What is Qi?

[From Fred Nickols (2017.09.03.1537 ET)]

Angus:

After re-reading your original post, I doubt my example is what you were looking for. Indeed, it’s not clear to me what you’re looking for. Your last sentence reads:

AJ: What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

What is the “nonbiological, non-human-designed, material world�? I don’t have a clue as to what that is.

Fred Nickols

···

From: Angus Jenkinson [mailto:angus@angusjenkinson.com]
Sent: Friday, September 1, 2017 11:50 AM
To: csgnet@lists.illinois.edu
Subject: Re: What is Qi?

[From Angus Jenkinson. 2017.9.1].

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological space).

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

………………… ¦â€¦â€¦â€¦â€¦…………………………………………….

Angus Jenkinson

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

[From Bruce Abbott (2017.02.12.1820 EST)]

[Vyv Huddy 1955.12.02.2017]

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature up.

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on a slippery surfaces and drivers are encouraged not to use them then.

BA: One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity with a single environmental variable (without some sort of bio engineering).

BA: Why not? Optic flow will do it.

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise control an intensity controller.

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Bruce

I missed the double negative too. Are you talking about naturally occuring control systems in the mineral kingdom?Â

···

On Sun, Sep 3, 2017 at 3:40 PM, Fred Nickols fred@nickols.us wrote:

[From Fred Nickols (2017.09.03.1537 ET)]

Â

Angus:

Â

After re-reading your original post, I doubt my example is what you were looking for. Indeed, it’s not clear to me what you’re looking for. Your last sentence reads:

Â

AJ: What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

Â

What is the “nonbiological, non-human-designed, material world�? I don’t have a clue as to what that is.

Â

Fred Nickols

Â

From: Angus Jenkinson [mailto:angus@angusjenkinson.com]
Sent: Friday, September 1, 2017 11:50 AM
To: csgnet@lists.illinois.edu
Subject: Re: What is Qi?

Â

[From Angus Jenkinson. 2017.9.1].

Â

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

Â

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological space).

Â

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

Â

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

Â

………………………………………… ¦â€¦â€¦â€¦â€¦……………….

Angus Jenkinson

Â

Â

Â

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

Â

[From Bruce Abbott (2017.02.12.1820 EST)]

Â

[Vyv Huddy 1955.12.02.2017]

Â

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.Â

Â

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

Â

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature up.

Â

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

Â

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on a slippery surfaces and drivers are encouraged not to use them then.

Â

BA:  One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

Â

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity with a single environmental variable (without some sort of bio engineering).

Â

BA: Why not? Optic flow will do it.

Â

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.Â

Â

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

Â

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.Â

Â

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise control an intensity controller.

Â

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Â

 Bruce

[From
Angus Jenkinson. 2017.9.1].

Â

        I

came across this recently. In it there is the remark by BA

        BA:

I don’t see any essential difference between
human-engineered control systems and biological ones; in
fact it is that correspondence that allowed Bill Powers (and
others) to apply control-system principles to biological
systems. What is true is that biological systems are
products of evolution, a process that involves gradual
modification of what is already there. Unlike a human
designer, evolution does not begin with a fresh sheet of
paper. What results is more like a hodge-podge of
alterations and fixes than a clean design, and this can make
it extremely difficult to tease out what the parts of a
given system are and how they interconnect. Bill Powers
notes, for example, that alpha motor neurons in the spinal
cord combine the functions of comparator and output function
(and even that is probably an oversimplification). So it
may be more difficult to figure out the system diagrams in
biological systems than in human-engineered systems, but
that does not imply that the underlying system principles of
the two are necessarily different. PCT is based on the
well-supported assumption that behavior can be explained by
control-system models.

Â

        I

take a rather different view, and it is important for my
research. Leaving aside the questionable comments about the
process of evolution (but bearing in mind Einstein’s comment
that anything seems complex/complicated until it is
understood), my concern is with the assumption of identity
between biological systems and mechanical systems (leaving
aside human engineering in the genetic/biological space).

···

………………………………………………………………………….

