dynamics vs control

[From Rick Marken (931129.1500)]

Martin Taylor (931129 12:30) --

Specifically, intentionality in control is always WITHIN an organism.
Seen from outside, as part of the larger universe, there is none.

What?

It is only when you shift viewpoint, and start to look (empathise)
from within the organism that you see control and intention.

But we can see controlled variables very clearly from the viewpoint
of an "outside" observer -- using "the test". That was the whole
point of my Behavioral Science paper; control is an observable
phenomenon.

Purpose arises only when the negative feedback has a changeable reference

I disagree. The basic phenomena of purpose (control) are produced by any
stable, closed negative feedback system; this was the point of my "Blind
Men and Elephant" paper.

Intention can't be seen from the dynamic picture of the total system,
because it isn't there.

The computer (doing "the test") can see it in the dynamic behavior
of the numbers roaming around the screen in the "mind reading" demo.

Perception is the way purpose is achieved

How about: Perception (the state of a perceptual variable) is the
purpose that is achieved by a control system.

, but without purpose, perception
would be pointless.

If "purpose" now refers to the reference signal then, yes.

From the outside, though, there is still no purpose.

I don't understand what this could possibly mean. From the outside
there is purpose when an observed variable passes the test for
being a controlled variable.

The explanation may be wrong, and
the kind may not fit your own perceptual function set very well, but if
it fits the dynamicist's and it works, then there is no ground for criticism.

What? You mean, if the dynamicists have the wrong explanation of
control but they think it's the right explanation then we have no
ground for criticism of their explanation?

Your [WTP's] "intention"
is quite specifically constrained by the hierarchic structure of PCT.

No, it's constrained by the nature of the aspect of the phenomenon
to which it refers. Guess 1) which aspect of 2) which phenomenon.
(Answer provided below -- no peeking).

Martin, it seems like this post was about why the work of the
"dynamicists" (which, I presume, includes the likes of Kelso, Saltzman,
Kugler, Turvey, etc) is important for students of purposeful behavior.
I have one question: is there anything (especially anything SIMPLE
and CLEAR) that a student of purposeful behavior could learn from
the "dynamicists"? What in the world is it? I've read the research of
the "dynamicists" and it was pretty clear that they were rather
(pardon my french) clueless about the nature of control in living
systems. Their research methodology guarantees that controlled variables
will remain undetected. And they have done what they could to prevent
PCT based research from appearing in the literature. What in the
world is it about "dynamicists" that you like?

Best

Rick

Answer: 1) reference signal 2) control

[Martin Taylor 931130 11:30]
(Rick Marken 931129.1500)

At cross purposes again, I see!

Rick, I was trying to explain why a dynamicist might not be interested in
control or purpose, and yet have a valid way of looking at the world.
You respond from the position that your way of looking at the world is
the only valid one, and if a person does not see everything as based on
control and purpose their view is wrong, wrong, wrong. I suggest that
their purpose is theirs, not yours.

But you have some valid points about ambiguous wordings.

Specifically, intentionality in control is always WITHIN an organism.
Seen from outside, as part of the larger universe, there is none.

What?

It is only when you shift viewpoint, and start to look (empathise)
from within the organism that you see control and intention.

But we can see controlled variables very clearly from the viewpoint
of an "outside" observer -- using "the test". That was the whole
point of my Behavioral Science paper; control is an observable
phenomenon.

The purpose you see is still within the organism, not in the wider system
that includes the whole control loop. An outside observer can infer that
there is a purposive control loop, but that wasn't what I was dealing with.

Purpose arises only when the negative feedback has a changeable reference

I disagree. The basic phenomena of purpose (control) are produced by any
stable, closed negative feedback system; this was the point of my "Blind
Men and Elephant" paper.

Well, I don't mind if you give every vortex in a stream "purpose," but I
do think that this usage goes a bit beyond the normal bounds of the term.

Intention can't be seen from the dynamic picture of the total system,
because it isn't there.

The computer (doing "the test") can see it in the dynamic behavior
of the numbers roaming around the screen in the "mind reading" demo.

