"powers 1973" - new results

[rsmarken]

[From Rick Marken (2017.11.30.1930)]

Erling Jorgensen (2017.11.30 0735 EST)
>RM [Responding to Martin Taylor]: But your rephrasing of the issue as "controlling to avoid a particular reference value for the controlled perception as opposed to "controlling to approach a particular reference value for the controlled perception" shows that I did not understand what the "issue" was at all. Indeed, your framing of the issue in this way makes it difficult for me to respond in any way other than to say that this issue has nothing to do with PCT. "Controlling to avoid a particular reference value for a controlled perception" is not "control of avoidance" because it's not control.Â
EJ:Â Gosh, Rick, these pronouncements of yours are difficult to take.Â

RM: I'm sorry to hear that. I'm really just saying these "pronouncements" based on my understanding of PCT. Maybe you, like everyone else on CSGNet, understands PCT better than I do. It doesn't seem like it to me but that's just my opinion and I am definitely in the minority here.
Â

EJ: The Crowd demo has a form of collision avoidance built into it, although I forget just now how it is implemented.Â

RM: It's implemented as control of proximity to other agents. Each agent acts so as to maintain a particular reference value of proximity relative to the other agents. It is not implemented as "controlling to avoid a particular reference value for a controlled perception" because that statement implies that each agent acts to move the controlled perception -- proximity - away from the reference value, which is obviously not control.Â

EJ: Ship captains learn that if the angle of displacement (is that the correct term?) of an orthogonal moving ship is not changing, then they either veer away or slow down to pass behind the other ship. Air traffic controllers try to keep approaching aircraft X-distance apart, and/or at different elevations. There are any number of ways to implement avoidance, whether by controlling distances or displacement angles or one's own velocity. I cannot see that this has "nothing to do with PCT."Â

RM: I think it has everything to do with PCT. The captain and the air traffic controller are acting to control a perception of the relationship between one moving object and another. They are not "controlling to avoid a the reference value for that relationship perception" ; they are controlling for keeping that relationship at the reference value.Â
RM: Perhaps my answer to Martin's statement about what he thought was the "issue" was too terse so I'll try to give a more complete reply.Â
RM: "Avoidance" and "approach" are words used to describe certain behaviors, like those of the ship captain and the air traffic controller. Martin gave a long list of behaviors that could be described as "avoidance" behaviors. As you may or may not know, PCT explains behavior as the control of perception. So the explanation of all these "avoidance" behaviors is the same as the explanation of all behavior -- "approach" behavior, "interception" behavior, "classy" behavior, "violent" behavior, etc. Indeed, the central focus of research based on PCT is aimed at discovering the perceptual variables that are under control when we see an organism behaving in a particular way. But such investigations have to start with a guess about the perceptual variable(s) being controlled. So I will try to demonstrate what I mean by guessing at the perceptual variables that might be under control in some of Martin's examples of "avoidance" behavior. Martin's examples are preceded by a "•¢ ":

•Â Â avoiding bumping into anyone in a crowd:

RM: A higher level system controls a perception of "bumping" at a reference of zero. This system keeps the bumping perception at zero by setting a reference for a lower level system controlling distance to other agents at some non-zero value: CVs = bumping, distance
Â

•Â    avoiding falling into the old mineshaft in the field.

RM: A higher level system controls a perception of falling into holes in the ground at a reference of zero. This system keeps from falling into holes by setting a reference for a lower level system controlling distance to holes in the ground at some non-zero value: CVs = falling in holes, distance
Â

•Â Â avoiding falling over the balustrade on the sevventh floor balcony.

RM: A higher level system controls a perception of falling over edges at a reference of zero. This system keeps from falling over edges by setting a reference for a lower level system controlling center of gravity at "over one's feet": CVs = falling, center of gravity
Â

•Â Â avoiding seeing the wine glass too near the edge of the table.

RM: A higher level system controls a perception of glasses falling off tables at a reference of zero. This system keeps the glass from falling by setting a reference for a lower level system controlling the distance from the glass to edge at about 5 inches: CVs = falling, distance.
Â

•Â Â avoiding hearing fooreigners talking their disgusting language in the bus.

