System Dynamics & PCT

System Dynamics & PCT
[From Erling Jorgensen (2005.02.11 1730 EST)]

Martin Taylor (2005.02.09.17.44)
[prior subject -- Re: Just Don't Get iT]

This was a very helpful post, Martin.

I want to contribute some things I have been mulling over,
about how Perceptual Control Theory may relate to System
Dynamics (SD). I am still new in my exploration of the
SD literature, but I believe I can follow the contours of
SD arguments & models. I'll use various headings here,
to try to keep the ideas clear.

SD Archetypes

(This section may serve as a brief introduction to SD, for
some on the CSGNet list who may not yet be acquainted with it.)

One natural point of correspondence between the notions of
SD & that of PCT is with regard to what the SD movement calls
"archetypes." These seem to be various modular components,
or patterns, that frequently recur in dynamic systems, and
which can be combined in various ways to map onto a specific
problem, to try to obtain explanatory & predictive clarity.

A useful summary of some of the basic SD archetypes can be found
at Gene Bellinger's website --
<http://www.systems-thinking.org/arch/arch.htm&gt;
He seems to draw upon earlier work by Peter Senge, and of course,
Jay Forrester.

These archetypes are thought to be "generic feedback structures."
They include things like a negative feedback "Balancing Loop,"
and a positive feedback "Reinforcing Loop," and various
combinations that seem to lead to predictable patterns of
dynamic behavior.

Other classic archetypes include: "Success to the Successful"
(two mutually reinforcing positive feedback loops), "Limits
to Success" (a reinforcing loop eventually held in check by
a balancing loop), "Escalation" (two balancing loops in
competition which max out as a reinforcing loop), "Fixes That
Fail" (a balancing loop which becomes reinforcing due to
unintended consequences), and other more complicated combinations
such as "Tragedy of the Commons", "Shifting the Burden", and
"Growth and Underinvestment".

These archetypes may be commonplace to those familiar with
SD, and they seem to have some utility, esp. to managers and
consultants, in analyzing complicated business or
organizational dynamics.

The specifying of such archetypes is part of a larger project
within the SD movement. It is nicely articulated on the first
page of an article by Scott Rockart, presented at the 2004
System Dynamics Conference. It is available at --
<http://www.systemdynamics.org/conf2004/indexpapers.htm&gt;
[scroll to Rockart, Scott. Number 350. Might Twenty Models
Cover Ninety Percent of All Situations Managers Encounter?]

Quoting from Rockart --
"Jay Forrester's call for a set of 'general, transferable
computerized cases' to cover most managerial situations is
one of the great tasks standing before the field of system
dynamics. A library of widely applicable cases, if accompanied
by reliable guidelines for when to apply them, would be a boon
to research, teaching, and management. Researchers could use
these cases as strong null models when evaluating new situations
and new theories (Bell 2001)."

Formulation of modular archetypes has been one response to
Forrester's call. A more elaborate one has been the specifying
of detailed computerized models of specific problem situations,
which have the potential for being exemplars as they are
modified and applied to other specific situations.

PCT in a SD Framework

My initial reaction to how PCT may fit into such a SD framework
was to consider the basic PCT control loop to be a more precise
mathematical specification for the basic "Balancing Loop"
archetype. Thus, the PCT equations of an elementary control
system nicely elaborate on an item already in the SD library
of archetypes.

In the SD models I have seen, balancing loops frequently occur
as aggregate negative feedback patterns. But I rarely see
a specifically-labelled intentional agent, which is controling
its perceived input as in a classical PCT control system.

This observation may be part of a larger debate in the field,
which contrasts the top-down Equation Based Modeling of typical
SD approaches, with the bottom-up Agent Based Modeling of other
approaches. One reference, also from the 2004 SD Conference,
would be a paper by Nadine Schieritz, "Exploring the Agent
Vocabulary: Emergence and Evolution in System Dynamics",
available at --
<http://www.systemdynamics.org/conf2004/indexpapers.htm&gt;
[again scroll to the author's name]

It is a reasonable guess that much or most negative feedback,
including that aggregately-displayed in SD computerized models,
derives from the operation of living systems. So it has
occurred to me that perhaps the individual agency of PCT
control systems could be usefully inserted into the "flows"
of SD structural diagrams. This could be a way of marrying
the top-down and bottom-up approaches, and deriving the
benefits of each.

Having said that, there is a drawback to the mathematical
precision of the PCT control loop. Every component and
function on the loop has to be specified, and that includes
the perceptual input function. In PCT modeling to date,
(or rather, in the needed expansion of PCT modeling to new
variables and domains,) this constraint has proved extra-
ordinarily severe.

_We just don't know_ how to model very many types of
perceptual input functions. We've got the equations for
the rest of the loop, and they are extremely rigorous and
flexible in their functioning. But beyond weighted sums,
and logical relations, and a flip-flop here & there, we
do not have realistic functional equations for many of those
other kinds of perceptions that we seem to be able to control.
This is a limitation of the current PCT approach.

An advantage of the SD approach, in terms of this very issue,
is that ad hoc first approximations of the equations, even
expressed with many "non-numerical" types of variables,
can still get you some pretty interesting results. All you
seem to need is some sense of plausible (aggregate) influences,
along with determining which way the feedback sign should go
-- positive or negative. With that, you can get a first
version simulation of a dynamical system up and running, so
you can start to examine its implications. This payoff seems
to be behind the "movement" appeal of the SD approach.

Asymmetry of Input and Output

Martin, this was the most helpful part of your post to me.
Specifically, you said --

there is a specific aspect of PCT that identifies where it
fits into the more general System Dynamics area. That
specific aspect is the essential asymmetry between the
input and the output side of the PCT loop.

In other words, classic PCT control loops all contain a
significantly large amplification factor in the output
function (typically called "gain"). This allows even a
small mismatch between a current perception and the
preferred reference state for that variable to generate
a potentially large output to try to correct the mismatch.
This capacity appears to be a fundamental property of
living systems.

SD structural diagrams certainly have room for such
amplification factors. I believe they appear as auxilliary
equations inserted into rate equations. But you are
right, Martin, they do not appear to be intrinsic aspects,
as they are with a PCT control loop.

And this gain factor, in concert with the error-reducing
arrangement of negative feedback itself, seems to be
pivotal in a thermodynamic sense, for developing the local
pockets of negentropic order, which characterize living
processes.

I believe this intrinsic aspect of how PCT equations are
calculated, with a large gain or amplication in the output
function, makes a PCT control loop an even better candidate
for inclusion in the SD library of basic modules.

I wondered about another aspect of your observations,
Martin. You said --

If you read, for example, the System Dynamics mailing
list, you will see lots of discussion of negative (and
positive) feedback, but almost nothing on control. The
feedback loops of interest tend to be symmetric in that
the energy levels and amplification factors are not
intrinsically different in different parts of the
circuits.

I agree with your observation. I wonder if this is because
the feedback effects in an SD model are most commonly
through the _side effects_ of control. In other words,
control processes are interfering with each other, (and
being aggregated in an SD model). But the interference
effects are often the result of accidental disturbance,
rather than concerted disturbance, if I can put it that
way.

A head-to-head conflict between two control loops trying
to control for different values of the same variable,
brings all the help and heartache of amplification factors
into full bloom. You can't help but notice their effects.

But when specific control systems are not explicitly modeled
(as their own controling agents) in an SD simulation, it
seems that interferences would tend to cancel one another
out in the aggregate, as side effects that are not
deliberately controlled. I think this would tend to leave
a relatively small _net_ feedback, which is either negative
or positive in an SD rate equation. This may be why we don't
see much asymmetry in different parts of the feedback loops
of SD models.

Hierarchical Arrangements of Control

A stronger candidate for inclusion in an SD library of
archetypal modules, I believe, is a basic PCT arrangement
of two (or more) control loops in a hierarchical relation.

(BTW, this has nothing to do with any particular proposals
of what levels of perception may occur in humans, as put
forward in what we customarily call HPCT.)

Bill Powers has produced some very robust demonstrations-
of-principle, with stabilized control occurring at multiple
levels of hierarchically-internested PCT control loops. Two
models that come to mind are a) his control of an inverted
pendulum by means of (I think) six layers of control, and
b) some of the work he reported with using derivatives as
controlled variables, in multiple layers, to improve the
resolution of inherently fuzzy star images (I think I'm
remembering that correctly).