Angus Jenkinson

Â

Â

Â

          On 12/02/2017, 23:19, "Bruce Abbott"

<bbabbott@frontier.com >
wrote:

Â

[From Bruce Abbott (2017.02.12.1820 EST)]

Â

[Vyv Huddy 1955.12.02.2017]

Â

        VH: This is great set of posts on this

thread and the previous one. Particularly helpful to see the
posts by rick and bruce describing the figure in the Powers
Science paper showing multiple V. I noticed that and missed
why it was important.Â

Â

        VH: I don't have my books with me now but

i recall Bill Powers (i think) wrote somewhere that the
controlled variable of a thermostat is actually the amount
of coil of the strip not the temperature of the room itself.
This is partly shown by putting a flame directly under the
thermostat - the furnace goes off without the room
temperature changing.

Â

        BA: The controlled variable is the

temperature of the air. The position of the coil (actually,
the contact on the free end of the coil) is the thermostat’s
perception of that temperature. Â The position of the other
contact sets the thermostat’s reference level. When the
contacts meet, this generates a nonzero error signal
indicating that the room temperature has fallen below the
reference level. This causes the furnace to switch on
(output function), heating the air and thus bringing the
room temperature up.

Â

        BA: The thermostat is a sensor of room

temperature only to the extent that the coil temperature
matches the room temperature. Â All sensors work this way,
sensing a variable through its effect on the sensor. Â In
this example changing temperatures of the air are conveyed
to the coil, producing different expansions on the two sides
of the bimetallic strip, thus moving the contact on the free
end. In the case of vision, photons striking molecules of
photochemical in the photoreceptors cause light-sensitive
chemicals within the photoreceptors to break down, which
through a series of chemical events causes the “generator
potential� of the photoreceptor to change. This in turn
alters the rate of firing of associated neurons.

Â

        VH: If so the controlled variable (qi) of

a cruise control would be the frequency of the counting
wheel turns in the speedometer mechanism? If so from that
perspective there is no “actual” speed; cruise controls
don’t work effectively on a slippery surfaces and drivers
are encouraged not to use them then.

Â

        BA: Â One could design cruise controls to

sense the car’s speed in a variety of ways. The typical
example is that speed is sensed indirectly by counting the
rotational frequency of the car’s drive shaft. Under normal
conditions this is proportional to the speed of the car.Â
This relationship breaks down if the wheels slip, as you
note. This problem could be avoided by using an optical
sensor to read the “optic flow� of the road beneath the car.
 However measured, there is still an actual speed that is
being measured, whether directly or indirectly, so long as
the expected relationships hold. In the absence of wheel
slippage, driveshaft rotations map directly onto the car’s
speed. Â Biological systems experience the same difficulties;
sensor reports do not always match reality. Our sensors
remain useful, however, because most of the time they
provide readings that are good enough to go by.

Â

        VH: As i write this though I'm beginning

to doubt the examples of thermostats or any other man made
control system as clear illustrations of control in living
systems. This is because machines input functions come about
in a totally different way to those of living things. They
can be made to be much simpler; a cruise control can sense
velocity via a single variable because of the way it is
organised (a turning crank and some frequency counter).
There is no way a living system can sense velocity with a
single environmental variable (without some sort of bio
engineering).

Â

BA: Why not? Optic flow will do it.

Â

        VH: I wonder if this difference makes

these examples hard for me understand. I find the two
domains don’t map onto each other that well.Â

Â

        BA: I don’t see any essential difference

between human-engineered control systems and biological
ones; in fact it is that correspondence that allowed Bill
Powers (and others) to apply control-system principles to
biological systems. What is true is that biological systems
are products of evolution, a process that involves gradual
modification of what is already there. Unlike a human
designer, evolution does not begin with a fresh sheet of
paper. What results is more like a hodge-podge of
alterations and fixes than a clean design, and this can make
it extremely difficult to tease out what the parts of a
given system are and how they interconnect. Bill Powers
notes, for example, that alpha motor neurons in the spinal
cord combine the functions of comparator and output function
(and even that is probably an oversimplification). So it
may be more difficult to figure out the system diagrams in
biological systems than in human-engineered systems, but
that does not imply that the underlying system principles of
the two are necessarily different. Â PCT is based on the
well-supported assumption that behavior can be explained by
control-system models.

