emergence, etc.

[William_T_Powers2]

[From Bill Powers (930618.1000 MDT)]

Hans Blom (930617a) --

My control laws for each individual were:
1) keep a minimum distance to others;
2) keep a maximum distance from others;
3) otherwise move at discretion (no specific distance!).

This can be at least partly implemented with the CROWD program.
The "seek another person" control system specifies a distance
that is to be maintained from the sought person, neither more nor
less (a reference distance). The proximity error gain can be set
low so that it seems that a upper and lower limit of desired
distance exists. With the destination-seeking control systems all
turned off, there will be no tendency to go anywhere in
particular. Movement will be maintained by the conflict between
collision avoidance and positive seeking of another person's
position. I have tried several setups like this, and they result
in a sort of milling around in a general area; the whole group
sticks more or less together but may drift randomly in one
direction, then another.

I haven't tried this, but by moving other groups through the main
one, we can introduce disturbances. I would expect the original
group to re-form, because of the seeking of other persons'
general vicinities, although I wouldn't expect the centroid to
move back where it was. If you have a copy of the CROWD program
you might like to experiment with this.

These describe the behavior of a real flock much better, in my
opinion. It may be that you do not like the random element, nor
the non-linear control law, but let's stick to my example for
the moment, shall we?

The control law in the crowd program is pretty nonlinear already:
the controlled variable for collision avoidance, "proximity," is
calculated as the sum of the inverse squares of all distances to
other persons in the field (divided into left and right proximity
relative to the direction of travel), and proximity is also the
controlled variable (with a positive but nonmaximum reference
setting) for seeking the position of another person. So the
interactions actually involve inverse fourth powers.

What do you mean by 'natural tendency'? The same thing as Aris-
totle when he said that a rock has a 'natural tendency' to
strive for the center of the earth?

How about giving me the benefit of the doubt, Hans? The natural
tendency of a rock is to maintain its state of motion unless
accelerated by an applied force, and then to resist acceleration
with a force proportional to its mass. The natural tendency of a
board nailed to a wharf is to resist being lifted, not because
it's a control system but because it's nailed down.

Please be explicit in what discriminates a 'natural tendency'
from control (should you do so, I am tempted to say, I will
give you a counter->example :-).

Explicitly, it's power gain. A control system has an output
function that produces vastly more power output than its inputs
provide (drawing, ultimately, on external energy supplies). The
physical environment (excluding other control systems) generally
imposes a power loss between input and output: work must be done
on it to make anything happen. A controlled variable has work
done on it by a control system. If the variable is uncontrolled,
any potential energy it contains normally simply dissipates and
it comes to some equilibrium condition of minimum energy (that's
its "natural tendency"). In PCT we speak of "loop gain" which is
a measure of power amplification around the loop. The controlling
part of the loop is that in which the greatest power
amplification occurs: the organism, not the environment.

When I look at my simulated flock, I may PERCEIVE a
'natural tendency' to form a flock, but that is just my
subjective interpretation.

It's just a subjective interpretation unless you have analyzed
the elements of the flock and can show that the outcome of the
interactions among individuals must be a tendency for the whole
to remain more or less together. Then it becomes a deduction.

To understand (or model) what goes on, I need a
law or a formula (and I don't care much whether you call that
law or formula a 'natural tendency' or a 'control law').

Well, I care. Using words like "control" loosely results in their
not meaning much of anything: have a nice day. The word
"control", outside its technical meaning which I ALWAYS intend,
is just a slipshod term vaguely indicating the effect of
something on something else. We already have plenty of vague
terms borrowed from informal usage. Why not refine them for
scientific use when we can?

You wouldn't see any semblance of control in your flock if you
had ever seen and interacted with a real working control system
-- knowingly. You don't arbitrarily perturb a real control system
without spitting on your hands first and bracing your feet. When
I say that control systems resist disturbance, I mean that they
resist it energetically and with as much effort as needed (up to
their limits of output). They don't passively wait for controlled
variables to be shoved far from their reference levels and then
daintily make polite efforts to encourage them to go back where
they belong. They react instantly and strongly and never let the
error get large.