That's hardly the total system, now, is it?

Perception is the way purpose is achieved

How about: Perception (the state of a perceptual variable) is the
purpose that is achieved by a control system.

Oh, come now. The difference between the perception and the reference
is the degree to which the purpose is achieved. The reference level is
the purpose, surely.

The explanation may be wrong, and
the kind may not fit your own perceptual function set very well, but if
it fits the dynamicist's and it works, then there is no ground for criticism.

What? You mean, if the dynamicists have the wrong explanation of
control but they think it's the right explanation then we have no
ground for criticism of their explanation?

Try rereading the quoted sentence. I grant it is ambiguous, so try this
expnasion as an aid to interpretation:

Within any framework, any particular explanation may be in error, and
the error found by testing the explanation within the framework. There
is no ground for criticizing an explanatory framework because the
explanations within it do not explain the things YOU want explained,
if they explain the things someone else wants explained. If someone
wants to explain something other than control, you have no ground for
criticizing them on that score. If a dynamicist has an explanation that
works for some phenomenon he/she is interested in but you are not, that
is no ground for criticizing their framework.

Martin, it seems like this post was about why the work of the
"dynamicists" (which, I presume, includes the likes of Kelso, Saltzman,
Kugler, Turvey, etc) is important for students of purposeful behavior.

It wasn't about that _at all_ (though you might be right that dynamical
analyses SHOULD be important). It was quite the opposite. It was about
why we should not necessarily expect someone interested in dynamics
issues to be concerned about PCT, and why we do not have grounds for
criticizing their lack of interest.

Their research methodology guarantees that controlled variables
will remain undetected.

So what, if their results are interesting to them, and hold whether
or not particular variables are controlled. It may be beneficial to
their interests to develop methods that guarantee to hide whether there
is control or not. It is true that systems in a strong non-equilibrium energy
flow tend to organize into quasi-stable structures. That does not depend
on whether some of that stability is induced by control,unless, of course,
by "control" you mean "negative feedback" as you suggested above. All
self-organization depends on negative feedback, and I don't consider it
control unless there is a variable reference level. For me, vortices
don't count as purposive.

···

================

However, to follow up on your inversion of the purpose of my posting:

I have one question: is there anything (especially anything SIMPLE
and CLEAR) that a student of purposeful behavior could learn from
the "dynamicists"?

Quite possibly.

What in the world is it?

I don't know at this moment. I'm inclined to think it would be in the area
of limiting criteria. Inasmuch as "control" is a special case of dynamics,
whatever is true in general of dynamic systems must also be true of
control systems, though the reverse is not the case. And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.
At any moment, someone who learns dynamics may get an insight from it
that could have profound implications for purposeful behaviour.

Martin

From Tom Bourbon [931201.0927]

I have a question for Martin about one part of his recent reply to Rick.

[Martin Taylor 931130 11:30]
(Rick Marken 931129.1500)

. . .

Martin:

However, to follow up on your inversion of the purpose of my posting:

Rick:

I have one question: is there anything (especially anything SIMPLE
and CLEAR) that a student of purposeful behavior could learn from
the "dynamicists"?

Martin:

Quite possibly.

Rick:

What in the world is it?

Martin:

I don't know at this moment.

Me:
So, Martin, your frequent posts asserting the importance of dynamical
systems science are expressions of pure faith? ;->

Martin:

. . . And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.

You have made this remark, or others very much like it, many times on the
net. Specifically, why do you believe this is so? Take any of my
interactive control tasks, in which two people, or one person using two
hands, are modeled by two independent single-level, single-loop PCT loops
in a non-hierarchic relationship. Pleae tell me, (1) specifically, *why* do
you say "you have to use dynamical analysis" in that instance, and (2)
specifically *how* how would you use dynamical analysis to improve on the
accuracy of re-constructions and predictions that I achieve with two
independent PCT models? I would appreciate thorough answers, on the net, to
both parts of my question; I have long been puzzled by your frequent
assertions about the necessity of "using" dynamical analysis any time there
are more than two non-hierarchic control systems. (Incidentally, precisely
*how* does one "use" dynamical analysis in such a case?)