RM: A higher level system controls a perception of hearing the sounds of foreigners talking at a reference of zero. This system keeps the sound from the foreigners from being heard by setting a reference for a lower level system controlling the distance to foreigners at a distance that keeps the sounds level from the foreigners near zero: CVs = sound level, distance.

•  avoiding offending that person with whose policies I disagree.

RM: A higher level system controls a perception of offensiveness of talk with this person at a reference of zero. This system keeps the talk inoffensive by setting a reference for a lower level system controlling the conversational topic to "the weather" (CV = offensiveness, topic of conversation)
RM: I think that's enough to give an idea of how PCT might explain behavior that we see as "avoidance". Of course, to really explain it you have to do the research to see what perceptual variables people are actually controlling when you see them doing these things.Â
RM: By the way, to see how PCT explains an example of "approach" behavior in terms of controlled perceptions I recommend a paper called "Chasin' Choppers" (<https://www.dropbox.com/s/eymkj4bxuorpyuy/Chasin'Choppers.pdf?dl=0&gt;https://www.dropbox.com/s/eymkj4bxuorpyuy/Chasin'Choppers.pdf?dl=0\) which contains a nice test of some control models of approaching toy helicopters. It would be pretty easy to turn these into models what "avoid" helicopters by changing the references for the variables controlled when "approaching" the helicopters.Â
BestÂ
Rick

···

--
Richard S. MarkenÂ
"Perfection is achieved not when you have nothing more to add, but when you
have nothing left to take away.�
                --Antoine de Saint-Exupery

[rupert]

[From Rupert Young (2017.12.01 11.10)]

(Rick Marken (2017.11.30.1930)]

Yes, these are just descriptions from an external observer's point

of view, but it is control of proximity which is actually
implemented for both, it’s just the reference which changes, or
stays the same and the environment changes. When Theresa wants to
talk to Donald she controls her proximity such that she moves within
earshot (“approach” behaviour), but if Donald gets too close,
perhaps by trying to grab something of hers, she continues to
control proximity with the same reference value and moves back
(“avoidance” behaviour).

I'd highly recommend actually modelling these theories of

“behaviour” as PCT systems, as it would save a lot of fruitless
discussion.

These robots, for example, that display "avoidance", which are

controlling proximity https://youtu.be/zS46Vi2qC3s

Regards,

Rupert

···

Erling Jorgensen (2017.11.30 0735 EST)

                  EJ: The Crowd demo

has a form of collision avoidance built into it,
although I forget just now how it is implemented.

            RM: It's implemented as control of

proximity to other agents. Each agent acts so as to
maintain a particular reference value of proximity
relative to the other agents.

            RM: "Avoidance" and "approach" are words

used to describe certain behaviors,

[wmansell]

Thanks for the clarity Rupert!

···

Erling Jorgensen (2017.11.30 0735 EST)

                  EJ: The Crowd demo

has a form of collision avoidance built into it,
although I forget just now how it is implemented.

            RM: It's implemented as control of

proximity to other agents. Each agent acts so as to
maintain a particular reference value of proximity
relative to the other agents.

            RM: "Avoidance" and "approach" are words

used to describe certain behaviors,

[MartinT]

[Martin Taylor 2017.12.01.12.01]

Yep. That's what Bill did and as I described it.

For the rest of the examples, you describe controlling for

correcting a situation that was not avoided (as did Jeff and I). You
don’t address the issue at all. (nor did I, but I have now, in
[Martin Taylor 2017.11.30.09.57]).

The issue is more generally described, perhaps, by not using the

word “avoid” at all. It is to control one’s perceptions of the
sources of possible disturbances to a controlled perception P in
such a way that those particular disturbances to P will not occur.

