Perceptual Control Theory (PCT)And the On-Going Evolution of CultureVersion 1.01 Beta ©April 2008

F. T. Cloak, Jr.

#SLIDE 1#. "Perceptual Control Theory(PCT) and the Evolution of Culture"

#SLIDE 2#. Darwin showed that living things evolve by the natural selection of biological features; i.e., he showed how evolution works.

But he could not show how natural selection works, because he didn't know about genetics. Later on, we learned how natural selection works through the rediscovery of Mendel and the resulting New Synthesis. #CLICK01#

Richard Dawkins and I, building on the work of George Williams and others, and after demonstrating the primacy of genes as units of natural selection, argued that culture evolves through the natural selection of cultural features. #CLICK02# But we could not show how that works, because we lacked a comparable theory of cultural transmission. #CLICK03#

As I've said previously, I think William T. Powers's Perceptual Control Theory, or PCT, may help us to address that lack. #CLICK04# Indeed, as I intend to show here, by providing a robust hypothesis about culture acquisition, PCT may actually reveal the elemental units of culture and cultural evolution.

#SLIDE 3#. PART ONE. PERCEPTUAL CONTROL THEORY (PCT)Perceptual Control Theory -- PCT -- challenges conventional assumptions about behavior, by asserting that when an organism acts it is invariably comparing its perceptions to perceptual reference standards stored in its nervous system, and that it will continue to act until its perceptions approximate those standards. #CLICK#

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The neuroanatomy and physiology of perceptual control is a product of hundreds of millions of years of evolution. The reference standards, too, are products of blind variation and selective retention -- genetic evolution, learning by individual carriers, and, in some species, cultural evolution. Thus the perceptual control apparatus is adapted to early and recent past environmental conditions -- both within and outside of the carrying organism. #CLICK#

The perceptions which the apparatus controls are, however, perceptions of the organism's current environmental conditions, as detected by its sensory cells, inferred by its neural input machinery, and stored in its memory.

PCT thus understands behavior not as simple responses to immediate stimuli, but as the maintenance of historically established states of the nervous system in the face of variations in its immediate surroundings.

#SLIDE 4#. The elemental neural mechanisms by which normal perceptual control occurs, the units of behavioral organization, are perceptual control systems, or CSes. As we shall see, CSes operate in functional hierarchies in the organism's central nervous system, each CS-in-a-hierarchy evoking reference standards in CSes below it.

Each individual CS consists of #CLICK01# an input function, #CLICK02# a comparator function, #CLICK03# an output function, #CLICK04# and memory in which its reference standards are stored.

The Input Function #CLICK05# receives perceptual signals from one or more CSes lower in the hierarchy or from sensory cells, and consolidates those signals, #CLICK06# producing its own perceptual signal, #CLICK07# which it sends to the Comparator #CLICK08# and passes on to a higher-level CS, #CLICK09# while storing some of it in memory.

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From time to time, #CLICK10# Memory receives an address signal from a higher-level CS’s Output Function, #CLICK11# determines the best-matching reference standard, #CLICK12# and sends that to the Comparator. Unless the input signal and the reference signal agree, #CLICK13# the Comparator sends an error signal to the Output Function, #CLICK14# which in turn sends signals addressing one or more lower-level CSes or reaching outside the CS realm to stimulate one or more muscles.

Signals are not generally simple. #CLICK15# Indeed, they may vary enormously in the amount of information they carry. The signals of a mid-level CS might be comparable in bandwidth to signals of high-definition television, complete with sound.

#SLIDE 5#. So here’s a typical CS in its resting state. Perceptual signals come in constantly, and are processed and passed on. But when a higher-level CS addresses #CLICK01# -- in other words, Googles -- a CS's memory, it springs into action. Selecting from stored perceptions which match the address signal, #CLICK02# memory sends a reference signal to the comparator. If the comparator determines #CLICK03# that the perceptual signal from the Input Function sufficiently approximates the reference signal, it does nothing. In other words, its surroundings appear, to this particular CS, to be O.K., so no action is necessary on its part.

But if the perceptual signal does not sufficiently approximate the reference signal, #CLICK04# the comparator sends an error signal to the output function, #CLICK05# which in turn generates address signals to lower-level CSes or directly to muscles.

#SLIDE 6#. The organism acts, and thus perhaps changes how their surroundings appear to its CSes, in particular to the CS we are talking about. This negative feedback process is repeated -- at several times per second -- until the comparator is satisfied that the signal from the Input Function #CLICK01# adequately approximates the reference signal. /comparator animation stops/comparator output stops/output animation

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stops/output output stops/#CLICK02# surroundings animation stops

Note that even though the comparator of this CS is satisfied, the comparator of a higher-level CS may not be satisfied with its perceptions,

#SLIDE 7#. so it may send down a different address signal, #CLICK# altering or restarting the process here at this level.