Eager to see your reply,

Tom

[Martin Taylor 931201 15:30]
(Tom Bourbon 931201.0927)

I always cringe when I see mail from Tom that starts something like:

I have a question for Martin about one part of his recent reply to Rick.

Tom knows!... Yes Tom, Mea culpa, mea maxima culpa.

···

=====================

. . . And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.

You have made this remark, or others very much like it, many times on the
net. Specifically, why do you believe this is so?

As stated, it's obviously wrong. And stupid. As soon as I saw your
posting, I could see that I had been taking a viewpoint that excluded
the one you are using, and had blinded myself to the obvious fact that
one CAN simulate and model as many interacting control systems as one
has compute power for. I was thinking analytically, and even there I
was wrong for small numbers of linear control systems.

In context of the rest of what you call my "frequent assertions about the
necessity of using dynamical analysis," I plead mitigation in that I have
always pointed out that dynamical analysis is the general case, and control
analysis the specific. When the specific can be applied, as I have said,
it is more precise and better to use it. So although I may have used language
that could be so interpreted, I have not been of the opinion that dynamical
(general) analysis is better used where control system analysis is available.
But there is a difference, as I posted to Bill P. Control analysis
describes process, dynamical analysis describes a space of behaviours.
They may often be two views of the same thing, which are in no conflict.

So, Martin, your frequent posts asserting the importance of dynamical
systems science are expressions of pure faith? ;->

I've never been sure of the position of "pure faith" in science. My position
is that we have a body of mixed fact and assumption that we take as true,
though that body does change over time. At present, we take as true
Einstein's laws of General Relativity, the laws of thermodynamics (in
particular, for PCT, Boltzmann entropy), the standard model of quantum physics
and stuff like that. We use, as if they were true, Newton's laws of
mechanics, because we are dealing with things whose size and velocity
do not require us to use either General Relativity or quantum physics.

Among the things we take on faith are the operations of mathematics as
applied to the world, and from these we get dynamics. In particular
(with respect to PCT) we get results such as that interacting systems
with gain and nonlinearities greater than a square law are prone to
going chaotic in some regions of parametric variation. Control systems
in such an environment MUST be constructed so that their parameters
keep them out of the range of chaotic operation. You don't run into
this problem with linear systems, so far as I know. But that's a boundary
criterion that comes from the general dynamic considerations.

Another thing to consider is the question of generic versus non-generic
dynamics. Your helping studies are generic, whereas at least some of
Kent's demonstrations are non-generic in that the results depend on the
two control systems having the same dynamical parameters. Two parallel
control systems DO help one another when their references and dynamics
are the same, but not, as you have in many ways demonstrated, when they
are different. The dynamical concept of genericity is a useful one.

All of which is to say that I don't know how much EXTRA faith is required
in asserting that dynamical considerations are useful when dealing with
interacting control systems.

The kind of thought I had in mind when talking about two or more interacting
control system was the approach to an attractor, which will be exhibited
not by either control system individually, but by the behaviour of the
interacting pair. Maybe the (externally observed) state of the doubly
influenced CEV approaches a steady state, maybe it oscillates, maybe it
goes chaotic, but the joint system exhibits some kind of dynamic. That
dynamic and its corresponding attractor-repellor structure describes how
the control group performs when the CEV is disturbed. If the attractor-
repellor structure is complicated, it is quite possible for a disturbing
event to push the state of the joint system from one basin into another.
Control system analysis, if the system is simple enough to permit it,
will find the same result. As I wrote to Bill P. (was it in the post
I repeated to the net?), a dynamical analysis describes the overall
situation, control analysis the process that makes the situation be what
is described.

Pleae tell me, (1) specifically, *why* do
you say "you have to use dynamical analysis" in that instance, and (2)
specifically *how* how would you use dynamical analysis to improve on the
accuracy of re-constructions and predictions that I achieve with two
independent PCT models? I would appreciate thorough answers, on the net, to
both parts of my question; I have long been puzzled by your frequent
assertions about the necessity of "using" dynamical analysis any time there
are more than two non-hierarchic control systems.