If a living control system gives way before a disturbance, it's
seldom because it couldn't resist it; it's usually because a
higher system is altering the reference signal to prevent
disturbance of some higher variable. If you see living control
systems drifting around and letting external forces have their
way, it's only because the effects of the external forces don't
matter much to the control systems (or because they're beyond the
capacity of the control system to resist them). The variables
that are under control are under CONTROL. There is no doubt about
a controlled variable when you find one. You can't simply take
hold of a real controlled variable and move it around. If you try
you'll have to struggle to get your way. Don't think of a flock
of birds. Think of a wild mountain lion. Try picking up the
mountain lion and putting it somewhere else to see if it rejoins
the group.

Let's try to stick to objective descriptions and try to avoid
'interpretations'.

I'm the one using an objective description of a control process;
you're the one using "control" as a metaphor.

An individual does not perceive 'flockness', yet 'flockness' is
preserved even if individuals are hidden from sight.

"Flockness" is an uncontrolled outcome of an interaction. Our
whole problem here is that you don't see the difference between a
lawful uncontrolled outcome and an actively controlled outcome.
You're refusing to go outside the boundary of phenomena that you
are trying to characterize as lawful, to see that there is
another kind of qualitatively different phenomenon.

For control in its technical sense to exist, there must be a
system that senses the state of the outcome, compares it with a
desired state, and turns the error into an output that has a very
high-powered effect on the outcome. If flockness were under
control by a competent control system, you would be unable to
disturb it without using extreme measures.

Isn't it remarkable how robust flockness is in the face of
disturbance?

I don't think you know what "robust" is. If the marble always
gets back to the bottom of the bowl after being displaced, you
would call its resistance to disturance robust. If a true control
system were keeping the marble at the bottom of the bowl, you
wouldn't be able to displace it appreciably in the first place.
THAT is "robust."

Remove WHICH control system? There is no control system for
'flockness'; that hypothetical one cannot be removed.

Correct. If you can't even find a potential control system, the
Test is failed before you begin.

Remove the sensors that measure distances to others, and the
flock will disintegrate: a random walk moves each individual
away without limit.

The Test would reveal that each control system was sensing and
controlling proximity to others (rather weakly). It would not
find any system controlling for the outcome of flockness. So the
conclusion would be that the individuals are controlling for
proximity, but there is no control system for flockness.
Flockness is a natural and lawful outcome of the interactions
between these individual control systems, but it is not a
controlled outcome.

Now, does 'flockness' pass The Test for the Controlled
Variable?

No.

If it were not for the fact that I remain upright while I walk,
the air along my path six feet above the ground would not be
displaced. The movement of the air follows lawfully from the
effects of my remaining upright while I walk, but it is not a
controlled variable. It is an uncontrolled, although lawful,
outcome of my control processes. A side-effect, as far as I am
concerned.

···

------------------------------------------------------------
Joel Judd (930617)

Ah, Joel, Herndon understands, doesn't he? And so do you. A
society based on coercion gets to the point where it considers
coercion a virtue.
------------------------------------------------------------
Best to all,

Bill P.

[William_T_Powers2]

[From Bill Powers (930620.1600 MDT)]

Sorry for the duplicate send; I got my wires crossed.

Hans Blom (930620) --

The slogan "it's all perception" is much too static. It has a
connotation of having to act in an a priori circumprescribed
way given a set of perceptions and a set of top-level (very
slowly changing; innate?) reference levels.

I agree. Perceptions are learned, too. There is a reason for the
slogan, however. It's to remind us that each of us sits inside
one of these gadgets, and that ALL we know either of the world or
of our own actions and inner being consists of perceptions. When
we produce a particular carefully crafted action, it is a
perception of that action that we know about and control. When we
see an effect of the action on the world, it is a perception of
the effect that we observe and adjust. When we feel joy or anger
at the result, that, too, is a perception. There is nothing else
to experience. Our actual outputs, the signals moving in the
outward direction, are not part of experience at all. This is of
no concern to an engineer, who looks at his control systems
strictly from outside. But in psychology it is the key to
understanding what control theory means for behavior.

Blaming what you see for what you do is usually considered a
defense mechanism or, if more forceful, for criminality.