Â

        VH: If cruise control p is really a

single voltage in wire then it would be only intensity
controller? Â For me Intensity control is best explained in
the context of the muscle tone example, as in b:cp.Â

Â

        BA: In HPCT, perceptual signals at all

levels are equivalent to single voltages in a wire (i.e.,
average neural current in a nerve). Â Thus, the fact that p
in cruise control is embodied as a single voltage in a wire
does not make the cruise control an intensity controller.

Â

In fact, all controllers in HPCT,
at whatever level, are intensity controllers in the sense
that they act to control the intensity of their neural
signal p’s.

Â

 Bruce

[From Angus Jenkinson. 2017.9.23] Apologies for the delay

Bruce, Fred, you ask

What is the “nonbiological, non-human-designed, material worldâ€??Â

I was asking what PCT behaviour there is in this domain.

All the bacteria, flora, vertebrates, non-vertebrates etc are biological. Computers, AI, thermostats, regulators on machines etc are human-designed. Therefore they are biological transposed into machine.

The origin of my question was a conversation about domains in which PCT applies. It seems to me that PCT is a phenomenon of life, or those instruments created as extensions of humans (in particular) that mechanically perform human activity at a distance.

Angus

···

From: Angus Jenkinson [mailto:angus@angusjenkinson.com]
Sent: Friday, September 1, 2017 11:50 AM
To: csgnet@lists.illinois.edu
Subject: Re: What is Qi?

[From Angus Jenkinson. 2017.9.1].

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological space).

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

Angus Jenkinson

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

[From Bruce Abbott (2017.02.12.1820 EST)]

[Vyv Huddy 1955.12.02.2017]

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature up.

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on a slippery surfaces and drivers are encouraged not to use them then.

BA: One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity with a single environmental variable (without some sort of bio engineering).

BA: Why not? Optic flow will do it.

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise control an intensity controller.

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Bruce

[From Angus Jenkinson. 2017.9.23] SORRY FOR THE DELAY

Fred, thank you for the response. As you said after this post, I agree that this is an example of a human-designed system for PCT behaviour. It is interesting, but not a behaviour of inorganic non-human-designed nature. This kind of control system is what the cybernetics folks were designing during the world war II.

···

On 03/09/2017, 20:38, “Fred Nickols” fred@nickols.us wrote:

[From Fred Nickols (2017.09.03.1521 ET)]

Angus:

I might have an example but I’ll let you be the judge of that.

When I joined the Navy in 1955 I was trained as a fire control technician. The “fire� in question was gunfire from the big guns found on warships. I won’t go into the intricacies of solving the fire control problem (namely, figuring out how to hit a moving target) but suffice it to say that the many calculations performed by the computer at the heart of a shipboard gunfire control system resulted in a set of orders to the gun mounts. The orders sent to the gun mounts constituted reference signals (one for horizontal positioning of the gun mount or “gun train order� and one for vertical positioning of the gun barrel or “gun elevation order.�

Servomechanisms and motor generators served to move the gun mount and its barrel and to ascertain (i.e., perceive) its current positions and compare those with the ordered positions. The “disturbances� included the pitch and roll of the ship, friction between the gun mount and the base ring upon which it sat and turned and any sudden, sharp maneuvers being made by the ship.

Is that the kind of example you are seeking?

Fred Nickols

From: Angus Jenkinson [mailto:angus@angusjenkinson.com]
Sent: Friday, September 1, 2017 11:50 AM
To: csgnet@lists.illinois.edu
Subject: Re: What is Qi?

[From Angus Jenkinson. 2017.9.1].

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological space).

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

………€¦â€¦……………………………………………………… ¦â€¦â€¦â€¦â€¦.

Angus Jenkinson

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

[From Bruce Abbott (2017.02.12.1820 EST)]

[Vyv Huddy 1955.12.02.2017]

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature up.

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on a slippery surfaces and drivers are encouraged not to use them then.

BA: One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity with a single environmental variable (without some sort of bio engineering).

BA: Why not? Optic flow will do it.

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise control an intensity controller.