(1) I misspoke. As to "*why*" I said that "have to" rather than "may,"
I don't have an answer.

(2) I don't believe that anything I wrote, considered in context of the
net interactions, could easily be taken to say that dynamical analysis
would

improve on the
accuracy of re-constructions and predictions that I achieve with two
independent PCT models

Any analysis tuned to the specific will always (if correctly done) achieve
better results than an analysis based on the more general case. But if
any specific analysis produces results that are inconsistent with the
general case, it is the specific that must be examined for unwarranted
assumptions or incorrect execution.

Eager to see your reply,

I don't know whether this is enough to satisfy your eagerness.

Incidentally, you, Rick, and Bill all have put me into some kind of
"dynamicist" camp, when all I have tried to do is to show that a dynamical
viewpoint need not be inconsistent with a control viewpoint. Before
learning of PCT, I did indeed approach the questions of thought from a
more general dynamical viewpoint. I wrote (for Behavioural and Brain
Sciences) a rather critical review of "The Emperor's New Mind" based on
this view as opposed to the algorithmic view of thought, and I would
change none of it now. I think that my exposure to the dynamical view
is one reason I found PCT so immediately congenial. Perceptual Control
is the special kind of dynamics that works for living systems.

Martin

[From: Oded Maler (931202)]

(Re: Martin Taylor 931201 15:30)

I also think the argument is based on misunderstanding. Dynamics
is the mathematical theory of things that change with time according to some
laws. Control systems (with or witout their environment) *are* dynamical
systems of certain sort. Rick's interpretation of "the dynamists" is, as usual,
a narrow interpretation of some people applying (perhaps wrongly)
advanced mathematical techniques to the analysis of human behavior.

I think a-priori that a PCTer might benefit from the study of dynamical
systems in the same sense that he will benefit from studying arithmetic
or linear algebra. The only damage can be due to the limited resources
of the individual in question (I myself, try to undestand some dynamical
system at this rather late stage of my life). Knowledge of sophisticated
math is not necessary for the basic PCT insight, and is certainly not
sufficient for it, but I cannot see how the possesion of a general
conceptual framework for analyzing systems that change with time, is not
an advantage for a PCTer.

--Oded

···

--

Oded Maler, VERIMAG, Miniparc ZIRST, 38330 Montbonnot, France
Phone: 76909635 Fax: 76413620 e-mail: Oded.Maler@imag.fr

From Tom Bourbon [931202.0909]

(Once again, my dateline is correct, but for how long?)

[Martin Taylor 931201 15:30]

(Tom Bourbon 931201.0927)

I always cringe when I see mail from Tom that starts something like:

I have a question for Martin about one part of his recent reply to Rick.

Tom knows!... Yes Tom, Mea culpa, mea maxima culpa.

I have a question for Martin about part of his repentant reply. But I will
save it until the end of my reply to him.

Martin:

. . . And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.

Tom:

You have made this remark, or others very much like it, many times on the
net. Specifically, why do you believe this is so?

Martin:

As stated, it's obviously wrong. And stupid. As soon as I saw your
posting, I could see that I had been taking a viewpoint that excluded
the one you are using, and had blinded myself to the obvious fact that
one CAN simulate and model as many interacting control systems as one
has compute power for. I was thinking analytically, and even there I
was wrong for small numbers of linear control systems.

I *thought* your earlier remarks might have been oversights. I am pleased
to know that was the case.

In context of the rest of what you call my "frequent assertions about the
necessity of using dynamical analysis," I plead mitigation in that I have
always pointed out that dynamical analysis is the general case, and control
analysis the specific. When the specific can be applied, as I have said,
it is more precise and better to use it. So although I may have used language
that could be so interpreted, I have not been of the opinion that dynamical
(general) analysis is better used where control system analysis is available.