Martin

···

[From Rick Marken (2017.11.30.1930)]

Erling Jorgensen (2017.11.30 0735 EST)

…

                  EJ: Ship captains

learn that if the angle of displacement (is that
the correct term?) of an orthogonal moving ship is
not changing, then they either veer away or slow
down to pass behind the other ship. Air traffic
controllers try to keep approaching aircraft
X-distance apart, and/or at different elevations.Â
There are any number of ways to implement
avoidance, whether by controlling distances or
displacement angles or one’s own velocity. I
cannot see that this has "nothing to do with
PCT."Â

          RM: I think it has everything to do with PCT. The

captain and the air traffic controller are acting to
control a perception of the relationship between one
moving object and another. They are not “controlling
to avoid a the reference value for that relationship
perception” ; they are controlling for keeping that
relationship at the reference value.Â

            RM: Perhaps my answer to Martin's

statement about what he thought was the “issue” was too
terse so I’ll try to give a more complete reply.Â

            RM: "Avoidance" and "approach" are words

used to describe certain behaviors, like those of the
ship captain and the air traffic controller. Martin gave
a long list of behaviors that could be described as
“avoidance” behaviors. As you may or may not know, PCT
explains behavior as the control of perception. So the
explanation of all these “avoidance” behaviors is the
same as the explanation of all behavior – “approach”
behavior, “interception” behavior, “classy” behavior,
“violent” behavior, etc. Indeed, the central focus of
research based on PCT is aimed at discovering the
perceptual variables that are under control when we see
an organism behaving in a particular way. But such
investigations have to start with a guess about the
perceptual variable(s) being controlled. So I will try
to demonstrate what I mean by guessing at the perceptual
variables that might be under control in some of
Martin’s examples of “avoidance” behavior. Martin’s
examples are preceded by a "• ":

            •¢Â 

 avoiding bumping into anyone in a crowd:

          RM: A higher level system controls a perception of

“bumping” at a reference of zero. This system keeps the
bumping perception at zero by setting a reference for a
lower level system controlling distance to other agents at
some non-zero value: CVs = bumping, distance

[rsmarken]

[From Rick Marken (2017.12.01.1055)]

···

Rupert Young (2017.12.01 11.10)

RY: Yes, these are just descriptions from an external observer's point

of view, but it is control of proximity which is actually
implemented for both, it’s just the reference which changes, or
stays the same and the environment changes…

Â

RY: I'd highly recommend actually modelling these theories of

“behaviour” as PCT systems, as it would save a lot of fruitless
discussion.

RM: Absolutely. And by “modeling” I presume you mean building what Bill called “working” models, either as robots or computer programs (like CROWD). But if one’s goal is to understand the behavior of living organisms, I would also recommend comparing the behavior of these working models to that of real organisms. This is something that has been sorely lacking in these discussions. It’s important an important component of model testing because there are many ways to build working models that can successfully imitate certain behaviors but don’t actually produce those behaviors the way organisms do.Â

BestÂ

Rick

These robots, for example, that display "avoidance", which are

controlling proximity https://youtu.be/zS46Vi2qC3s

–
Richard S. MarkenÂ

"Perfection is achieved not when you have nothing more to add, but when you
have nothing left to take away.�
                --Antoine de Saint-Exupery

            RM: "Avoidance" and "approach" are words

used to describe certain behaviors,

[MartinT]

[Martin Taylor 2017.12.01.16.46]

[From Rick Marken (2017.12.01.1055)]

Agreed in principle. But making the models isn't as easy as

describing them. Even for something that seems as simple on the
surface as the power law relation between curvature and along-curve
velocity, nobody yet has even sought the controlled variable, either
by simulation of various possibilities or by using the TCV. And you
really can’t have a PCT model for a particular situation without
having a controlled variable. How much more difficult is it to
provide a working model for constructs that theory says can emerge
only when a minimum number of components work together and those
theoretical components are control systems?

Very true. Finding out how organism produce those behaviours is

indeed the problem, especially when you have many differently
structured working models that produce the same results, so far as
any external observer can tell. When I was working in colouring
remote sensing imagery, the term was “ground truth”. You can see
differences in the imagery, but you don’t know what they mean until
you get quite independent ways of looking at what ought to be the
same thing. Without the analogue of ground truth, how do you tell
whether your favourite model is the one and only model that produces
those behaviours the way organisms do. Maybe none of them do,
including one’s own.