So from this we see that each CS uses CSes below it to control its perceptions and, in turn, is similarly used by the CSes above it.

#SLIDE 8#. Now let's take a look at the way CSes are linked together to interact in an animal's nervous system.

#CLICK01# A three-dimensional schematic diagram of CS interaction would show the CSes arranged in a number of concentric spheres, rather like an onion. #CLICK02# …

#SLIDE 9#. The CSes in the outermost sphere or layer are connected to sensory cells and muscles.

#CLICK# CSes in each layer are connected to CSes in layers closer to the center, passing perceptual signals to them, and, as needed, receiving address signals from them.

#SLIDE 10#. An organism of any complexity thus has thousands of CSes acting at the same time, each CS a module in at least one interactive hierarchy.

#CLICK01# Through evolution, learning, and culture this cacophony of nervous activity has become a fairly well integrated parliament of CS modules. The underlying neural machinery can have been devised only by natural selection, operating on the animal nervous system over hundreds of millions of years.

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#SLIDE 11#. The hierarchy of CS modular levels is not hard and fast, and is still being researched, but the general principle surely holds.

Powers's most recent listing of CS levels, starting with the outermost, or bottom level, includes

a. #1# CS modules controlling perceptions of Intensities of stimulation - of sensory nerve-endings -- light, sound, heat, pressure, and proprioceptive feedbacks from muscle fibers.

b. #2# CS modules controlling perceptions of Sensations, compiled from intensities -- colors, shapes, edges, musical tones

c. #3# CS modules controlling perceptions of Configurations -- particular static arrangements of sensations, such as objects and musical chords

d. #4# CS modules controlling perceptions of Transitions -- changes in level 1, 2, and 3 perceptions, for example the motion of an object, or a musical chord transition

e. #5# Modules controlling perceptions of Events -- familiar packages of lower-level perceptions

f. #6# Modules controlling perceptions of Relations -- between lower-level perceptions -- such as above, below, near, or following

g. #7# Modules controlling perceptions of Categories, to which lower level perceptions belong, or don't

h. #8# Modules controlling perceptions of Sequences -- temporal orders of lower level perceptions

i. #9# Modules controlling perceptions of Programs -- "structures of tests and choice-points connecting

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sequences" or other lower level perceptions. Quoting Powers: "To control a perception of a program is to vary the lower level perceptions to keep the program going right." An example is a routine for performing long division. Level 9 is the level of rational thinking.

j. #10# Modules controlling perceptions of Principles: the reasons why we have programs

k. #11# Modules controlling perceptions of Systems: organizations of principles, from religions to bowling leagues

#SLIDE 12#. Now that we understand how Control System Modules work in a hierarchy, let’s look again at what the Input Function of each Module does. A Configuration Level Input Function, for example, takes in Sensation Level Perceptual Signals #CLICK01# and interprets them as a bowl of fruit. #CLICK02# That is to say, from those perceptual signals it infers that there is a bowl of fruit out there at a certain place in the world.

#SLIDE 13#. So an Input Function is an inference engine, #SLIDE 14#. and it might be more accurate to say that an

Input Function takes in perceptual signals from a lower level Module and delivers inferential signals to the Comparator and Memory storage and to the next higher level Module

#SLIDE 15#. – which in turn takes them in as perceptual

signals.

We should realize, however, that the inferences made by the Control Modules of an evolved brain, while pragmatically accurate, are not necessarily the inferences that would be made by a team of scientists studying the same environment.

We should also note that the evolved Control Modules can and often do make inferences that could not be made by a scientific team today; some of them, for example, can infer another animal’s intentions pretty reliably, by reading his

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facial expression or his “body language”. But about that more later.

To illustrate how the levels work together,

#SLIDE 16#. Suppose that the Configuration-level Module which is inferring the fruit-bowl gets Googled #CLICK01# by a higher-level Module, with an address signal eliciting PEAR from its memory. In other words, it's being told "Control a perception -- that is, obtain and maintain a perception -- of a pear."

Not close enough. #CLICK02# Your Configuration-level Module's comparator sends out an error-signal #CLICK03# telling its output function to address various Sensation-level Modules. But wait a minute.

#SLIDE 17#. At this point we need to change our method of exposition, to accommodate multiple interacting Modules on one screen. From now on, we will identify a CS Module by a noun-phrase representing the perception which that Module is currently controlling. #CLICK# For example, the configuration-level Module now under study can be identified simply as *PEAR*.