Understood, but the language in many of your posts sometimes gives the
opposite impression. A few years ago, at a CSG meeting in Kenosha,
Wisconsin, Wayne Hershberger talked about the need for PCT theorists to use
"radical" language, meaning that we should be diligent in our efforts to
state the differences between PCT and other theories as clearly and
consistently as possible. We all agreed, but Wayne's injunction is easier
in the saying than the doing. There is no need for one of us to cringe when
reminded by another (or several others) that we have slipped up.

But there is a difference, as I posted to Bill P. Control analysis
describes process, dynamical analysis describes a space of behaviours.
They may often be two views of the same thing, which are in no conflict.

Whether or not there is conflict depends on the ends toward which the
various parties direct their analyses. I have no reason to question most
of the ends to which I see people applying dynamical systems analysis (DSA).
(I am not competent to question most of those applications.) However, when
psychologists claim that DSA adequately explains behavior and that PCT does
not, I am interested. When the models offered by DSA people as explanations
of a particular kind of behavior do not behave, but PCT models of the same
kind of behavior do behave very nearly the same way as people behave, then I
believe the DSA models are wrong, or irrelevant. I feel perfectly justified
in so saying -- in those particular instances, but such a comment implies
nothing at all about applications of DSA in other areas.

So, Martin, your frequent posts asserting the importance of dynamical
systems science are expressions of pure faith? ;->

I've never been sure of the position of "pure faith" in science. My position
is that we have a body of mixed fact and assumption that we take as true,
though that body does change over time. At present, we take as true
Einstein's laws of General Relativity, the laws of thermodynamics (in
particular, for PCT, Boltzmann entropy), the standard model of quantum physics
and stuff like that. We use, as if they were true, Newton's laws of
mechanics, because we are dealing with things whose size and velocity
do not require us to use either General Relativity or quantum physics.

Agreed, but in all of the instances you cited, I am certain that you can
provide specific illustrations of how and why those "laws," models and
"principles" merit our faith. In the case of "using" DSA to explain the
phenomenon of control, when Rick asked for examples, you said you
couldn't think of any. Perhaps I should have said *blind* faith, rather
than *pure* faith. ;-))
. . .

Another thing to consider is the question of generic versus non-generic
dynamics. Your helping studies are generic, whereas at least some of
Kent's demonstrations are non-generic in that the results depend on the
two control systems having the same dynamical parameters. Two parallel
control systems DO help one another when their references and dynamics
are the same, but not, as you have in many ways demonstrated, when they
are different. The dynamical concept of genericity is a useful one.

Agreed. In the various cases of two interacting elementary PCT models
that I have examined, the interactions *we* see, and the name we give them,
depend on the reference signals and the gains of the two models. And, of
course, on the couplings between environmental variables. The models are
the same, in their organization, but can differ in reference signals and
gains. Given only those differences, and the same environmental couplings,
two models, or two people, can create the impression that there is a large
array of "attractor basins."
. . .

The kind of thought I had in mind when talking about two or more interacting
control system was the approach to an attractor, which will be exhibited
not by either control system individually, but by the behaviour of the
interacting pair. Maybe the (externally observed) state of the doubly
influenced CEV approaches a steady state, maybe it oscillates, maybe it
goes chaotic, but the joint system exhibits some kind of dynamic. That
dynamic and its corresponding attractor-repellor structure describes how
the control group performs when the CEV is disturbed.

It describes **the state of the CEV** when the control group performs. It
says nothing at all about *how* the group performs, in terms of mechanisms
or their functions. What PCTers disagreee with is the assertion by some DSA
psychologists that they can explain *how* and that PCT cannot. You also
expressed this idea:

. . . As I wrote to Bill P. (was it in the post
I repeated to the net?), a dynamical analysis describes the overall
situation, control analysis the process that makes the situation be what
is described.

Pleae tell me, (1) specifically, *why* do
you say "you have to use dynamical analysis" in that instance, and (2)
specifically *how* how would you use dynamical analysis to improve on the
accuracy of re-constructions and predictions that I achieve with two
independent PCT models? I would appreciate thorough answers, on the net, to
both parts of my question; I have long been puzzled by your frequent
assertions about the necessity of "using" dynamical analysis any time there
are more than two non-hierarchic control systems.