The resolution to his, I think, is to give equal precedence to as

many different ways of looking at the problem as you can implement.
In physics, theory and modelling and experiment all go hand in hand.
For Astronomy, experiment isn’t possible, so theory and modelling
work as a unit. Experiments, where they are available, provide data,
but that’s not useful without theory and modelling. When they all
fit together around one concept, it’s not unreasonable to suppose
that there could be some truth in all of them.

Of course, you never know when your nicely argued, modelled, and

compared with living organisms concept may have to be totally
rejigged for reasons now completely unknown. Unless you are an
omniscient being that does know the “ground truth”.

Martin

···

Rupert Young (2017.12.01 11.10)

…

            RY: I'd highly

recommend actually modelling these theories of
“behaviour” as PCT systems, as it would save a lot of
fruitless discussion.

          RM: Absolutely. And by "modeling" I presume you mean

building what Bill called “working” models, either as
robots or computer programs (like CROWD). But if one’s
goal is to understand the behavior of living organisms, I
would also recommend comparing the behavior of these
working models to that of real organisms. This is
something that has been sorely lacking in these
discussions.

          It's important an important component of model testing

because there are many ways to build working models that
can successfully imitate certain behaviors but don’t
actually produce those behaviors the way organisms do.

[rsmarken]

[From Rick Marken (2017.12.01.1850)]

Martin Taylor (2017.12.01.16.46)–

···

MT: Agreed in principle. But making the models isn't as easy as

describing them. Even for something that seems as simple on the
surface as the power law relation between curvature and along-curve
velocity, nobody yet has even sought the controlled variable, either
by simulation of various possibilities or by using the TCV. And you
really can’t have a PCT model for a particular situation without
having a controlled variable. How much more difficult is it to
provide a working model for constructs that theory says can emerge
only when a minimum number of components work together and those
theoretical components are control systems?

RM: You certainly can’t have a PCT model of behavior unless you have some idea about the controlled variable(s) involved. That’s because research on living control systems always starts with observations (phenomena first!) and the observations that lead one to develop a PCT model of behavior are ones that suggest that the behavior involves control. Nobody had ever sought the controlled variable that is involved in the power law relationship observed for curved movement because power law researchers had no idea that the production of these movements involved control. They saw curved movements as generated outputs and they thought of the power law as a consequence of kinematic and physiological constraints on the way these movements were generated. If they had observed that curved movements are a consistent result produced in the face of varying disturbances by appropriately varying means then they would have realized that the curved movements produced by living organisms are controlled results. And their research would then have taken a vary different course; the research would have been aimed a determining the variable aspects of these movements that are controlled and, with that knowledge, they would have been able to develop models of curved movements as the control of these variables: PCT models.Â

MT: The resolution to this, I think, is to give equal precedence to as

many different ways of looking at the problem as you can implement.
In physics, theory and modelling and experiment all go hand in hand.
For Astronomy, experiment isn’t possible, so theory and modelling
work as a unit. Experiments, where they are available, provide data,
but that’s not useful without theory and modelling. When they all
fit together around one concept, it’s not unreasonable to suppose
that there could be some truth in all of them.

RM: The sine qua none of science is observation! You can’t do experiments in astronomy but you can sure make observations. Without observation, modeling and theorizing are just mental masturbation; a lot of fun to do, perhaps, but it gets you nowhere in terms of understanding behavior.Â

MT: Of course, you never know when your nicely argued, modelled, and

compared with living organisms concept may have to be totally
rejigged for reasons now completely unknown. Unless you are an
omniscient being that does know the “ground truth”.