As long as certain properties are adhered to, a hierarchical
arrangement of control loops -- where lower levels of control
are the means of implementing higher levels of control --
can arrive at very stable control of several variables at
once. I have likened the difference between the topmost
layer and the lower layers in this way: The topmost layer
implements control as essentially a compensatory tracking
task, despite disturbances percolating up from lower in the
hierarchy. Each lower layer implements control as essentially
a pursuit tracking task, seeing as its next-higher layer may
be dynamically changing the reference signal on the fly, so
that the higher layer also achieves adequate control. Control
of perceptual variables is happening at all levels. But for
lower levels it looks like the goal for each one is moving all
over the place.

Perhaps this combination of the appearance of compensatory
tracking at the highest level and pursuit tracking at each
lower level might qualify for some kind of mini-archetype...
(:slight_smile: whaddya think?) It is perhaps worth noting, that the
moving target of the lower level's pursuit tracking task
does appear in the SD list of archetypes as currently
formulated. There is one entitled "Drifting Goals", which
seems to involve two Balancing Loops in a hierarchical
relation, with a "pressure to adjust desire" (i.e., change
the reference standard). I am not convinced that it operates
exactly as outlined, but it is trying to capture the dynamic
where a system "reaches an equilibrium other than what was the
initial desired state" (cited from Gene Bellinger's website --
<http://www.systems-thinking.org/arch/arch.htm&gt; ).

One of the key properties that must be included, for
hierarchically-arranged control loops to operate correctly
without inherent instabilities, is that a higher layer
must operate at a _slower_ rate relative to a lower layer.
(In terms of evidence, I think this can be demonstrated
fairly simply with most any of the PCT simulations.)
The easiest way to understand this is that you can't call
for results from a lower level faster than they can be
produced.

A key benefit of hierarchically-arranged control is that
tasks can be partitioned into independent degrees of freedom,
without sacrificing precision of control. And the components
needed to maintain control over each degree of freedom can
be relatively simple (i.e., the equations of a basic PCT
control loop). This enormously simplifies the modular task
of building up more complicated forms of control.

The P in PCT

Martin, I appreciate your thermodynamic formulations of
what is involved in PCT control systems. You describe --

the necessary structure: a low-energy "sensor" (a portal
through the "shell") leading to a low-energy internal state,
which in some fashion affects actions that can counter the
potentially damaging high-energy influence.

This is the basis for the amplification of output and the
asymmetry, that was discussed above. What I'm struck with
here is the filtering effects of the 'sensor through the
shell's portal'.

Control systems need not directly represent all of what is
outside the shell. Indeed, I think you are arguing even
stronger that they cannot; the energy differences are
sometimes too great. For instance --

If the internal representation depended on energy levels
similar to the potentially damaging influence, they would
themselves be damaging to the organism.

While I am not sure I follow the necessity of all this, I
think the net result is that the sensor filters the energy
in some way, and maps it in a low-energy form onto an
internal representation (what we in the Control Systems
Group would call a "perception").

I believe this leads to a fundamental property of specifically
a _perceptual_ control system (the P in PCT). A perceptual
control system only measures its environment in terms of the
state of its perceptual _input_. (Incidentally, I believe
this holds whether that effective environment be "inside" or
"outside" the organism itself.)

I realize there is often a "Yeah. So what?" reaction
among some control theorists or other dynamic modelers,
when this point is stressed. But I think some important
implications do follow from this elementary point. (For
simplicity, I'll use here your shorthand term of an ECU,
for Elementary Control Unit.)

To restate the point itself, a perceptual control system,
an ECU, does not "care" about anything else, other than
its input. To be precise, it cares about it in relation
to its own reference standard for the preferred state of
that input, but that reference is essentially "given" to
it from outside the ECU loop. It is always trying to
stabilize its input to make it match the (possibly changing)
state of its reference standard.

Another way of saying this is that an ECU does not "know"
about anything else, other than its input. In this
notion of "knowledge", I do include both the changing state
of the perceptual input (i.e., the signal), and the evolved
or learned structure embodied in the perceptual input
function itself. The combination of these two is all
that an elementary perceptual control system knows.

This means, as a corollary, that an ECU does not know or
care about the _source_ of any influences or disturbances
that are affecting its functioning.

[As an aside, I do not think this precludes meta-level ECU's
from arising. By this I mean certain ECU's being constructed
to embody and thereby perceive certain regularities among
disturbances -- (such as, 'a visual perception of rain can
become a tactile perception of wetness'.) If such meta-level
perceptions are constructed, this would confer the possibility
of using an imagined model of the environment to "plan" or
even "predict" perceptions to control for. That might be a
way to fine-tune and stabilize control of what we might call
Sequence or Program perceptions. That's my current take, at
any rate, on the recent discussion of "prediction" on the
CSGNet. End of aside.]

Certain implications follow from this basic property of an
ECU knowing only its input. First of all is a simplicity
of design. The whole world outside (each) ECU is condensed to
a single variable to monitor, into which is rolled both its
own recursive input and the net effects of any and all
"disturbances" from beyond its borders.

Further, how it arrives at stabilized input (relative to
its reference) is immaterial to it. It can stumble upon
it, it can actively bring it about, some other agent can
bring it to pass, it can benefit from some regularity in
the environment; it really doesn't matter.

Granted, the most efficient way is by means of its own
recursive input (i.e., the intended effects of its output
function), since that is the only influence that consistently
pushes the input toward its reference. But its essential
structure will make use of "whatever works".

The payoff of all this is as follows, I believe:

1. There is a flexibility in terms of the control loop's
use of what we would call the environmental feedback
function. This means that there might be countless ways
that negative feedback control could be restored. If one
means doesn't work, try another. That makes for a fairly
robust, self-correcting system. (I realize I'm likely
talking here about a network of integrated ECU's, where
any of its output degrees of freedom might do the trick
for a given ECU.)

2. All influences are treated the same, whether they
originate in environmental disturbances, other control
systems outside the organism, or even other control loops
within the organism. Input, from whatever source, will
simply be monitored and brought closer (if possible) to
the reference standard.

3. If a given ECU can influence the reference of another
ECU, so that the second ECU's functioning helps bring the
input of the first ECU closer to its reference, then a
hierarchy of control loops becomes possible. This is an
extremely robust arrangement, if it can arise.

4. This is perhaps a corollary of the foregoing points.
A given ECU doesn't care how far its feedback path has to
travel before it is closed. That means that extremely
complicated and convoluted feedback paths become possible,
and they will still do the trick.

I think this is why the SD models have such flexibility.
Feedback is feedback -- (albeit with the caveat, that
amplification factors can lead to _directed_ feedback, as
in a PCT control system.) Therefore, there may be complex
interactions of feedback loops. Sometimes these may be
aggregated, as in the Equation Based Modeling of SD. And
sometimes these may be highly specified in terms of the
parameters of Agent Based Modeling, which paradoxically
may lead to emergent phenomena among the agents.

From the standpoint of an Elementary Control Unit, it will

simply monitor its input. Whether the feedback path wends
in and out of other living control systems, or in and out
of organizational (virtual?) control systems, or through the
physical properties of the environment, it all eventually
comes through the single path of the perceptual input function
for that ECU, and that is all the ECU has to pay attention to.

To sum up, let me first just list the various sections of
this post, that I've tried to address:

SD Archetypes
PCT in a SD Framework
Asymmetry of Input and Output
Hierarchical Arrangements of Control
The P in PCT

This has covered more ground than I originally intended
when I started out with this essay. I think the potential
advantages of attending to a Perceptual Control Theory
version of a control system, and incorporating it into
System Dynamics thinking, might be the following qualities
of a PCT approach:

** Modularity (as one or more potential archetypes for
     an SD library)
** Amplification (with its implications for negentropic
     order)
** Partitioning Degrees of Freedom
** Agency (allowing a bottom-up approach to complement
     the top-down modeling of SD)
** Flexibillity (allowing for self-correcting tendencies)
** Simplicity of Design
** Hierarchy (making for rigorous stabilization)
** Handling Complexity
** Robustness

While it is not the only modeling approach, I think PCT
has an awful lot to offer, to complement the work of other
approaches, esp. that of System Dynamics.

Thanks, Martin, for your contributions, that helped to
crystalize these ideas.

