume it is useful is that they don't realized how large the effects of common disturbances on controlled variables really would be without negative feedback. The reason they don't realize that is that they don't see the negative feedback that is taking place to stabilize those variables against disturbances, making them think that the effects are generally small and that the universe is a lot more repeatable and reliable than it actually is. You have to know some physics or mechanical engineering to understand what would happen without the feedback component, and few psychologists have that sort of knowlege. I know you understand physics, so don't take that personally. But it definitely applies to a lot of people who think feedforward can acomplish everything. They haven't "done the numbers."

Best,

Bill P.

[From Bill Powers (2009.12.28.1640 MDT)]

Martin Taylor 2009.12.28.11.04 –

MT: I’m afraid I don’t know
where in the past there has been much use of “feedforward”, so
I don’t really think it’s attachment to the past that leads people to
want to use the word.

BP: It may have been Karl Pribram who introduced the word – I think I’ve
been trying to discourage it since before B:CP was published. It would be
interesting to know who the culprit was.

Best,

Bill P.

[From Bill Powers (2009.12.28.1645 MDT)]

Rick Marken (2009.12.28.0920) --

RM: Yes, I described it poorly. It was not a feedforward or predictive control model at all; it's a two level hierarchical feedback control model. ...

The level two system is implicitly controlling for a constant velocity and the level one system is controlling for keeping the cursor at the reference specified by the level two velocity control system.

Actually, if you're describing the same organization I was describing in Demo 5-1, the second level of control is controlling position, the integral of velocity. I'll have to check that out with a sine-wave disturbance.

Best,

Bill P.

[From Rick Marken (2009.12.28.1645)]

Bill Powers (2009.12.28.1645 MDT)--

Rick Marken (2009.12.28.0920) --

RM: Yes, I described it poorly. It was not a feedforward or predictive
control model at all; it's a two level hierarchical feedback control model.
...

The level two system is implicitly controlling for a constant velocity and
the level one system is controlling for keeping the cursor at the reference
specified by the level two velocity control system.

Actually, if you're describing the same organization I was describing in
Demo 5-1, the second level of control is controlling position, the integral
of velocity. I'll have to check that out with a sine-wave disturbance.

I think this discussion has given me my next research project. I
should have done this back in 1993. My theory of this combined
pursuit-compensatory tracking task is that, when the pursuit target
moves in a regular temporal/spatial pattern, a higher level system can
controls for perceiving the cursor moving along with the target in
that pattern. I think the combined pursuit/compensatory tracking task
would be a good way to test for two levels (at least) of control going
on at the same time and also for testing to see what the higher level
systems are controlling for. I could also compare the hierarchical
feedback control models to "predictive" models in terms of their match
to the human data. There are probably experimental operations that
will make the comparison quite clear.

This will be the second time this year that a discussion on CSGNet has
led to some actual research. The discussion a few months ago about
correlation and causality in a closed loop system led to the research
that a student and I have recently written up and submitted for
publication (as you know since your comments turned the paper into a
silk purse from its initial incarnation as a sow's ear;-)) And it's
always discussions with Martin that do it! So thanks, Martin.

Best

Rick

···

--
Richard S. Marken PhD
rsmarken@gmail.com
www.mindreadings.com

[From Bjorn Simonsen (2009.12.29.2215 EU ST)]

I have followed your discussion about “feedforward”. If you are interested in what Tom Bourbon and other expressed about "feedforward in 1994, you can read my encloced word document.

You find more on http://www.perceptualcontroltheory.org/articles/BestOfCSGNet/newcomer.001.html

and if you search for the one text about feedforward in http://www.perceptualcontroltheory.org/articles/BestOfCSGNet/newcomer.002.html

you will find why Tom Bourbon thinks “feedforward” is not a PCT concapt.

(I guess that would rule out “feedforward,” wouldn’t it?:wink: (at the bothom of the page)

bjorn

[From Bjorn Simonsen (2009.12.29.2245 EU ST)]

Thiws is mail number 2. I forgot the enclosure

I have followed your discussion about “feedforward”. If you are interested in what Tom Bourbon and other expressed about "feedforward in 1994, you can read my encloced word document.