RM: And the reason models have to change is because of observations that pose a problem for existing models. PCT wasn’t developed to replace the Input-Output (IO) model of behavior because it’s such a nice model. PCT was developed because Powers made an observation that couldn’t be accounted for by any version of the IO model (one version being the Gibsonian models used in power law research); Powers observed that what we call behaviors involve the production of consistent results in a disturbance prone environment by variable means that precisely compensate for the effects of these disturbances. That is, he observed that behavior is control, a fact that cannot be explained by any IO model. It can only be explained by a control model – a model that acts to control its own perceptual input.Â

          RM: Absolutely. And by "modeling" I presume you mean

building what Bill called “working” models, either as
robots or computer programs (like CROWD). But if one’s
goal is to understand the behavior of living organisms, I
would also recommend comparing the behavior of these
working models to that of real organisms. This is
something that has been sorely lacking in these
discussions.

          RM: It's important an important component of model testing

because there are many ways to build working models that
can successfully imitate certain behaviors but don’t
actually produce those behaviors the way organisms do.Â

Best

Rick

Richard S. MarkenÂ

"Perfection is achieved not when you have nothing more to add, but when you
have nothing left to take away.�
                --Antoine de Saint-Exupery

[_Boris_Hartman]

Down …

···

From: Richard Marken [mailto:rsmarken@gmail.com]
Sent: Friday, November 24, 2017 7:17 PM
To: csgnet@lists.illinois.edu
Subject: Re: “powers 1973” - new results

[From Rick Marken (2017.11.24.1005)]

On Thu, Nov 16, 2017 at 7:59 AM, Warren Mansell wmansell@gmail.com wrote:

WM: I am circulating a neat new study by Jeff that starts to address Charles Carver’s messing about with ‘control theory’…

RM: I’m sure Jeff’s paper is an improvement over whatever Carver has come up with.

HB : it seems that you are well acquanted with Carvers work for such a conclussion. Well I would agree with you some 5-6 years ago when I was mediating between Bill and Carver. But Carvers’ last articles show improvement which I don’t see in Jeff’s articles.

RM : But there are several problems with Jeff’s paper – at least from my perspective as one who barely understands PCT so this can be taken as merely the rantings of a crotchety old man – that make it less than stellar (in my eyes) as an example of a PCT model of control. The problems are: 1) The paper makes a distinction between avoidance and approach goals but there is no such distinction in PCT, where there are just goals (reference states for controlled variables). 2). There is no “choice” function in PCT (see Figure 3 in Jeff’s paper) that chooses between pursuing an approach versus an avoidance goal and 3) The age of a predator’s tracks can’t be a controlled variable (as it is in the single loop example) since the organism can’t control that variable; the organisms can only control it’s distance from the tracks depending on their age.

HB : I’ll not analyse this because I didn’ read enough article but I could agree in some points. What you let out as biggest mistake in Vancouver at all article is their diagram. It’s disaster.

HB : The questions are :

1.   Where did Vancouver and others get information that this is »generic« diagram ? I can't find it  in their article ? And how does it resemble to PCT diagram ?
   

2.   How did they get idea that there is one »variable« somewhere in the space and time outside organism and make it as general theory or as they say »formalization« of model of goal regulation ? So it seems that people are continuously acting on environment 24 hours a day to achieve some wanted state in »outer environment« ?
   

3.   Diagram is equiped with »input« and »output«, but in text Vancouver at all are talking about »input function« and »ouptut function« what is clearly stolen from PCT diagram without mentioning that. I'm not surprised that Mary Powers didn't like Vancouver as it was obviously that he was stilling informations from Bills' work. I warned Jeff about this theft but he is acting like nothing has happened. Maybe Powers ladies should do something to protect Bills and Marys work. The only author in history of Cybernetics that i know who used »input function« and »output function« was Bill Powers. And he also confirmed taht he was the frist to introduce Cyberentics to Psychology. So where did Vancouvers generic diagram came from ? Bills' dirgam has special meaning. It's showing »Control of Perception« as any other dirgam don't. Maybe Vancouver will prove that I'm wrong. Carver couldn't. So whatever Vancouver was writing about he should use Bill as reference when using his terms. Diagrma anyway doens't look like Powers.
   

Vancouver at all : An avoidance goal is an undesired state from which person seeks to distance themselves

HB : Well it seems very strange formulation. Undesired state where ? If Vancouver ment state inside organism than no »avoidance goal« is created to distance oneself from undesired state. It’s simply that »error« is eliminated (which probbaly shows undesired state) as PCT diagram shows. It’s normal feedback control. There is no special »avoindance goal« created which could distance us from undesired state. Undesired state is simply a result of matching perception to reference with probably significant error which is probably felt as undesired state.