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Bruce

[From Angus Jenkinson. 2017.9.23] SORRY FOR THE DELAY

Bruce, you asked…

[…] biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect.

03/09/2017, 19:57 BN> You suggested that you have reservations about this. Do you disagree, or is something really important missing?

AJ > I t is of course true that there are “gradual modifications�. Evolution and human designers do not begin with fresh sheets of paper. But I do not think that a “hodge podge� is a reasonable description of the extraordinary designs of life.

A further reservation might be assuming something not intended.  This is that the classical (neo-Darwinian) view of evolution requires significant modification. This argument is based in part on several leading positions in the contemporary biology of evolution as I understand them. This provides for a high degree of “cultural evolutionâ€? of life – a phrase of Maturana. He goes so far as to suggest that “loveâ€? is the primary design principle of the last 4 billion years, in so far as evolution is a process of developing co-operative co-evolution. This argument follows from autopoiesis, genetic drift, and the contribution of epigenetic factors in reproduciton. It proposes that learning experience of a life is biologically inheritable in part, a neo-Lamarckian view.

Moreover, as a further reservation, the historic neo-Darwinian view of evolution is classical and draws on randomness, entropy and causality. By contrast, I think it follows from PCT that intentional control is a feature of life at all levels of detail. This means that I think we need to do some more work on the mechanisms of evolution.

Returning to the question of whether the “hodge podge� makes it difficult to tease out what is happening, maybe we are just not very good at knowing what is going on. We are discovering new Philae in the guts of creatures.  We don’t know how many cells there are in a human. We have many unanswered questions not only about how an organism works but about how to even go about understanding how it works: look at our interest in PCT and the general blindness. It is only one of several paradigms that will surely be revisited. How the morphology of the arm is populated by cellular organisation is unknown.

I think that with time we may to come to see the morphology of organisms and their organic deep systemness as rather a wonder. In that direction, if we look at the way morphology and metamorphosis operates in flora, there is a systemic modification in which all the “parts� dynamically respond and flex in relation to each other as part of the adaptation of a plant (species) to its environmental niche(s). the primary form modifies somewhat like how a drawing on a balloon will flex with any distortion of the balloon (that’s no more than a crude analogy).  There was an interesting book by Wilhelm Schad I came across in this direction.

Angus

···

On Fri, Sep 1, 2017 at 11:49 AM, Angus Jenkinson angus@angusjenkinson.com wrote:

[From Angus Jenkinson. 2017.9.1].

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological space).

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

………………………………………… ¦â€¦â€¦â€¦â€¦……………….

Angus Jenkinson

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

[From Bruce Abbott (2017.02.12.1820 EST)]

[Vyv Huddy 1955.12.02.2017]

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature up.

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on a slippery surfaces and drivers are encouraged not to use them then.

BA: One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity with a single environmental variable (without some sort of bio engineering).

BA: Why not? Optic flow will do it.

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise control an intensity controller.

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Bruce

[Angus Jenkinson (2017-09-24.12.14)]

···

AJ> First, I thank you for going to the trouble of an extensive reply to my question.

AJ> Let me respond here to your first answer. I appreciate its contents and follow it. I have represented the line of thought in the following (simplified) terms: observers perceive situations, which are those aspects that attention is
given to within multidimensional descriptive spaces; they only control for the parameters of those descriptive spaces that they perceive, the aspects to which they pay attention; thus the process of forming a ‘situation’ is itself a control activity. In response
to that situation, the observer attempts to control for desired outcomes as desired presents. The self-represented multidimensional descriptive space corresponds in some way to a possible multidimensional actual space, so that controlling for the descriptive
space may or may not deal with all of the parameters (dimensions) of the actual space, as it emerges over time. The actual space/situation is not to be understood as any kind of absolute reality, merely those aspects of reality that might become actualised
over time within the situation, or descriptive space, of the observer.

AJ> I hold in suspense the question of whether this logical description of a multidimensional descriptive space can actually be fully realised in mathematics, at least the mathematics of today. My suspicion is that the logic of the ‘situation’
(of the PCT modeller or the observer in life-being-lived) requires a sufficiency of dimensions and that the process of reducing them all to mathematical form imposes the probability of dimensions becoming actual that have not been introduced into the situation
and controlled for.