All the best,
Erling

P.S. Martin, I am not in contact with any of the System
Dynamics mailing lists. If you are, and if you think it
would contribute to any of the discussions, feel free to
import this post accordingly.

System Dynamics & PCT

[From Erling Jorgensen (2005.02.11 1730 EST)]

Martin Taylor (2005.02.09.17.44)

[prior subject – Re: Just Don’t Get iT]

This was a very helpful post, Martin.

I want to contribute some things I have been mulling over,

about how Perceptual Control Theory may relate to System

Dynamics (SD). I am still new in my exploration of the

SD literature, but I believe I can follow the contours of

SD arguments & models. I’ll use various headings here,

to try to keep the ideas clear.

SD Archetypes

(This section may serve as a brief introduction to SD, for

some on the CSGNet list who may not yet be acquainted with it.)

One natural point of correspondence between the notions of

SD & that of PCT is with regard to what the SD movement calls

“archetypes.” These seem to be various modular
components,

or patterns, that frequently recur in dynamic systems, and

which can be combined in various ways to map onto a specific

problem, to try to obtain explanatory & predictive clarity.

A useful summary of some of the basic SD archetypes can be found

at Gene Bellinger’s website –

<http://www.systems-thinking.org/arch/arch.htm>

He seems to draw upon earlier work by Peter Senge, and of course,

Jay Forrester.

These archetypes are thought to be “generic feedback
structures.”

They include things like a negative feedback “Balancing Loop,”

and a positive feedback “Reinforcing Loop,” and various

combinations that seem to lead to predictable patterns of

dynamic behavior.

Other classic archetypes include: “Success to the Successful”

(two mutually reinforcing positive feedback loops), "Limits

to Success" (a reinforcing loop eventually held in check by

a balancing loop), “Escalation” (two balancing loops in

competition which max out as a reinforcing loop), "Fixes That

Fail" (a balancing loop which becomes reinforcing due to

unintended consequences), and other more complicated combinations

such as “Tragedy of the Commons”, “Shifting the
Burden”, and

“Growth and Underinvestment”.

These archetypes may be commonplace to those familiar with

SD, and they seem to have some utility, esp. to managers and

consultants, in analyzing complicated business or

organizational dynamics.

The specifying of such archetypes is part of a larger project

within the SD movement. It is nicely articulated on the first

page of an article by Scott Rockart, presented at the 2004

System Dynamics Conference. It is available at –

<http://www.systemdynamics.org/conf2004/indexpapers.htm>

[scroll to Rockart, Scott. Number 350. Might Twenty Models

Cover Ninety Percent of All Situations Managers Encounter?]

Quoting from Rockart –

"Jay Forrester’s call for a set of 'general, transferable

computerized cases’ to cover most managerial situations is

one of the great tasks standing before the field of system

dynamics. A library of widely applicable cases, if accompanied

by reliable guidelines for when to apply them, would be a boon

to research, teaching, and management. Researchers could use

these cases as strong null models when evaluating new situations

and new theories (Bell 2001)."

Formulation of modular archetypes has been one response to

Forrester’s call. A more elaborate one has been the specifying

of detailed computerized models of specific problem situations,

which have the potential for being exemplars as they are

modified and applied to other specific situations.

PCT in a SD Framework

My initial reaction to how PCT may fit into such a SD framework

was to consider the basic PCT control loop to be a more precise

mathematical specification for the basic “Balancing Loop”

archetype. Thus, the PCT equations of an elementary control

system nicely elaborate on an item already in the SD library

of archetypes.

In the SD models I have seen, balancing loops frequently occur

as aggregate negative feedback patterns. But I rarely see

a specifically-labelled intentional agent, which is controling

its perceived input as in a classical PCT control system.

This observation may be part of a larger debate in the field,

which contrasts the top-down Equation Based Modeling of typical

SD approaches, with the bottom-up Agent Based Modeling of other

approaches. One reference, also from the 2004 SD Conference,

would be a paper by Nadine Schieritz, "Exploring the Agent

Vocabulary: Emergence and Evolution in System Dynamics",

available at –

<http://www.systemdynamics.org/conf2004/indexpapers.htm>

[again scroll to the author’s name]

It is a reasonable guess that much or most negative feedback,

including that aggregately-displayed in SD computerized models,

derives from the operation of living systems. So it has

occurred to me that perhaps the individual agency of PCT

control systems could be usefully inserted into the “flows”

of SD structural diagrams. This could be a way of marrying

the top-down and bottom-up approaches, and deriving the

benefits of each.

Having said that, there is a drawback to the mathematical

precision of the PCT control loop. Every component and

function on the loop has to be specified, and that includes

the perceptual input function. In PCT modeling to date,

(or rather, in the needed expansion of PCT modeling to new

variables and domains,) this constraint has proved extra-

ordinarily severe.

We just don’t know how to model very many types of

perceptual input functions. We’ve got the equations for

the rest of the loop, and they are extremely rigorous and

flexible in their functioning. But beyond weighted sums,

and logical relations, and a flip-flop here & there, we

do not have realistic functional equations for many of those

other kinds of perceptions that we seem to be able to control.

This is a limitation of the current PCT approach.

An advantage of the SD approach, in terms of this very issue,

is that ad hoc first approximations of the equations, even

expressed with many “non-numerical” types of variables,

can still get you some pretty interesting results. All you

seem to need is some sense of plausible (aggregate) influences,

along with determining which way the feedback sign should go

– positive or negative. With that, you can get a first

version simulation of a dynamical system up and running, so

you can start to examine its implications. This payoff seems

to be behind the “movement” appeal of the SD approach.

Asymmetry of Input and Output

Martin, this was the most helpful part of your post to me.

Specifically, you said –

there is a specific aspect of PCT that identifies where it

fits into the more general System Dynamics area. That

specific aspect is the essential asymmetry between the

input and the output side of the PCT loop.

In other words, classic PCT control loops all contain a

significantly large amplification factor in the output

function (typically called “gain”). This allows even a

small mismatch between a current perception and the

preferred reference state for that variable to generate

a potentially large output to try to correct the mismatch.

This capacity appears to be a fundamental property of

living systems.

SD structural diagrams certainly have room for such

amplification factors. I believe they appear as auxilliary

equations inserted into rate equations. But you are

right, Martin, they do not appear to be intrinsic aspects,

as they are with a PCT control loop.

And this gain factor, in concert with the error-reducing

arrangement of negative feedback itself, seems to be

pivotal in a thermodynamic sense, for developing the local

pockets of negentropic order, which characterize living

processes.

I believe this intrinsic aspect of how PCT equations are

calculated, with a large gain or amplication in the output

function, makes a PCT control loop an even better candidate

for inclusion in the SD library of basic modules.

I wondered about another aspect of your observations,

Martin. You said –

If you read, for example, the System Dynamics mailing

list, you will see lots of discussion of negative (and

positive) feedback, but almost nothing on control. The

feedback loops of interest tend to be symmetric in that

the energy levels and amplification factors are not

intrinsically different in different parts of the

circuits.

I agree with your observation. I wonder if this is because

the feedback effects in an SD model are most commonly

through the side effects of control. In other words,

control processes are interfering with each other, (and

being aggregated in an SD model). But the interference

effects are often the result of accidental disturbance,

rather than concerted disturbance, if I can put it that

way.

A head-to-head conflict between two control loops trying

to control for different values of the same variable,

brings all the help and heartache of amplification factors

into full bloom. You can’t help but notice their effects.

But when specific control systems are not explicitly modeled

(as their own controling agents) in an SD simulation, it

seems that interferences would tend to cancel one another

out in the aggregate, as side effects that are not

deliberately controlled. I think this would tend to leave

a relatively small net feedback, which is either negative

or positive in an SD rate equation. This may be why we don’t

see much asymmetry in different parts of the feedback loops

of SD models.

Hierarchical Arrangements of Control

A stronger candidate for inclusion in an SD library of

archetypal modules, I believe, is a basic PCT arrangement

of two (or more) control loops in a hierarchical relation.

(BTW, this has nothing to do with any particular proposals

of what levels of perception may occur in humans, as put

forward in what we customarily call HPCT.)