True. This is one of the things that PCT is trying to change in
psychology: the idea that perception causes behavior. PCT says
that the person selects some experience as a goal, and acts to
make present-time perception conform to it. Behavior controls
perception, not the other way around.

Optimal control theory applied to humans says that you can
fine-tune your actions as well, that you have control over how
you control, i.e. that you have SELF-control.

Again, I agree. Of course you can't fine-tune your actions
directly unless you can perceive them; otherwise, you can only
reorganize until the perceived result of the actions is what you
want, without any direct knowledge of the actions themselves. And
it remains true that even when you specifically adjust your
actions, it is a perception of the actions you must adjust; the
action itself is output, and not sensible.

Yes, see how far this reaches when you consider humans. We do
not only operate on the outside world but on the inside world
as well.

The distinction between inside and outside is a perceptual
classification; both, as far as the brain (or PCT) is concerned,
are inside (or both are outside, it makes no difference).
Everything the brain can deal with exists in one space, the space
we call the experienced world. This world is derived completely
from signals generated by sensory receptors; there is no other
way to get information about an external world. The nature of
that world has to be inferred by the brain from the behavior of
the signals and how they respond to attempts to affect them.

We can tune our responses finer and finer, and reach ever
higher qualities of response and perception.

I'm not sure how you mean this, but it sounds like one of the
concepts we're trying to destroy. "Response" is the conceptual
opposite of "control." It implies a blind reaction to an input,
and carries overtones of jab-and-jump psychology. If we can "tune
responses" we must be sensing something that depends directly on
them; all we can actually tune is the sensory consequence, for a
pure response (of your own) is not itself experiencable. Whether
you intended this or not, this way of speaking about what is
learned encourages the old idea that perceptual inputs cause
motor outputs -- the very idea that allows people to blame what
they see for what they do. This is one of the many basic
conventional concepts that stand arrayed against PCT.

Control over control is self-control, perceiving your own
perceptions is self-perception, consciousness.

That sounds nice, but I don't believe it. If you diagram a system
that senses the stability of a control system and adjusts
parameters to control stability, you do not have a system
controlling itself: you have a system controlling something about
a different system. If you perceive your own perceptions, one
subsystem is perceiving the perceptions originating in another
subsystem, and most likely interpreting them in a different way.
The moment you say "I am thinking," you have denied the
statement: the system that is aware of the thinking is not
thinking, it is making a statement about a system that is
thinking. The "I" of which you speak is never the "I" that
speaks.

The only way to make sense of self-reflexive ideas is to treat a
person as if that person were solid, like a potato: only the
whole person perceives and acts. Only in that way can one say
that the referring self is the self referred to. That view is
contrary to the modeling approach, in which we try to understand
the whole in terms of interactions among its subsystems.

I said:

In other words, I could ask the question, "How is competent
adult human behavior organized when its organization is not
being changed?" This is what HPCT is about.

And you said:

Whereas my focus is more on how human behavior can become even
more competent, i.e. more on learning (and evolution as a kind
of learning).

I think that my goals have to be reached before yours can be
reached (at which point yours would be mine, too). Before you can
study how to make the human being more competent, you have to
have a way to measure its competence. Psychology has fallen down
on that job; nothing it says about behavior can be taken as a
clear fact, because its factual statements are riddled with
important exceptions and counterexamples. We need a highly
predictive and accurately descriptive model of how behavior works
when it is not changing. Only then can we measure change in any
reliable way, and know whether our attempts to improve competence
are having any effect, good or bad.

···

--------------------

One can, at our level of discourse, see a feedback amplifier or
some such device in two very different ways. The first is as a
device that transforms an input (voltage, current or power)
into an output (voltage, current or power). The feedback is not
really relevant here. The (voltage, current or power) gain may
be any value; both gains and losses can be similarly realized.
The second way is to see the device as a power modulator, where
the input modulates the transfer of power from its power supply
to its output. The feedback is not relevant here either.

Neither of these concepts is especially relevant to PCT. The
first is the usual idea in which the "input" (meaning, really,
the reference input) is confused with sensory inputs, so it
appears that an input from the environment is causing an output
into the environment. In living control systems the reference
input does not come from the environment, but from higher
systems.