(1) I misspoke. As to "*why*" I said that "have to" rather than "may,"
I don't have an answer.

OK, for now. But "we" will be watching! :-)))

(2) I don't believe that anything I wrote, considered in context of the
net interactions, could easily be taken to say that dynamical analysis
would

improve on the
accuracy of re-constructions and predictions that I achieve with two
independent PCT models

Neither do I (think you said that). That was why I wondered what point
you were trying to make in the original post, and in others like it in the
past, when you said we "have to use" DSA.

Any analysis tuned to the specific will always (if correctly done) achieve
better results than an analysis based on the more general case. But if
any specific analysis produces results that are inconsistent with the
general case, it is the specific that must be examined for unwarranted
assumptions or incorrect execution.

PCT modeling of an instance of control by a living system recreates the
phenomenon of control *and* it incidentally produces the side effects that
so fascinate DSA people. In contrast, the DSA models and analyses we have
seen all provide descriptions of the side effects, but they do not produce
control behavior. Applying your argument, I believe we can conclude that
the general analysis produces results that are inconsistent with nearly all
specific analyses and that it is the general that must be examined for
unwarranted assumptions or incorrect execution.

Eager to see your reply,

I don't know whether this is enough to satisfy your eagerness.

Much of it. Thanks.

. . . Before
learning of PCT, I did indeed approach the questions of thought from a
more general dynamical viewpoint. I wrote (for Behavioural and Brain
Sciences) a rather critical review of "The Emperor's New Mind" based on
this view as opposed to the algorithmic view of thought, and I would
change none of it now. I think that my exposure to the dynamical view
is one reason I found PCT so immediately congenial. Perceptual Control
is the special kind of dynamics that works for living systems.

So, DSA was one of the rafts that brought you to PCT. Was it Lao tzu who
spoke of people who so love the raft that carried them safely across a
river that they struggle to continue carrying it, long after their path has
taken them into the high mountains? (It can be difficult indeed to let go
some of the traditional baggage -- or to step out onto the unseen bridge.)

(Relocated from the beginning of the paragraph above)

Incidentally, you, Rick, and Bill all have put me into some kind of
"dynamicist" camp, when all I have tried to do is to show that a dynamical
viewpoint need not be inconsistent with a control viewpoint.

My question to you is this: Why do you say I have put you into a
"dynamicist" camp? All I asked was why you said:

. . . And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.

Until later,

Tom

[Martin Taylor 931202 14:00]
(Tom Bourbon 931202.0909)

Donning my "red-herring-chaser" cap...

My question to you is this: Why do you say I have put you into a
"dynamicist" camp?

Quoting Tom Bourbon (931201.0927)

Me:
So, Martin, your frequent posts asserting the importance of dynamical
systems science are expressions of pure faith? ;->

and

. . . And when you have
two or more interacting control systems that do not have a hierarchic
relationship, you have to use dynamical analysis beyond simple control.

You have made this remark, or others very much like it, many times on the
net. Specifically, why do you believe this is so?

I read these three sentences of yours each as showing you to perceive me
as belonging to the dynamics camp. I don't think min is an unreasonable
reading.

Your (Wayne Hershberger's) point about radical language is well taken,
but not always possible to follow. It is a lot easier to talk about
controlling the cursor-target relation than to repeat "the perceptual
signal corresponding to the CEV that is the cursor-target relation."

It gets even trickier when there is an outstanding issue as to whether
the CEV actually IS the perceptual signal or is something outside. I'm
having precisely this problem in my still-pending working note on "Helping,"
which I want you (Tom) to vet before it goes public. For autonomous systems
to interact, they have to interact through the outer world, by affecting
each other's CEV(s). But if the CEVs do not exist in the outer world,
there is no language to describe the interaction. Big problem in seeking
consistent use of language.