Bill Powers has produced some very robust demonstrations-

of-principle, with stabilized control occurring at multiple

levels of hierarchically-internested PCT control loops. Two

models that come to mind are a) his control of an inverted

pendulum by means of (I think) six layers of control, and

b) some of the work he reported with using derivatives as

controlled variables, in multiple layers, to improve the

resolution of inherently fuzzy star images (I think I’m

remembering that correctly).

As long as certain properties are adhered to, a hierarchical

arrangement of control loops – where lower levels of control

are the means of implementing higher levels of control –

can arrive at very stable control of several variables at

once. I have likened the difference between the topmost

layer and the lower layers in this way: The topmost layer

implements control as essentially a compensatory tracking

task, despite disturbances percolating up from lower in the

hierarchy. Each lower layer implements control as essentially

a pursuit tracking task, seeing as its next-higher layer may

be dynamically changing the reference signal on the fly, so

that the higher layer also achieves adequate control. Control

of perceptual variables is happening at all levels. But for

lower levels it looks like the goal for each one is moving all

over the place.

Perhaps this combination of the appearance of compensatory

tracking at the highest level and pursuit tracking at each

lower level might qualify for some kind of mini-archetype…

(:slight_smile: whaddya think?) It is perhaps worth noting, that the

moving target of the lower level’s pursuit tracking task

does appear in the SD list of archetypes as currently

formulated. There is one entitled “Drifting Goals”, which

seems to involve two Balancing Loops in a hierarchical

relation, with a “pressure to adjust desire” (i.e., change

the reference standard). I am not convinced that it operates

exactly as outlined, but it is trying to capture the dynamic

where a system "reaches an equilibrium other than what was the

initial desired state" (cited from Gene Bellinger’s website –

<http://www.systems-thinking.org/arch/arch.htm>
).

One of the key properties that must be included, for

hierarchically-arranged control loops to operate correctly

without inherent instabilities, is that a higher layer

must operate at a slower rate relative to a lower layer.

(In terms of evidence, I think this can be demonstrated

fairly simply with most any of the PCT simulations.)

The easiest way to understand this is that you can’t call

for results from a lower level faster than they can be

produced.

A key benefit of hierarchically-arranged control is that

tasks can be partitioned into independent degrees of freedom,

without sacrificing precision of control. And the components

needed to maintain control over each degree of freedom can

be relatively simple (i.e., the equations of a basic PCT

control loop). This enormously simplifies the modular task

of building up more complicated forms of control.

The P in PCT

Martin, I appreciate your thermodynamic formulations of

what is involved in PCT control systems. You describe –

the necessary structure: a low-energy “sensor” (a portal

through the “shell”) leading to a low-energy internal
state,

which in some fashion affects actions that can counter the

potentially damaging high-energy influence.

This is the basis for the amplification of output and the

asymmetry, that was discussed above. What I’m struck with

here is the filtering effects of the 'sensor through the

shell’s portal’.

Control systems need not directly represent all of what is

outside the shell. Indeed, I think you are arguing even

stronger that they cannot; the energy differences are

sometimes too great. For instance –

If the internal representation depended on energy levels

similar to the potentially damaging influence, they would

themselves be damaging to the organism.

While I am not sure I follow the necessity of all this, I

think the net result is that the sensor filters the energy

in some way, and maps it in a low-energy form onto an

internal representation (what we in the Control Systems

Group would call a “perception”).

I believe this leads to a fundamental property of specifically

a perceptual control system (the P in PCT). A perceptual

control system only measures its environment in terms of the

state of its perceptual input. (Incidentally, I believe

this holds whether that effective environment be “inside” or

“outside” the organism itself.)

I realize there is often a “Yeah. So what?” reaction

among some control theorists or other dynamic modelers,

when this point is stressed. But I think some important

implications do follow from this elementary point. (For

simplicity, I’ll use here your shorthand term of an ECU,

for Elementary Control Unit.)

To restate the point itself, a perceptual control system,

an ECU, does not “care” about anything else, other than

its input. To be precise, it cares about it in relation

to its own reference standard for the preferred state of

that input, but that reference is essentially “given” to

it from outside the ECU loop. It is always trying to

stabilize its input to make it match the (possibly changing)

state of its reference standard.

Another way of saying this is that an ECU does not “know”

about anything else, other than its input. In this

notion of “knowledge”, I do include both the changing state

of the perceptual input (i.e., the signal), and the evolved

or learned structure embodied in the perceptual input

function itself. The combination of these two is all

that an elementary perceptual control system knows.

This means, as a corollary, that an ECU does not know or

care about the source of any influences or disturbances

that are affecting its functioning.

[As an aside, I do not think this precludes meta-level ECU’s

from arising. By this I mean certain ECU’s being constructed

to embody and thereby perceive certain regularities among

disturbances – (such as, 'a visual perception of rain can

become a tactile perception of wetness’.) If such meta-level

perceptions are constructed, this would confer the possibility

of using an imagined model of the environment to “plan” or

even “predict” perceptions to control for. That might be
a

way to fine-tune and stabilize control of what we might call

Sequence or Program perceptions. That’s my current take, at

any rate, on the recent discussion of “prediction” on the

CSGNet. End of aside.]

Certain implications follow from this basic property of an

ECU knowing only its input. First of all is a simplicity

of design. The whole world outside (each) ECU is condensed to

a single variable to monitor, into which is rolled both its

own recursive input and the net effects of any and all

“disturbances” from beyond its borders.

Further, how it arrives at stabilized input (relative to

its reference) is immaterial to it. It can stumble upon

it, it can actively bring it about, some other agent can

bring it to pass, it can benefit from some regularity in

the environment; it really doesn’t matter.

Granted, the most efficient way is by means of its own

recursive input (i.e., the intended effects of its output

function), since that is the only influence that consistently

pushes the input toward its reference. But its essential

structure will make use of “whatever works”.

The payoff of all this is as follows, I believe:

  1. There is a flexibility in terms of the control loop’s

use of what we would call the environmental feedback

function. This means that there might be countless ways

that negative feedback control could be restored. If one

means doesn’t work, try another. That makes for a fairly

robust, self-correcting system. (I realize I’m likely

talking here about a network of integrated ECU’s, where

any of its output degrees of freedom might do the trick

for a given ECU.)

  1. All influences are treated the same, whether they

originate in environmental disturbances, other control

systems outside the organism, or even other control loops

within the organism. Input, from whatever source, will

simply be monitored and brought closer (if possible) to

the reference standard.

  1. If a given ECU can influence the reference of another

ECU, so that the second ECU’s functioning helps bring the

input of the first ECU closer to its reference, then a

hierarchy of control loops becomes possible. This is an

extremely robust arrangement, if it can arise.

  1. This is perhaps a corollary of the foregoing points.

A given ECU doesn’t care how far its feedback path has to

travel before it is closed. That means that extremely

complicated and convoluted feedback paths become possible,

and they will still do the trick.

I think this is why the SD models have such flexibility.

Feedback is feedback – (albeit with the caveat, that

amplification factors can lead to directed feedback, as

in a PCT control system.) Therefore, there may be complex

interactions of feedback loops. Sometimes these may be

aggregated, as in the Equation Based Modeling of SD. And

sometimes these may be highly specified in terms of the

parameters of Agent Based Modeling, which paradoxically

may lead to emergent phenomena among the agents.

From the standpoint of an Elementary Control Unit, it will

simply monitor its input. Whether the feedback path wends

in and out of other living control systems, or in and out

of organizational (virtual?) control systems, or through the

physical properties of the environment, it all eventually

comes through the single path of the perceptual input function

for that ECU, and that is all the ECU has to pay attention to.

To sum up, let me first just list the various sections of

this post, that I’ve tried to address:

SD Archetypes

PCT in a SD Framework

Asymmetry of Input and Output

Hierarchical Arrangements of Control

The P in PCT

This has covered more ground than I originally intended

when I started out with this essay. I think the potential

advantages of attending to a Perceptual Control Theory

version of a control system, and incorporating it into

System Dynamics thinking, might be the following qualities

of a PCT approach:

** Modularity (as one or more potential archetypes for

 an SD library)

** Amplification (with its implications for negentropic

 order)

** Partitioning Degrees of Freedom

** Agency (allowing a bottom-up approach to complement

 the top-down modeling of SD)

** Flexibillity (allowing for self-correcting tendencies)

** Simplicity of Design

** Hierarchy (making for rigorous stabilization)

** Handling Complexity

** Robustness

While it is not the only modeling approach, I think PCT

has an awful lot to offer, to complement the work of other

approaches, esp. that of System Dynamics.