Vancouver at all : Avoidance goal regulation involves acting to distance oneself from something undesired; whereas approach goal regulation involves acting to obtain something desired.

HB : It seems to me that Vancouver is talking about goals outside organism. There is no such thing in PCT. Perception can’t avoid reference (goal) or approach to it. So we are not acting toward some goals in environment to obtain something desired or »runaway« from soething undesired. It’s seems to me more as confussion. I must admitt that I hardly read such texts as Vancouvers’ is. So it could be that I misssed something about his article.

Goals (references) are not outside the control system. So in this sense we can’t approach to goals or avoid them. Behavior is always consequence of matching perceptual signal to reference (goals) which tends to stabilize (keep constant) internal environment of organism. That’s necessary for survival. That’s what definitions of control in PCT tells us.

So by my oppinion there can be no »approach« or »avoidance« goals in the sense that they are outside. It’s always a »trial« of eliminating errors in hierarchy of goals whether you »fight«, »flight« or »freeze« or you go into meditation… So I don’t see anyy point in emphasizing »avoidance« to goals and »approach« to goals. How can perception avoid reference or approach to it ? Whether reference for the perception are set or they are not set. Well it’s possible that we »avoid« perceptions to meet references where we expect »error« to occur. Or that we imagine »error« if some perceptions are controlled. I think that Bruce Abbott gave satisfying explanations.

BA : Where the intensity of a stimulus is being controlled, a standard PCT-style control system could have a reference of either zero intensity or of some low, threshold intensity below which no further action would be taken. Any source of stimulation above this level would produce actions that reduce the perceived intensity, such as increasing the distance. An animal behaving like this might be described as being “photophobicâ€? (fearing the light), but could just as well be described as preferring the darkness.

In the case of the bear, a common view is that the bear arouses fear, and that fear decreases as distance from the bear increases. The person who moves away from the bear is probably not controlling for being at a fixed distance from the bear but rather, for a low level of fear (alternatively, a low perceived probability of being seen/attacked by the bear.) Moving away from the source is the means by which fear is brought toward this reference level; it may not matter in which direction one moves so long as the distance from the bear increases.

Technically speaking, it is more accurate to describe these situations as involving escape rather than avoidance. Escape involves being exposed to the stimulation and removing/reducing that exposure; avoidance involves preventing that exposure in the first place. Both may be involved. In the case of the bear, by moving to a “safeâ€? distance we escape from intense fear but in so doing avoid being mauled by the bear. And we fear the bear because we have learned that bears can and sometimes do maul and kill humans.

HB : I also think that problem is about “errorsâ€? in hierarchy and how they are eliminated. We can “avoidâ€? bear, we can “runwayâ€?, we can “approachâ€?, we can “make a trapâ€?, we can “shootâ€? a bear… All in accordance with “errorsâ€? in organism and the way we choose to eliminate them.

RM: So once again my lack of understanding of PCT (as it is understood on CSGNet anyway) combined with my inability to do mathematics lead me to give the work of a friend of PCT a poor grade. You may all now feel free to set me straight.

HB: Your lack of understanding PCT is well defined. I can prove it any time with CSGnet archives. The problem is that you are not doing anything to change you lack of PCT understanding or you don’t want to switch from RCT to PCT. O.K. there are bright moments.

Boris

Best

Rick

Warren

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Date: Thu, Nov 16, 2017 at 5:55 AM
Subject: “powers 1973” - new results
To: wmansell@gmail.com

The dynamics of avoidance goal regulation

T Ballard, G Yeo, JB Vancouver, A Neal - Motivation and Emotion

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Richard S. Marken

"Perfection is achieved not when you have nothing more to add, but when you
have nothing left to take away.�
–Antoine de Saint-Exupery

[_Boris_Hartman]

Martin

···

From: Martin Taylor [mailto:mmt-csg@mmtaylor.net]
Sent: Thursday, November 30, 2017 5:20 AM
To: csgnet@lists.illinois.edu
Subject: Re: “powers 1973” - new results

[Martin Taylor 2017.11.29.23.17]

[From Rick Marken (2017.11.29.1715)]

Martin Taylor (2017.11.28.23.40)

MT: I should have asked why you referred to approach-avoidance conflict, when the issue was about how control of avoidance is performed.