AJ> And then you kindly discuss biological and nonbiological systems and introduce the term bionics, which I am familiar with, of course, in both senses. However, what I take out of your reply is in agreement that there is no case of
perceptual control of a variable to bring about a required outcome was setting outside the domains of biology and human created systems. We may be able to create systems that ape biology and who knows exceed it in some dimensions. Have I understood you?

Angus

[Martin Taylor 2017.09.04.12.00]

[From Angus Jenkinson. 2017.9.1].

I came across this recently. In it there is the remark by BA

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence
that allowed Bill Powers (and others) to apply control-system principles to biological systems. What is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer,
evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect.
Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological
systems than in human-engineered systems, but that does not imply that the underlying system principles of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

I take a rather different view, and it is important for my research. Leaving aside the questionable comments about the process
of evolution (but bearing in mind Einstein’s comment that anything seems complex/complicated until it is understood), my concern is with the assumption of identity between biological systems and mechanical systems (leaving aside human engineering in the genetic/biological
space).

I’m not sure how the subject line connects to this concern in your mind, but I will try to answer with the bias that there is a connection.

AJ> Apologies probably due.

First question: What is “questionable” about what BA says about evolution? It seems straightforward and non-controversial to me – but let’s leave that aside, as you say, and concentrate on “* my concern is with
the assumption of identity between biological systems and mechanical systems*”.

Obviously, there are many surface differences. Most biological systems are soft. Most mechanical systems are hard. Some mechanical systems have wheels and gears; no biological systems I know of have either. Some mechanical systems incorporate logic that works
on nanosecond time-scales. No biological systems do. And so forth. The claim is only that functionally, control is identical no matter what the system, biological and evolved, or mechanical and designed, or simulated and evolved. So let’s look at that.

To control anything, which we can call “Z”, means to compare it with what it “should” be, which we can call “R”, and to do something to improve the match. In engineering, Z must be representable by a number or a vector of numbers, and therefore R must be representable
by a vector of the same dimensionality (a number can be treated of a vector of one dimension, otherwise known as a scalar). Is this true of biological control? Yes.

In the nature of control, there must be some means by which control is implemented. Nothing in the nature of control implies the hardware or software by which control is performed. Nevertheless, there must be some action mechanism A of dimensionality equal
to the dimensionality of the vector Z. Maybe A works directly on Z, but maybe A works on something else we can call “V”, and changes in V affect the values of the vector elements in Z. V also has to have a dimensionality equal to that of Z, R and A.

All the above is true of one control loop. What happens between A, V, and Z, and between A and Z and R together is relevant to the mechanism of control, but not to the functionality of control. Biological and machine control necessarily use different mechanisms,
but I don’t think that difference is what you are getting at. I think you are really getting at the relationship between R and V, which is functionally identical but conceptually different in the two contexts. An engineered control system is built so that
R can be set deliberately and the setting can determine the value of V. A biological system is built to survive long enough to propagate its structure down through time. That’s very different.

In an engineered system, an external Operator can set R and can observe V. R does not have to equal V or be of the same kind. R might be the angle of a pointer on a dial, while V could be a temperature or a rate of supply of a feedstock into a manufacturing
process. What matters to the Operator is that V responds reliably to changes in R, both of which she can perceive, though she may not be able to perceive the values of A and Z. In no biological system can any external Operator set or perceive R, though he
might be able to infer it by observing and manipulating V, if V is indeed observable from outside. By no means are all V’s in a biological organism perceptible to an outside observer, though many are.

In a biological organism, Z is not important to the survival of the organism. The V’s of control are. Some V’s are external variables, such as the nature and location of something that might eat it, or the concentration of some chemical in its internal fluids.
The Z’s, like the engineered dial pointer, are not things that might eat the perceiver.
The Zs are numbers . Most discussion of PCT assumes that the Z’s are the firing rates of neurons averages over time and bunches of correlated neurons, but that assumption could be discarded if other biosciences so suggest, without affecting PCT as a
theory in the slightest.