You find more on http://www.perceptualcontroltheory.org/articles/BestOfCSGNet/newcomer.001.html

and if you search for the one text about feedforward in http://www.perceptualcontroltheory.org/articles/BestOfCSGNet/newcomer.002.html

you will find why Tom Bourbon thinks “feedforward” is not a PCT concapt.

(I guess that would rule out “feedforward,” wouldn’t it?:wink: (at the bothom of the page)

bjorn

Tom Bourbon a o about feedforward.docx (23.5 KB)

[Martin Taylor 2009.12.29.16.35]

[From Rick Marken (2009.12.28.1645)]

Bill Powers (2009.12.28.1645 MDT)--

Rick Marken (2009.12.28.0920) --

RM: Yes, I described it poorly. It was not a feedforward or predictive
control model at all; it's a two level hierarchical feedback control model.
...
       
The level two system is implicitly controlling for a constant velocity and
the level one system is controlling for keeping the cursor at the reference
specified by the level two velocity control system.
       

Actually, if you're describing the same organization I was describing in
Demo 5-1, the second level of control is controlling position, the integral
of velocity. I'll have to check that out with a sine-wave disturbance.
     

I think this discussion has given me my next research project. I
should have done this back in 1993. My theory of this combined
pursuit-compensatory tracking task is that, when the pursuit target
moves in a regular temporal/spatial pattern, a higher level system can
controls for perceiving the cursor moving along with the target in
that pattern. I think the combined pursuit/compensatory tracking task
would be a good way to test for two levels (at least) of control going
on at the same time and also for testing to see what the higher level
systems are controlling for. I could also compare the hierarchical
feedback control models to "predictive" models in terms of their match
to the human data. There are probably experimental operations that
will make the comparison quite clear.
   
Probably so. But you may have a problem finding conditions that would offer good discrimination between the two models. As you said in 1995, the advantage of including prediction shows up mainly when feedback is sluggish. In my sleep-loss study, the difference between the drug conditions showed up only after a night of sleep loss, and even then the effect, though clear, was not very big. As Bill has pointed out, control is pretty good without prediction under the conditions usually used in tracking studies, so under those conditions there isn't much room for either prediction or higher-level sequence generators to show off their advantages. That makes it even harder to demonstrate the relative benefit of one over the other under the best discriminative conditions.

Independently of those considerations, your higher-level system in each subject will need to be constructed from scratch by reorganization, separately for each repetitive pattern you use. Your subjects will be rather unlikely to have already learned the repetitive patterns (I hope plural) that you will use in the experiment, so they will have to be trained to recognize each one individually, not only to identify it as being repetitive, but also to learn the exact timing of every move in the pattern. I'm sure it can be done, since there's an analogue in the concert pianist's learning of the sound sequence to be produced in a performance. But I doubt it will be easy, at least for patterns that extend over more than a few seconds. This problem doesn't apply to the linear predictive model you and I both used in 1995, so unless the "generated repetitive pattern" (GRP) model clearly shows a better fit, it will be even more difficult to know at the end of the experiment whether it would have done had the subjects been trained longer on each specific pattern.

Then we come to another question: interpretation of the results. Since the predictive model does fit better than one without prediction even when the subject is untrained on any particular pattern, it is potentially viable as a model of what people do in everyday situations -- judging whether it is safe to cross the road in front of an oncoming car, for example. The GRP model is not viable as a model of that kind of everyday behaviour, though it may well be a viable model for trained behaviour like that of the concert pianist playing a well-learned piece. So how would one interpret the results if GRP turned out to be a better fit than linear prediction, but only after the subject had had some substantial training?

This will be the second time this year that a discussion on CSGNet has
led to some actual research. ... And it's
always discussions with Martin that do it! So thanks, Martin.
   
You are most welcome.

Martin