Thanks, Martin, for your contributions, that helped to

crystalize these ideas.

All the best,

Erling

P.S. Martin, I am not in contact with any of the System

Dynamics mailing lists. If you are, and if you think it

would contribute to any of the discussions, feel free to

import this post accordingly.

Thanks Erling, I found the post very interesting and
relevant contextualizing and assessing PCT through SD
lens.

···

At 02:40 PM 12/02/2005, you wrote:
Rohan Lulham
Ph.D. Student
Environment, Behaviour and Society Research Group
Faculty of Architecture, University of Sydney
Australia

[From Erling Jorgensen (2005.02.12 1500 EST)]

Rohan Lulham (Sat, 12 Feb 2005 19:19:58 [Aus])

Thanks Erling, I found the post very interesting and relevant
contextualizing and assessing PCT through SD lens.

Thank you for the feedback, Rohan. I'm glad it was helpful.

It's a little hard to gauge from the lack of response whether
others found it useful as well. I know others have commented
from time to time on finding themselves in a similar position,
with few or no responses to a given post, & not knowing how
to interpret that.

A basic implication of PCT is "no error, no action," (or at
least no change in action). From that I have to surmise
that my post did not lead to sufficient error for others'
perceptions to call for corrective action. But as the
Behavioral Illusion reminds us, it can be hard to infer
the intentions or the reasons for the (lack of) action.

There are several possibilities. One is that the post
was perceived as making pretty good sense as it stands, so
'what's to comment on?'. Another is that it was perceived
as irrelevant for some folks, for whatever reason -- e.g.,
main interests elsewhere, too busy, etc. Another is that
there was disagreement, but no real desire to pursue it.
Another is that any resulting error is still in the process
of being corrected.

I am aware that I try to have pretty high standards for
myself when I post to CSGNet. I suspect that it's tied to
an environmental regularity growing up, where there was a
lot of criticism flying around. So I think I fairly
consistently try to control for not leaving myself too
vulnerable to perceived criticism. One way I do that is
by trying to catch the errors or inconsistencies in my
contributions before others do.

An unintended (or not fully intended) side effect of that,
I think, is that it tends to limit the amount of interaction
I receive from others. Interactions proceed off the energy
of the unfinished components ("error" in a PCT sense), and
once those are taken care of we move on to something else.

I suspect I would get more responses if I weren't quite
so cautious, and left more room for others to collaboratively
help work out the inadequacies of a given subject I was
interested in. Then others would have more of a stake in the
process, because as we know, people control their own
perceptions for their own reasons, not because others think
they "should" be interested in a given issue.

Being a fairly autonomous person -- let me correct that:
every person is autonomous, but I think I control for a
good deal of perceived autonomy. Because of that, I am
mostly content to post to the net when I think I have
something valuable to contribute, and then to let others
do with it (or not) what they will.

But I will confess to wanting at least some response or
indications from others, so I can check on the alignment
of my ideas with theirs. Again, thanks for your reply
in that regard.

All the best,
Erling

[From Rick Marken (2005.02.12.1250)]

Erling Jorgensen (2005.02.12 1500 EST) to Rohan --

Thank you for the feedback, Rohan. I'm glad it was helpful.

It's a little hard to gauge from the lack of response whether
others found it useful as well.

But I will confess to wanting at least some response or
indications from others, so I can check on the alignment
of my ideas with theirs.

I didn't reply because, though I didn't agree with much of your post on PCT and SD, I didn't disagree with it enough to want to take the trouble to reply. I didn't agree with your post because what is important about PCT is how it _differs_ from SD (and other applications of control theory), not how it is similar. I think nothing has caused more problems for PCT than the idea that it is similar to some existing theory of behavior. It results in people going off thinking they are using PCT when, in fact, they are not. I guess I didn't respond to your post because, after 25 years of confronting this problem, I think I've finally realized that there is _nothing_ I can do about it.

Best

Rick

···

----
Richard S. Marken
marken@mindreadings.com
Home 310 474-0313
Cell 310 729-1400

[From Brian D'Agostino (2005.02.12.1520)]

I found Erling's post very helpful. I was not familiar with system dynamics previously, and I came away with a good introduction and also with a better appreciation of what is unique about PCT. In this regard, I'm puzzled by Rick Marken's post (2005.02.12.1250), which reads:

I didn't reply because, though I didn't agree with much of your post on PCT and SD, I didn't disagree with it enough to want to take the trouble to reply. I didn't agree with your post because what is important about PCT is how it _differs_ from SD (and other applications of control theory), not how it is similar. I think nothing has caused more problems for PCT than the idea that it is similar to some existing theory of behavior. It results in people going off thinking they are using PCT when, in fact, they are not. I guess I didn't respond to your post because, after 25 years of confronting this problem, I think I've finally realized that there is _nothing_ I can do about it.

I'm puzzled by this, because I don't see how anyone reading Erling's post could possibly confuse PCT and SD, or to think that the two theories are redundant. On the contrary, Erling's post makes it clear that the two theories address different things, and therefore are not competing with each other. Why is Rick so threatened by the idea that PCT might be related to something other than itself in a fruitful way that benefits both theories. Why do the leaders of CSG need to maintain this Olympian posture of being superior to everything else that's out there? This is a very personal question for me, because I presented work to CSG some years ago on the psychology of militarism, which was informed by PCT but addressed questions that no one in CSG was asking, using statistical methods that were suitable to the rather urgent real world problem I was addressing (why people support wars and war preparations), and the attitude in CSG was "this is not what we do, your work has no value to us." (See Self-Images of Hawks and Doves: A Control Systems Model of Militarism, _Political Psychology_ Vol 16, No. 2, 1995) So for my part, I would like to get beyond this kind of thinking and open CSG to precisely the kind of dialogues that Erling's thinking makes possible, in this case with the SD community.

Brian D'Agostino
bdagostino@verizon.net
212-864-1159

[From Erling Jorgensen (2005.02.12 1750 EST)]

Rick Marken (2005.02.12.1250)

Thanks for your candor and clarity about how you see this.

I didn't agree with your post because what is important about
PCT is how it _differs_ from SD (and other applications of
control theory), not how it is similar.

I suspect we need both tasks, articulating how it differs
and how it is similar.

I think nothing has caused more problems for PCT than the
idea that it is similar to some existing theory of behavior.
It results in people going off thinking they are using PCT
when, in fact, they are not.

Two thoughts here. People cannot avoid "using PCT", if we
are correct in our beliefs that people are indeed living control
systems.

However, this is not the same as "understanding PCT," which
I think is the point you're getting at here. And there are
indeed problems with people of poor understanding "thinking
they are using PCT."

To my mind, the problem is especially acute when folks are
analyzing in terms of linear causality instead of circular
causality. This is why I have less problem with what the SD
folks are doing, because _finally_ somebody is getting it
right that the dynamics of living systems have to be based
on feedback patterns of circular causality.

There are some important differences between PCT & SD, which
the post tried to point out, but because SD is already in
the circular causality camp (albeit with aggregate methods),
I think there is room for augmentation between the two
approaches.

I guess I didn't respond to your post because, after 25 years
of confronting this problem, I think I've finally realized
that there is _nothing_ I can do about it.

You definitely have expended more energy and time in these
trenches than I have. And you have succeeded in getting
quite of lot of your efforts published, which I really
appreciate & have benefitted from.

I suspect we control for different preferences in terms of
strategy. I don't think there has to uniformity in our
respective approaches.

All the best,
Erling

From Marc Abrams (2005.02.12.1709)]

In a message dated 2/12/2005 4:33:47 P.M. Eastern Standard Time, bdagostino@VERIZON.NET writes:

[From Brian D’Agostino (2005.02.12.1520)]

So for my part, I would like to get beyond this kind of thinking and
open CSG to precisely the kind of dialogues that Erling’s thinking makes
possible, in this case with the SD community.

Brian D’Agostino
bdagostino@verizon.net
212-864-1159
A very nice idea, I just don’t think you have a chance in hell of this happening on CSGnet, unfortunately.

Marc

[From Rick Marken (2005.02.12.1555)]

Erling Jorgensen (2005.02.12 1750 EST)--

Rick Marken (2005.02.12.1250)

I think nothing has caused more problems for PCT than the
idea that it is similar to some existing theory of behavior.
It results in people going off thinking they are using PCT
when, in fact, they are not.