PCT modeling of an instance of control by a living system recreates the
phenomenon of control *and* it incidentally produces the side effects that
so fascinate DSA people. In contrast, the DSA models and analyses we have
seen all provide descriptions of the side effects, but they do not produce
control behavior. Applying your argument, I believe we can conclude that
the general analysis produces results that are inconsistent with nearly all
specific analyses and that it is the general that must be examined for
unwarranted assumptions or incorrect execution.

Not having looked at the examples you are talking about, I have to assume
you are assessing them correctly. In that case, I must agree with your
last clause.

...Given only those differences, and the same environmental couplings,
two models, or two people, can create the impression that there is a large
array of "attractor basins."

I doubt it would be just an impression. It is more likely to be a correct
description of the dynamic (or the superdynamic, more likely).

That
dynamic and its corresponding attractor-repellor structure describes how
the control group performs when the CEV is disturbed.

It describes **the state of the CEV** when the control group performs.

That wasn't what I meant. I meant "how it performs," meaning it describes
the orbits and possible different characteristic interactions that could
occur with different kinds of disturbance. One way of saying it, using
the words "**the state of the CEV**" is that it describes all possible
undisturbed evolutions of **the state of the CEV**, following all possible
step-wise disturbances.

It
says nothing at all about *how* the group performs, in terms of mechanisms
or their functions.

In that sense of "how it performs," you are right.

What PCTers disagreee with is the assertion by some DSA
psychologists that they can explain *how* and that PCT cannot. You also
expressed this idea:

. . . As I wrote to Bill P. (was it in the post
I repeated to the net?), a dynamical analysis describes the overall
situation, control analysis the process that makes the situation be what
is described.

I see nothing to change in what I wrote here. But there are at least
two possible ambiguities in the word "how." One, I illustrated above.
The other is in the application of Occam's razor. If (and I am, please
note, NOT saying it is so) a general theory makes the same predictions
with no more parameters than are used by a special one, then the general
theory quite legitimately can be said to show "how" the specific works.

It's when there is a crossover, the specific giving better prediction
or with fewer parameters that there is a problem with the general
explanation of the specific. We have that situation here, I think.
The dynamic description with the "large array of attractor basins"
describes all of the possible behaviours of the system. The analytic
equations do, too, if they are soluble. The simulation demonstrates
behaviour that samples a potion of the whole dynamic, but the simulation
does something different--it deals with the processes that cause the dynamic
to be as it is. So now the two approaches are not even dealing with
the same set of observations, just with observations that have a large
overlap.

This last point illustrates why there might be a problem with a dynamic
description of the phenomenon of control. Control exists when random
disturbances are resisted. Within a dynamic description, a control
system looks like a deep, steep, attractor basin. There's nothing
in it that could possibly talk about energy gain. That's part of the
process model, appropriate perhaps for constructing the equations that
define the dynamic. But within the dynamic, one has a phase space within
which orbits are described. Disturbances come from outside. They displace
the state across orbital paths. Discrete stepwise disturbances move
the point describing the current state from one orbit it is following
onto another. The dynamic description can show what the state will then
do (return more or less rapidly toward the attractor), but it cannot
deal with the disturbance itself. The dynamic description is of a
closed system's behaviour, starting from all possible states in the
phase space. So the dynamic and the process views share some but not
all of their relevant observations.

However, when
psychologists claim that DSA adequately explains behavior and that PCT does
not, I am interested.

Yes, it would seem an "interesting" claim. I would regard "adequate" as
being in the eye of the beholder, but "that PCT does not" seems more
absolute.

When the models offered by DSA people as explanations
of a particular kind of behavior do not behave, but PCT models of the same
kind of behavior do behave very nearly the same way as people behave, then I
believe the DSA models are wrong, or irrelevant.

I'm not clear in what way a dynamic description "does not behave." As
I mentioned, it does not--it cannot--explicitly incorporate disturbances,
but it can deal with the recovery from error (in principle). If extant
dynamic models do not behave the way people do, and PCT models fit well,
then you are right to "believe the DSA models are wrong, or irrelevant."
But not all possible such models. Only the ones that are wrong. It is
quite possible that they are ALL irrelevant to something that interests
you, namely, process.

This red herring spread a long trail, didn't it?

Martin