The second applies primarily to the output function. It's not
often necessary to draw the power supply of a control system; the
behavior of the system is quite insensitive to changes in the
power supply, as you know.

Then, internal in the device, we see the LOOP GAIN, which has
nothing to do with power at all, but is the gain in the loop
that the SIGNAL travels. A decent control system has a loop
gain much greater than one, although a loop gain of less than
one is not unthinkable. In the latter case we might not want to
consider the system a CONTROL system.

Loop gain, in PCT, is not "internal to the device." The relevant
closed-loop path passes through the environment. I suspect that
you haven't yet understood just how the PCT diagram differs from
the standard engineering one. Actually, I'm working on this
subject right now for the joint paper, but I suppose it won't
dilute the writing too much to show you three diagrams that will
be in the paper, and preview the discussion. It's important to
understand exactly what we have done with the standard diagram.

Fig. 1 is what the behavioral sciences have taken from
engineering, for the most part:

            < ------------"the device" -------->

                        error
Input ----> comparator ----> forward function -----> Output
          + - | |
FIG 1 | |
                  --<----- feedback function <---

If you draw a circle around everything under "the device" above,
that is everything but the Input and the Output, you have the
first case you describe above, as well as your third statement in
which feedback is "internal to the device."

Now let's just add a few details without altering the overall
appearance: I'll have to use some abbreviations to fit it all in.

        < -- "device"----><-- environment -------------- >

sr --->[Comp]- se -->[fo]--> qo -->[fe] --> qc <--- [fd]<-- qd.
    + - | |
FIG 2 | |
        sp <------------[fi]<---------------

Here sr = reference signal, comp = comparator, se = error signal,
[fo] = forward or output function, qo = output quantity (the
immediate effector output), [fe] = environmental function (which
transforms the effector output into an effect on the controlled
quantity), qc = controlled quantity (the physical quantity
actually under control), [fi] = input function (which includes
the sensory receptors and any computations that immediately
follow), and finally, sp = perceptual signal, the internal analog
of the controlled quantity. [fd] and qd provide for representing
independent disturbances and their influence on the controlled
quantity.

I hope you agree that the organization of this model is identical
to that of Fig. 1, except for the explicit inclusion of a
possible disturbance and insertion of some stages implicit in
Fig. 1. I have relabelled the "input" as the reference signal,
which does no violence to engineering custom, and the "output" as
the controlled quantity, which is also an acceptable alternative
in engineering parlance.

However, I have expanded the details at the system's output a
bit. I have distinguished between the immediate effector output
and the controlled quantity, and introduced an environmental
function expressing the dependence of the controlled quantity on
the effector output. An example would be a control system that
controls a shaft's angular position. The controlled quantity qc
is the angle at the end of the shaft where the load or workpiece
is; the output quantity qo is the torque output of the driving
motor. The intervening [fe] expresses the way torque is converted
into shaft position, given the way load resistance depends on
angular position (which could be assigned to the disturbing
branch).

This separation is always important in detailed control-system
design, but especially so when the effector is coupled to the
controlled quantity loosely or through complex intervening
processes. Then we clearly would expect the effector output to be
changing far more than the controlled quantity is changing. Even
when we're just talking about output torque and controlled shaft
position, the system may have to vary the output torque
radically, even changing direction, in order to maintain a
specified shaft position, as twisting disturbances are applied
one way and the other to the controlled quantity at the end of
the shaft. I know you know all this; I'm just making the
description complete.

Now consider Fig. 3:

                             >sr ref signal
                         - +|
                  sp ------[Comp] --->-- se
                  > >
                  > sensor actuator | system
    :::::::::::::[fi]::::::::::::::::::::[fo]:::::::::::::::
                  > > environment
     controlled qc <------[fe] --------- qo
       quantity | actuator output
                  >
FIG 3 [fd]
                  >
                 qd disturbing quantity

This is organized exactly like Fig. 2. It is simply rearranged.
It is actually just like Fig 1., with details added. The plane of
separation between system and environment, however, is not the
one suggested by the first diagram. To locate it in the first
diagram, you would have to draw a line like this:

                                 [SYSTEM] | [ENV]
                                            >
Input ----> comparator ----> forward function -----> Output
                 > > >
                 > > >
                  ---------- feedback function <---
FIG 4 |
                                            >

This distinction means little in engineering, but in PCT it is
essential for getting the correspondences between the engineering
diagram and the physical organism right. In Fig. 3, the
horizontal line separates the nervous system of the organism from
all that is not nervous system. Sensors and actuators lie on the
boundary. Notice that in Fig. 3, there is no chance of mistaking
the reference input for a sensory input. The reference signal
comes from higher up, inside the behaving system. The sensory
inputs are strictly associated with the feedback path through the
environment. In living control systems, unlike artificial ones,
the reference signals are not accessible from outside the
behaving system.

In those control systems that have been traced out in human
beings and animals, Fig. 3 corresponds closely to the sensors,
intervening cells, and output paths. The reference input
corresponds physically and functionally with what are
traditionally called "command" signals, signals which carry
outputs from systems higher in the brain. Those command signals
have been thought of traditionally as carrying commands to the
muscles, causing them to contract (the feedback paths are ignored
even though they are mentioned in a sort of puzzled way). The
control-system diagram, with parameters filled in to make it fit
real behavior, shows that the so-called command signal is really
a reference signal. Its primary effect is to specify the level to
which the perceptual signal will be brought. The actual outputs
could be in any state, depending on what disturbances happen to
be acting on the controlled variable. The closed loop system
varies the output in any way required to make the controlled
quantity, and thus the perceptual signal, match the reference
signal. It does this without any instructions from the reference
signal.

Fig. 3 was drawn as it is with full knowledge of the engineering
diagram of Fig 1, for a specific purpose. Almost without
exception, behavioral scientists have interpreted the "input" of
Fig. 1 to mean "sensory input." When that is done, Fig. 1 becomes
nothing but a stimulus-response diagram with an internal feedback
loop having no obvious function. Wiener said it "reduced the
dependence of the output on the load." This has been taken as
cybernetic justification for the old model in which sensory
inputs cause behavioral outputs.

The reason for emphasizing the distinction between the actual
effector output and the controlled quantity (usually absorbed
into a single equation in engineering) is to show the difference
between the physical action of the system and the sometimes
remote outcome of that action which is actually under control.
When we see the controlled variable separated from the effector
output, we can much more easily understand that the visible
behavior of an organism is really just its actuator output, while
the focus of the control action is an effect of that actuator
output -- a joint effect, because disturbances act on the
controlled quantity, too. Thus, with this diagram, we can point
out the specific difference between what we see an organism doing
and the controlled outcome of those variable actions.

You might think that this rearrangement would be easy to explain
to real control engineers, but that has not always proven to be
the case. Control engineers get just as set in their ways as
psychologists. Long experience only seems to make matters worse.
One old control engineer with whom we went around and around for
six months on the net ended by saying that he saw what we meant,
but he just couldn't get used to talking about a controlled
variable as associated with input. So he bade us farewell,
wishing us luck in a gentlemanly way. Of course a much younger
one, encountered in a different venue, thought this was terrific,
and adopted the PCT model for teaching control theory to graduate
students. I guess there are a couple of control engineers on this
net who have seen the light. I don't know whether you have or
not; it's hard to tell from what you say.

All this volume of output was necessary to explain why I object
to your statement

Then, internal in the device, we see the LOOP GAIN, which has
nothing to do with power at all, but is the gain in the loop
that the SIGNAL travels.

The loop gain in Fig. 3 is the product of the partial derivatives
of [fi], [Comp], [fo], and [fe]. That is the gain that
determines how tight the control will be. It specifically must
include the path through the external environmental feedback
function. The control loop in PCT is NEVER "internal to the
system." It ALWAYS passes through the environment, no matter what
level of control is involved. This is what makes PCT models
testable. There may in fact be closed loops totally above the
line in Fig. 3, but in behavioral experiments we can do nothing
with them. Their effects will simply be absorbed into the basic
model of the control system.

And I think that's quite enough of my Sunday and your time to
spend on one post.
-------------------------------------------------------------
Best,

Bill P.