In PCT, Z is not a perception, but it is a number that represents the value of a perception. If R is to relate reliably to V, as should be the case if controlling Z is to be useful for survival, then Z must relate at least as reliably to V. We can say colloquially
that Z is a perception of V, where V is the location and demeanour of a tiger in the external universe, but when we do serious analysis we must be careful not to say that either V or Z is anything but a number or a vector of numbers having a specific dimensionality.

In the case of the tiger, the dimensions might be the nature of the object (“tiger”, not “penguin” nor shadows and sunny patches), the direction and distance to it, how interested it seems in hunting, and whether its hunting target is you. That’s a vector of
about five dimensions, which together might result in a single number that represents “degree of danger”, which could be a one-dimensional value worth controlling. “Worth controlling” means you are more likely to survive by controlling it than if you don’t,
unless you control it with a reference at a high value, as some young men (mainly men, I think) do, such as wing-suit-gliders who fly through gaps in high cliffs, or car drivers who “play chicken” at night.

Lots of quite different combinations of perceptions yield a Z that we might call “degree of danger”. A car approaching while you are crossing the road on foot, eating a mushroom you picked, living in Oklahoma, and so on and so on. All are multidimensional perceptions
that are converted by a learned (reorganized) process into a single number. This is true of most, if not all, of the perceptions we control.

If there is a single number (a scalar) Z, it corresponds to a scalar V that intervenes between A and Z, and that may be in the environment external to the organism. That V is not what we should call an “objective” property of the environment, however much the
“objective” danger to the organism “you” exists in the environment. “Objective” is a loaded term, because it refers to something that is absolutely true, a property never available to any biological organism. Here, it means that if a similar set of variable
values were to occur many times, and on some of those occasions the organism would be damaged or die, the higher the probability of damage, the greater the danger.

“You” may perceive danger when there is none, because the “tiger” might be a projection of a picture on a screen, or might be alive, but separated from you by a glass wall you cannot see. You may control for a non-zero degree of danger. If you live in Oklahoma
you perceive that your house could be destroyed by a tornado, but that perception is in your imagination. In your imagination or not, you perceive the danger to be in your environment.

“You” do not perceive the danger as being inside you. You perceive it as being part of the state of your current environment. It is real for “you”. And it is one-dimensional, having possible values that could range anywhere from zero (completely safe) to infinity
(“you” will certainly die). It is Qi in the control diagram.

It seems to me to be precisely the case that PCT actually demonstrates the difference between the two domains. While Bill
Powers started off as a control engineer, he also went the path of cybernetics, which led to new understanding, particularly in the biological, psychological, and sociological spaces. PCT leads to an understanding of autonomous purposeful behaviour via the
control agency. Any mechanical device that has a control system (governor) that enables regulation of behaviour according to sensory/signal input (like the steam engine) is capable of PCT-type behaviour on the dimensions controlled by the governor. These
are normally fairly simple. And to my knowledge, most/all of them were created by human beings so that the mechanical device makes use of biological principles.

By “PCT-type behaviour” do you mean acting on some variable to bring a related variable into agreement with a supplied setting? By the way, the biological-engineering relationship is two-way. In my younger days,
the discipline in question was called “bionics”, but that word has now taken on a quite different meaning. Of old, “bionics” meant that by solving an engineering problem one could better understand how biological systems operate, and by understanding how biological
systems operate, one could design better engineered systems using the solutions found by evolution.

What examples are there in the nonbiological, non-human-designed, material world of PCT behaviour?

You are asking about the second leg of the PCT “bionics” feedback loop. The PCT understanding of biological systems comes from understanding engineered systems. In future, engineered systems may be improved by understanding biological control. Rupert Young
is embarking on that project, and may eventually get to the point of evolving, or at least self-reorganizing, robots, which would be what I think you are asking about. I have no knowledge of any existing outside of simulation environments, but they might,
and I have no doubt that they will some day.

Martin

On 12/02/2017, 23:19, “Bruce Abbott” bbabbott@frontier.com wrote:

[From Bruce Abbott (2017.02.12.1820 EST)]

[Vyv Huddy 1955.12.02.2017]

VH: This is great set of posts on this thread and the previous one. Particularly helpful to see the posts by rick and bruce describing the figure in the Powers Science paper showing multiple V. I noticed that and missed why it was important.