Two thoughts here. People cannot avoid "using PCT", if we
are correct in our beliefs that people are indeed living control
systems.

I don't think that's true. Obviously, psychologists have been able to use theories that are completely inconsistent with PCT for years without any obvious problem.

However, this is not the same as "understanding PCT," which
I think is the point you're getting at here.

Sort of. It's a hard point to make without sounding like I'm _for_ PCT and _against_ some other application of control theory. To me, PCT is mainly a way of approaching the problem of understanding behavior. The basis of this understanding is control theory so there will be a lot of overlap between PCT and other control theory-based approaches to understanding behavior. I think we should celebrate those aspects of these other approaches that are consistent with PCT, ignore those aspects that are wrong (for example, when they do analyses based on the assumption that the reference signal is outside the system) and learn from those aspects that _appropriately_ go beyond what we currently know (by "correctly" I mean that they as clearly based on a PCT-based understanding of how to model living systems).

A friend of mine referred me to a recent article by Thomas Sheridan called "Driver distraction from a control theory perspective" (_Human Factors_, 46 (4), 2004, pp. 587-599). Sheridan is a pioneer in the application of control theory to understanding human behavior. He is part of what I have called the "manual control" school. This is the school that can analyze the heck out of a control system but can't seem to figure out that the reference signal is _inside_ the controller. But in this article, Sheridan finally gets it. He puts the reference (he even calls it the "intention") inside the system and correctly shows that it is a sensed representation of the actual state of the vehicle that is controlled. I haven't read the entire paper yet, but, so far, it looks very good. I think he makes nice use of a control model to make predictions about how various kinds of distraction (which he calls disturbances) might affect driving behavior, depending on whether the distraction leads to a change in the reference, the perception or the effect of output on the system. In fact, the paper seems startlingly similar to my paper describing a control _framework_ for understanding prescribing error.

I guess my point is this: I don't judge ideas based on the "school" from whence then come. Ideas aren't worthwhile because they come from PCT or manual control or SD or whatever. It's the ideas that matter. The Sheridan article happens to be a nice example of some ideas that I find potentially useful, even though they _happen_ to come from a manual control theorist. It's the ideas that matter. Saying that some theory, like SD, is consistent with PCT over-generalizes in a way that, I think, leads people to think they are using PCT when, in fact, they are not. Sheridan's article is worth considering because he doesn't think he is using PCT when, to a large extent, he is.

And, yes, I plan to write to Sheridan and tell him all kinds of nice things about his paper.

Best

Rick

···

---
Richard S. Marken
marken@mindreadings.com
Home 310 474-0313
Cell 310 729-1400

[From Bill Powers (2005.02.12.1709 MST)]

Erling Jorgensen (2005.02.12 1500 EST) --

It takes a bit of time to follow up on everything in every thread, and often a bit more than I actually have for this.

The "Archetypes" of SD simply show what is to be expected in certain arrangements of computing blocks. We see an ordinary negative feedback control system, a positive feedback system, interacting negative and positive feedback systems, and of course conflicting feedback systems. It's good to be able to recognize them when you see them and know what sort of behavior to expect. The idea of developing a cookbook approach might be useful, especially for people who know nothing of control theory or analog computing.

My own inclination is to prefer to analyse each system as it comes along rather than trying to match it to some previous situation. There's always a danger that the resemblance to a known situation might be too approximate, so unless one simply does the system analysis anyway (in which case why use the archetypes?), one can easily make wrong predictions. For example, positive feedback situations can exist without causing disasters, but it doesn't take much change in parameters like lag and gain to create explosive blowups rather than mild enhancements of reactions.

Best,

Bill P.

From [Marc Abrams (2005.02.12.1923)

This post from Rick serves, I believe several useful purposes. I’ll leave it up to each of you to figure out exactly what those benefits might be.

I will say at the outset that the entire premise of Rick’s post is a Straw man.

Rick has it in his mind that SD is a competing theory of PCT and he just doesn’t get or understand Martin Taylor, or myself.

SD is the calculus, a method; it is not a competing theory of behavior to PCT. With this in mind lets go to the post.

In a message dated 2/12/2005 6:54:10 P.M. Eastern Standard Time, marken@MINDREADINGS.COM writes:

[From Rick Marken (2005.02.12.1555)]

Erling Jorgensen (2005.02.12 1750 EST)–

Rick Marken (2005.02.12.1250)

I think nothing has caused more problems for PCT than the
idea that it is similar to some existing theory of behavior.
It results in people going off thinking they are using PCT
when, in fact, they are not.
This argument by Rick is a red herring as well.

First, Rick talks about ‘competing’ theories. But Erling is not. Erling is talking about SD & PCT. Second, Erling was not talking about what people were thinking about when they were attempting to learn PCT.

Two thoughts here. People cannot avoid “using PCT”, if we
are correct in our beliefs that people are indeed living control
systems.

I don’t think that’s true. Obviously, psychologists have been able to
use theories that are completely inconsistent with PCT for years
without any obvious problem.

Sorry, another red herring here. Erling was talking about how since PCT is about all human behavior, anybody talking about behavior must be talking about and observing things PCT SHOULD be able to explain.

Erling was not talking about the logical consistency of any theory.

However, this is not the same as “understanding PCT,” which
I think is the point you’re getting at here.

Sort of. It’s a hard point to make without sounding like I’m for PCT
and against some other application of control theory.

Gee, why would anyone in his right mind think that?

But SD is NOT an application of control theory. SD is an application of the calculus.

To me, PCT is mainly a way of approaching the problem of understanding behavior.

Me too, but unfortunately it is still very much of a work in progress.

The basis of this understanding is control theory so there will be a lot of
overlap between PCT and other control theory-based approaches to
understanding behavior.

Yes, and saying it is BASED on control theory, is like saying it is based on the calculus. Maybe a theory of human behavior needs to be BASED on DATA and VALIDATED with a model, rather than the other way around.

I think we should celebrate those aspects of
these other approaches that are consistent with PCT, ignore those
aspects that are wrong (for example, when they do analyses based on the
assumption that the reference signal is outside the system) and learn
from those aspects that appropriately go beyond what we currently
know (by “correctly” I mean that they as clearly based on a PCT-based
understanding of how to model living systems).

This is an excellent strategy. When do you plan on starting it?

A friend of mine referred me to a recent article by Thomas Sheridan
called “Driver distraction from a control theory perspective” (Human
Factors
, 46 (4), 2004, pp. 587-599). Sheridan is a pioneer in the
application of control theory to understanding human behavior.

Rick, if you spent just a wee bit of time looking at some literature, you would find a wealth of ‘PCT’ style thinking out there. But then again, that may very well be the reason you don’t want to look.

The question remains; given this, what does PCT provide him that would enhance their understanding of the problem? NOT your theory.

I guess my point is this: I don’t judge ideas based on the “school”
from whence then come. Ideas aren’t worthwhile because they come from
PCT or manual control or SD or whatever. It’s the ideas that matter.

I wish you actually believed this, but this is a MYTH of the worst kind, because you are not even capable of being honest with yourself.

It is obvious from Bill Powers’ post that he too is ignorant of SD and has not read my posts on it. So, if I am a 15 year old undereducated moron, what does that make him?

The Sheridan article happens to be a nice example of some ideas that I
find potentially useful, even though they happen to come from a
manual control theorist.

For what?

It’s the ideas that matter.

If you repeat this enough times you might even begin to believe it, but I doubt it.

Saying that some
theory, like SD, is consistent with PCT over-generalizes in a way that,
I think, leads people to think they are using PCT when, in fact, they
are not.

Yes, this is certainly true, along with the notion that you have absolutely no idea about what SD is about.

Sheridan’s article is worth considering because he doesn’t
think he is using PCT when, to a large extent, he is.

And, yes, I plan to write to Sheridan and tell him all kinds of nice
things about his paper.

I’m sure Sheridan will be thrilled to hear from you, just don’t discuss the merits of SD, and stick to congratulating him. I’m sure he will feel honored that he is ‘doing’ PCT, even though he currently doesn’t realize it.

I see it’s just about time for me to log off again, I’ll hang until tomorrow and see if any one responds to my posts.