RM: Because I thought we were talking about Jeff’s model of conflict. And I don’t know what “control of avoidance” would be. We control variables. If so, how do you measure the variable “avoidance”?

MT: It would be more suitable for you to address what you know to be the issue rather than to quibble about my use of a common short form. “Control of avoidance” as opposed to “control of approach” is the issue, or if you prefer, "controlling to avoid a particular reference value for the controlled perception as opposed to “controlling to approach a particular reference value for the controlled perception”. Personally, I prefer to use the form I did use, and will continue to do so, knowing that you understand very well exactly what I mean by it.

RM: …your rephrasing of the issue as "controlling to avoid a particular reference value for the controlled perception as opposed to “controlling to approach a particular reference value for the controlled perception” shows that I did not understand what the “issue” was at all. Indeed, your framing of the issue in this way makes it difficult for me to respond in any way other than to say that this issue has nothing to do with PCT. “Controlling to avoid a particular reference value for a controlled perception” is not “control of avoidance” because it’s not control.

HB : Well odd PCT language. What is particular reference value for a controlled perception ??? What is »controlled perception« ?

But if you are talking about perceptual signal which can not avoid their reference then i agree with you.

MT : Why is it not control? And is not PCT supposed to be a theory about how people function?

HB : Right. PCT is about how Living organism function. And they function in the manner of »Control of perception«. Perceptions meet references.

MT : Are you saying that people do not try to avoid situations,

HB : I would say that people try to control perception of situations so that what is perceived is matched to references in hierarchy and when discrepancy occurs they try to eliminate discrepancy. Perceptual signal can’t avoid reference.

Maybe people try to avoid perceiving some situations where significant »error« can occur ?

MT : …or that PCT doesn’t addrress that aspect of how people function? You must be saying one or the other. Which is it?

HB : I think Martin that this time Rick is saying that »CONTROLLED PERCEPTION« is matched to references so that we can talk about control in PCT. The only problem is what is matched to references is not »controlled perception«.

Boris

Martin

[_Boris_Hartman]

Sorry Rupert to jump in…

···

From: Richard Marken [mailto:rsmarken@gmail.com]
Sent: Friday, December 01, 2017 7:56 PM
To: csgnet@lists.illinois.edu
Subject: Re: “powers 1973” - new results

[From Rick Marken (2017.12.01.1055)]

Rupert Young (2017.12.01 11.10)

RM: “Avoidance” and “approach” are words used to describe certain behaviors,

RY: Yes, these are just descriptions from an external observer’s point of view, but it is control of proximity which is actually implemented for both, it’s just the reference which changes, or stays the same and the environment changes…

RY: I’d highly recommend actually modelling these theories of “behaviour” as PCT systems, as it would save a lot of fruitless discussion.

RM: Absolutely. And by “modeling” I presume you mean building what Bill called “working” models, either as robots or computer programs (like CROWD). But if one’s goal is to understand the behavior of living organisms, I would also recommend comparing the behavior of these working models to that of real organisms. This is something that has been sorely lacking in these discussions.

HB : Mostly because of you, who were always on the side of demos and simluations. I’ve been telling you for years that nature is the final arbiter.

It’s important an important component of model testing because there are many ways to build working models that can successfully imitate certain behaviors but don’t actually produce those behaviors the way organisms do.

HB : Maybe you finally got the point of what PCT is.

Best

Rick

These robots, for example, that display “avoidance”, which are controlling proximity https://youtu.be/zS46Vi2qC3s

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Richard S. Marken

"Perfection is achieved not when you have nothing more to add, but when you
have nothing left to take away.�
–Antoine de Saint-Exupery