VH: I don’t have my books with me now but i recall Bill Powers (i think) wrote somewhere that the controlled variable of a thermostat is actually the amount of coil of the strip not the temperature of the room itself. This is partly shown
by putting a flame directly under the thermostat - the furnace goes off without the room temperature changing.

BA: The controlled variable is the temperature of the air. The position of the coil (actually, the contact on the free end of the coil) is the thermostat’s perception of that temperature. The position of the other contact sets the thermostat’s
reference level. When the contacts meet, this generates a nonzero error signal indicating that the room temperature has fallen below the reference level. This causes the furnace to switch on (output function), heating the air and thus bringing the room temperature
up.

BA: The thermostat is a sensor of room temperature only to the extent that the coil temperature matches the room temperature. All sensors work this way, sensing a variable through its effect on the sensor. In this example changing temperatures
of the air are conveyed to the coil, producing different expansions on the two sides of the bimetallic strip, thus moving the contact on the free end. In the case of vision, photons striking molecules of photochemical in the photoreceptors cause light-sensitive
chemicals within the photoreceptors to break down, which through a series of chemical events causes the “generator potential� of the photoreceptor to change. This in turn alters the rate of firing of associated neurons.

VH: If so the controlled variable (qi) of a cruise control would be the frequency of the counting wheel turns in the speedometer mechanism? If so from that perspective there is no “actual” speed; cruise controls don’t work effectively on
a slippery surfaces and drivers are encouraged not to use them then.

BA: One could design cruise controls to sense the car’s speed in a variety of ways. The typical example is that speed is sensed indirectly by counting the rotational frequency of the car’s drive shaft. Under normal conditions this is
proportional to the speed of the car. This relationship breaks down if the wheels slip, as you note. This problem could be avoided by using an optical sensor to read the “optic flow� of the road beneath the car. However measured, there is still an actual
speed that is being measured, whether directly or indirectly, so long as the expected relationships hold. In the absence of wheel slippage, driveshaft rotations map directly onto the car’s speed. Biological systems experience the same difficulties; sensor
reports do not always match reality. Our sensors remain useful, however, because most of the time they provide readings that are good enough to go by.

VH: As i write this though I’m beginning to doubt the examples of thermostats or any other man made control system as clear illustrations of control in living systems. This is because machines input functions come about in a totally different
way to those of living things. They can be made to be much simpler; a cruise control can sense velocity via a single variable because of the way it is organised (a turning crank and some frequency counter). There is no way a living system can sense velocity
with a single environmental variable (without some sort of bio engineering).

BA: Why not? Optic flow will do it.

VH: I wonder if this difference makes these examples hard for me understand. I find the two domains don’t map onto each other that well.

BA: I don’t see any essential difference between human-engineered control systems and biological ones; in fact it is that correspondence that allowed Bill Powers (and others) to apply control-system principles to biological systems. What
is true is that biological systems are products of evolution, a process that involves gradual modification of what is already there. Unlike a human designer, evolution does not begin with a fresh sheet of paper. What results is more like a hodge-podge of
alterations and fixes than a clean design, and this can make it extremely difficult to tease out what the parts of a given system are and how they interconnect. Bill Powers notes, for example, that alpha motor neurons in the spinal cord combine the functions
of comparator and output function (and even that is probably an oversimplification). So it may be more difficult to figure out the system diagrams in biological systems than in human-engineered systems, but that does not imply that the underlying system principles
of the two are necessarily different. PCT is based on the well-supported assumption that behavior can be explained by control-system models.

VH: If cruise control p is really a single voltage in wire then it would be only intensity controller? For me Intensity control is best explained in the context of the muscle tone example, as in b:cp.

BA: In HPCT, perceptual signals at all levels are equivalent to single voltages in a wire (i.e., average neural current in a nerve). Thus, the fact that p in cruise control is embodied as a single voltage in a wire does not make the cruise
control an intensity controller.

In fact, all controllers in HPCT, at whatever level, are intensity controllers in the sense that they act to control the intensity of their neural signal p’s.

Bruce