Marc

Marc

[From Rick Marken (2005.02.13.0030)]

Brian D'Agostino (2005.02.12.1520)--

Why is Rick so threatened by the idea that PCT might be related to something other than itself in a fruitful way that benefits both theories.

I'm not threatened by this idea. I just don't often see this kind of thing. If you have something specific in mind -- some theory that will benefit PCT -- please feel free to bring it up. But don't expect whatever you present to get an uncritical reception.

Why do the leaders of CSG need to maintain this Olympian posture of being superior to everything else that's out there?

I'm not a leader of PCT. I'm just someone who is interested in developing a scientific understanding of living systems in general (and human systems in particular). And I have found the PCT model to be the best basis for doing this . If there are ideas out there that are superior to PCT or can improve my work then I'd be glad to hear about them.

This is a very personal question for me, because I presented work to CSG some years ago on the psychology of militarism, which was informed by PCT... and the attitude in CSG was "this is not what we do, your work has no value to us." ..So for my part, I would like to get beyond this kind of thinking and open CSG to precisely the kind of dialogues that Erling's thinking makes possible, in this case with the SD community.

If our criticism of your work was really just "this is not what we do, your work has no value to us" then I agree that we should get the dialog beyond that. But I think the criticism was a bit more substantive than that. I suggest that if you don't agree with criticism of your work then just try to answer the criticism in a convincing way. Or do you want us to do away with critical discussion on CSGNet entirely?

Richard S. Marken
marken@mindreadings.com
Home 310 474-0313
Cell 310 729-1400

[From Brian D'Agostino (2005.02.13.0456)]

[From Rick Marken (2005.02.13.0030)]

Brian D'Agostino (2005.02.12.1520)--

Why is Rick so threatened by the idea that PCT might be related to something other than itself in a fruitful way that benefits both theories.

I'm not threatened by this idea. I just don't often see this kind of thing. If you have something specific in mind -- some theory that will benefit PCT -- please feel free to bring it up. But don't expect whatever you present to get an uncritical reception.

Whenever PCT aims to address processes at the level of self psychology, it can benefit from other psychological research on the self, such as work in the psychoanalytic tradition. Of course such work is not and cannot be replicable science, any more than MOL can. But replicable science has its limits when we undertake to explore human subjectivity, which is why practitioners of MOL, psychoanalysis, etc. need to proceed as they do. Because there is no objective check on what they do, much of it will prove to be a waste of time, but peer reviewed scientific journals are also filled with work that satisfies rigorous objective methods and may also be a waste of time, so quality control in scientific work is an elusive problem that we are not going to solve on CSGnet.

Why do the leaders of CSG need to maintain this Olympian posture of being superior to everything else that's out there?

I'm not a leader of PCT.

Yes, and John Paul II not really the Pope, just an ordinary Catholic humbling practicing his faith in the privacy of the Vatican.

I'm just someone who is interested in developing a scientific understanding of living systems in general (and human systems in particular). And I have found the PCT model to be the best basis for doing this . If there are ideas out there that are superior to PCT or can improve my work then I'd be glad to hear about them.

Again, the assumption is: another theory either has to be superior to PCT or inferior to it. This precludes at the outset any possibility of a genuine dialogue and exchange. This is dominance-submission stuff, and the psychoanalytic literature has plenty to offer you in understanding it. You said you would be "glad to hear about [this]," but I'm skeptical.

This is a very personal question for me, because I presented work to CSG some years ago on the psychology of militarism, which was informed by PCT... and the attitude in CSG was "this is not what we do, your work has no value to us." ..So for my part, I would like to get beyond this kind of thinking and open CSG to precisely the kind of dialogues that Erling's thinking makes possible, in this case with the SD community.

If our criticism of your work was really just "this is not what we do, your work has no value to us" then I agree that we should get the dialog beyond that. But I think the criticism was a bit more substantive than that. I suggest that if you don't agree with criticism of your work then just try to answer the criticism in a convincing way. Or do you want us to do away with critical discussion on CSGNet entirely?

No, Rick, I don't want to do away with critical discussion on CSGNet. If you go back and read the archives (I think the discussion of my work would have been in 1995 or 1996), you will see that I answered _all_ the substantive criticisms that you, Bill and others made of my work. In the end, you either conceded on the individual points or simply stopped responding. This is in the archival record of CSG. I think it will be apparent from the record that you proceeded from the assumption that my work was based on the statistical fallacy, and that I showed that the problem I was asking required survey research and statistical analysis and that I performed both with integrity and used PCT as part of my theoretical framework. In so doing I brought objective scientific methods to the study of phenomena that previously were examined using only subjective methods such as MOL and psychoanalysis. (See B. D'Agostino, Self-Images of Hawks and Doves: A Control Systems Model of Militarism, _Political Psychology_ Vol 16, No. 2, 1995). But while all of that occurred on CSGnet, and in person at one of the summer conferences, no ongoing scientific dialogue ever came out of it because, as I said, the attitude from you and Bill remained, even after the abovementioned critical dialogue, "we don't do this, your work has no value to us." I should mention that some individual members of CSG found my work worthwhile, but you and Bill signaled unambiguously to the community that this work was not worthy of the group's attention, and it was thereafter excluded from CSG's agenda. That is not "critical discussion," it is authoritarian social behavior.

Brian D'Agostino
bdagostino@verizon.net
212-864-1159

···

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From [Marc Abrams (92005.02.13.1045)]

I’m jumping in here because I believe I have something to offer.

In a message dated 2/13/2005 3:28:09 A.M. Eastern Standard Time, marken@MINDREADINGS.COM writes:

[From Rick Marken (2005.02.13.0030)]

Brian D’Agostino (2005.02.12.1520)–

Why is Rick so threatened by the idea that PCT might be related to
something other than itself in a fruitful way that benefits both
theories.

I’m not threatened by this idea. I just don’t often see this kind of
thing. If you have something specific in mind – some theory that will
benefit PCT – please feel free to bring it up. But don’t expect
whatever you present to get an uncritical reception.
This exchange typifies many I have seen down and through the years and one I only recently have been able to understand from both sides, or at least I think so. :slight_smile:

PCT is a very specific way Bill has decided to look at the human nervous system. In it he has basically broken down ‘behavior’ down to the ‘cell’ level. That is, PCT is intended to represent control processes at there most basic and fundamental level.

A good question is, what exactly is that level? That is, does control’ begin at the organ system level, cell level, DNA, organism, etc? Or _all of the above, but in somewhat different configurations. Again, does this mean 'PCT" operates the same way at the cellular level as it does for an organism?

So a central question is, exactly what does PCT represent? the actions of what?

Well we have seen that it can and has represented just about everything, as it should. But the current structure (hierarchy) cannot account for all of this. Only a very small limited view right now.

So when Rick, says you are NOT doing PCT what he is saying is that you are not representing the behavior in a way that actually shows the feedback, but what Rick has failed to see, is that many times people are either viewing a part of a larger system, or they simply do not understand that what they are witnessing is in fact a feedback process.

People unfortunately wind up talking past each other because neither one really understands what the other is saying and neither party asks for or gets clarification, so everyone walks away pissed.

Why do the leaders of CSG need to maintain this Olympian posture of
being superior to everything else that’s out there?

I’m not a leader of PCT.
This is simply not true. You like referring to yourself as Powers’ right hand man and ultimate successor. Successor to what if not the ‘throne’ of CSGnet, or more accurately the King of PCT.

I’m just someone who is interested in
developing a scientific understanding of living systems in general (and
human systems in particular). And I have found the PCT model to be the
best basis for doing this . If there are ideas out there that are
superior to PCT or can improve my work then I’d be glad to hear about
them.
And Rick, believe it or not, this holds true for EVERYONE. So all PCT has to do is ‘show’ its ‘superiority’ and others will climb onboard. Don’t, and the flock will dissipate. It’s that simple.

If our criticism of your work was really just “this is not what we do,
your work has no value to us” then I agree that we should get the
dialog beyond that.
How?

But I think the criticism was a bit more
substantive than that. I suggest that if you don’t agree with criticism
of your work then just try to answer the criticism in a convincing way.
Or do you want us to do away with critical discussion on CSGNet
entirely?

This is both a red herring and a strawman fallacious argument.

A red herring because Rick brings up the relevancy of a ‘critical discussion’ on CSGnet which was not the point of Brian’s criticism , diverting the attention away from the criticism of him not being open to hear new ideas. It is also a strawman because he counter-claimed that Brian was too sensitive to criticism, distorting what Brian said, and making it easy to attack Brian as being ‘too sensitive’ to criticism rather than addressing Brian’s concern for Rick being unable to accept new ideas. Rick simply made the argument about Brian instead of himself.

A worthwhile endeavor for a control system IF you can get away with it.

Sorry Rick, you BS is over. I will expose you all the time and everytime you try to pull this crap on this net. Get used to it.

I appreciate the good arguments you are certainly capable of bringing to the table. I hope to see more of those and less of these.

regards,

Marc

[From Rick Marken (2005.02.13.0935)]

Marc Abrams (92005.02.13.1045)--

Rick Marken (2005.02.13.0030)--

I'm not a leader of PCT.

This is simply not true. You like referring to yourself as Powers' right hand man and ultimate successor. Successor to what if not the 'throne' of CSGnet, or more accurately the King of PCT.

Please show me where I have I ever referred to myself as "Powers' right hand man and ultimate successor".

I don't mind your silly insults and useless blather. But I don't appreciate substantive lies like this. Some people might actually believe this crap.

Richard S. Marken
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From [Marc Abrams (2004.02.13.1239)]

In a message dated 2/13/2005 12:36:39 P.M. Eastern Standard Time, marken@MINDREADINGS.COM writes:

[From Rick Marken (2005.02.13.0935)]

Please show me where I have I ever referred to myself as “Powers’ right
hand man and ultimate successor”.
Oh, you did not use those words. So the strawman strikes again.

You often referred to yourself as some ancient Greek companion to a god, which I cannot recall the specific name of, because of my lack of knowledge about the classics, but the implications were clear.

I don’t mind your silly insults and useless blather.
[Ad hominem attack]

But I don’t appreciate substantive lies like this.
Be VERY careful who you accuse things of and what you accuse them of. You really seem vindictive and petty. Like your flailing around without the capacity to come back with a substantive argument about the ideas that are causing you so much pain. You look weak and hapless

Some people might actually believe this crap.
Why?

[From Rick Marken (2005.02.13.1015)]

Marc Abrams (2004.02.13.1239)--

Rick Marken (2005.02.13.0935)]

Please show me where I have I ever referred to myself as "Powers' right
hand man and ultimate successor".

You often referred to yourself as some ancient Greek companion to a god, which I cannot recall the specific name of, because of my lack of knowledge about the classics, but the implications were clear.

Then you should have no trouble finding several examples ("often" is more than once).

I think I might have once compared my relationship to Bill to T.H. Huxley's relationship to Darwin. But that was just for fun. I do consider myself an ardent advocate of Bill's ideas. But certainly not his "right hand man" and no more his "successor" than anyone else who can do PCT - based modeling and research competently.

···

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[From Rick Marken (2005.02.13.1055)]

Brian D'Agostino (2005.02.13.0456)--

Rick Marken (2005.02.13.0030)--

I'm not a leader of PCT.

Yes, and John Paul II not really the Pope

Was there a smoke signal that someone didn't tell me about?

And I have found the PCT model to be the best basis for doing this . If there are ideas out there that are superior to PCT or can improve my work then I'd be glad to hear about them.

Again, the assumption is: another theory either has to be superior to PCT or inferior to it. This precludes at the outset any possibility of a genuine dialogue and exchange.

I used the word "superior" because you had mentioned it in your post. I added the phrase "or can improve my work" to make it clear that it's not a matter of superiority/inferiority.

No, Rick, I don't want to do away with critical discussion on CSGNet.

Great.

If you go back and read the archives (I think the discussion of my work would have been in 1995 or 1996), you will see that I answered _all_ the substantive criticisms that you, Bill and others made of my work. In the end, you either conceded on the individual points or simply stopped responding.

So what's the problem?

I should mention that some individual members of CSG found my work worthwhile, but you and Bill signaled unambiguously to the community that this work was not worthy of the group's attention, and it was thereafter excluded from CSG's agenda. That is not "critical discussion," it is authoritarian social behavior.

I don't know if you've noticed but what Bill or I "signal" has virtually no impact on what the "CSG community" thinks. There was a huge uproar over Bill's "signals" regarding the nature of coercion and our "signals" regarding the "universal error curve" and the "I see you have chosen" statement, and so on. Authoritarian social behavior should be made of sterner stuff.

Richard S. Marken
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Cell 310 729-1400

From [Marc Abrams 92005.02.13.1339)]

In a message dated 2/13/2005 1:13:48 P.M. Eastern Standard Time, marken@MINDREADINGS.COM writes:

[From Rick Marken (2005.02.13.1015)]

Marc Abrams (2004.02.13.1239)–

You often referred to yourself as some ancient Greek companion to a
god, which I cannot recall the specific name of, because of my lack of
knowledge about the classics, but the implications were clear.

Then you should have no trouble finding several examples (“often” is
more than once).
Yes, as a matter of fact I remember it occurring on at least two separate occasions. I’ll get the cites for you.

I think I might have once compared my relationship to Bill to T.H.
Huxley’s relationship to Darwin. But that was just for fun.
How would anyone know this? You are both prideful and boastful that you and Powers are the only ones, who truly understand PCT.

And in fact you may be absolutely correct in this assumption because it seems we are all having a bit of trouble defining, exactly what PCT represents. Is it MOL? Is it the hierarchy in B:CP? How about the dual hierarchies in the ‘lost’ chapter of B:BP in Living Control Systems?

Is Bill ready, after 35 years, to designate the ‘levels’ as he has seen them to be? If not, why should I believe they exist? By what body of evidence?

I do consider myself an ardent advocate of Bill’s ideas.
Yes, with the key word here being advocate. You don’t question, nor do you inquire. You are the ‘sponge’ Bill likes to have around. That is someone, who just ‘soaks’ up whatever it is he has to say and takes it to the bank. You are uncritical of him and always seem to defer to him. You also act as his unofficial ‘front man’. That is, you often will try to discredit someone who Bill Powers does not have the stomach for. Bill Williams was a great example of this. Powers blocked his posts and you just kept on plugging. You are a bulldog, but your fallacious arguments will no longer go unchallenged as long as I’m on line, but don’t let that deter you. I’ll be leaving when I stop talking with folks

But certainly not his “right hand man” and no more his “successor” than anyone else who can do PCT - based modeling and research competently.
And exactly who might that be?

regards,

Marc

From [Marc Abrams (2005.02.13.1424)]

In a message dated 2/13/2005 2:19:43 P.M. Eastern Standard Time, bryanth@SOLTEC.NET writes:

[From Bryan Thalhammer (2005.02.13.1420)]
I’m afraid you and Brian do not know what an Ad hominem attack is.

It is NOT an insult.

It is when you deflect the argument and make in into a personal attack. I was explaining WHY I felt, that is giving evidence, that Rick, is Bill’s right hand man, and the REASONS I felt that way.

I no sooner send my quote of your pledge not to post ad hominems, and here you
go again. Will you be leaving…? I am merely quoting you… Are you a mensch?

–B.

···

[Marc Abrams 92005.02.13.1339)]
[Rick Marken (2005.02.13.1015)]
…You are the ‘sponge’ Bill likes to have around. That is someone,
who just ‘soaks’ up whatever it is he has to say and takes it to the bank.
You
are uncritical of him and always seem to defer to him. You also act as his
unofficial ‘front man’. That is, you often will try to discredit someone who
Bill Powers does not have the stomach for. Bill Williams was a great
example
of this. Powers blocked his posts and you just kept on plugging. You are a
bulldog, but your fallacious arguments will no longer go unchallenged as
long as
I’m on line, but don’t let that deter you. I’ll be leaving when I stop
talking with folks

regards,

Marc


This message was sent using IMP, the Internet Messaging Program.

[From Rick Marken (2005.02.13.1140)]

Marc Abrams 92005.02.13.1339)--

Rick Marken (2005.02.13.1015)

I do consider myself an ardent advocate of Bill's ideas.

Yes, with the key word here being _advocate_. You don't question, nor do you inquire. You are the 'sponge' Bill likes to have around... You are uncritical of him and always seem to defer to him.

I never realized that all the experiments I did were advocacy pieces. Lucky they came out supporting PCT, I guess.

···

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