And from now on, a whole CS Module will be represented schematically by a single box, containing a verbal, pictorial, or diagrammatic representation of the perception which that Module controls. For example --

#SLIDE 18#. With that in mind --

#SLIDE 19#. CS Module PEAR's output-signals address several sensation-level Modules, evoking from their several memories reference signals to

#CLICK01# Perceive greenish-yellow, #AGAIN02# perceive pear-shape,

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#AGAIN03# perceive pear-odor.

#CLICK04# The Sensation-level Modules send address signals to Intensity-level Modules, evoking:#CLICK05# Perceive eye-movement rightward and downward, #AGAIN06# perceive nostrils expanding, #AGAIN07# perceive sniffing.

#SLIDE 20#. ---- and those Modules presumably modify the tensions in muscles in eye, nose, lungs, neck, etc., adjusting those intensities #CLICK01# until their input proprioceptions approximate their respective internal reference signals.

#CLICK02# From the resulting visual and olfactory intensity perceptions, the second level Modules infer sensations, compare them to the Pear Odor, Shape, and Color sensation standards, adjust their output address signals accordingly, #CLICK03# and send them on up to PEAR….

In a fraction of a second, after several dozen iterations, PEAR’s Input Function infers that it is perceiving a pear, and all the Modules involved are, for the moment, at equilibrium. #CLICK04# No address signals are going out, and you are focused on the pear.

So, in the hierarchy, each Module calls upon the ones below it to help it control its assigned perception, by assigning them perceptions to control.

O.K. Now, how did you get confronted with that fruit-bowl, and why are you seeking a perception of a pear?

#SLIDE 21#. In other words,

#SLIDE 22#. where did that PEAR-Google come from?

#CLICK01# It might well have come from a Transition-level Module *REACHING FOR PEAR*, #CLICK02# Googled by an Event-level Module *TAKING PEAR FROM BOWL*, #CLICK03#

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ultimately evoked by a Program-level Module *GETTING AND EATING A PEAR* #CLICK04# -- which utilizes many other subordinate Modules to get you into arms-length of the fruit-bowl from wherever you were, and afterwards to get you to proceed with the task of pear-ingestion.

#SLIDE 23#. To summarize our presentation of PCT so far:Behavior, in general, can be understood as the control of perception. #CLICK01#The unit of behavior is the Control System (CS), #CLICK02# and even the simplest activity requires the cooperative interaction of an inordinate number of CSes. #CLICK03# CSes are indeed the individual bricks of behavioral castles.

#SLIDE 24#. CSes are arrayed as Modules in interactive hierarchies. #CLICK01# Each Module passes its inferences, about the world outside the CS realm, to the next higher level in the form of perceptual signals. #CLICK02# To control its incoming perceptions, each CS Module uses lower-level Modules, by invoking reference standards for them to control their perceptions to. #CLICK03# The hierarchy provides behavioral reference standards for the entire range of human activity. #CLICK04#

Part Two#SLIDE 25#.#SLIDE 26#. Part Two. Evolution of the Input Function and

Culture Acquisition

We've said that Input Functions are, in effect, Inference Engines. #CLICK01# So far the inferences we've discussed have been "empirical", such as a scientist or other careful objective observer might make. #CLICK02#

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For example, a 3rd Level Input Function infers the presence of a bowl of fruit from a set of perceptions from 2nd Level modules, or an Event Level Input Function infers that a dog is chasing a cat from Transition Level perceptions of a moving dog, a moving cat, and so forth. Another example would be a prey animal's inferring that a predator was present.

These empirical inference engines no doubt evolved from simpler neural networks half a billion years ago, and have been refined by natural selection ever since.

But successful inferences may be trans-empirical or, in the vernacular, judgmental. #CLICK03# …

#SLIDE 27#. As a very simple and early example, the prey animal might infer that the predator has detected him, or not, before the predator actually starts to attack. #CLICK01#

Continuing in that vein, the next evolutionary stage might be that the prey infers whether or not the predator intends to attack. From input perceptions of the predator's behavior, the prey is inferring the reference standard to which the predator is controlling its perceptions. #CLICK02#

It would be interesting to survey the literature of ethology to learn what species are capable of making inferences at each of these stages, and trying to reconstruct their phylogeny. Certainly we can say that the ability to guess, with increasing degrees of accuracy, what the other fellow was trying to do, what he was "up to", has had great survival value. Besides predator/prey relations, such ability has been very useful in interactions with conspecifics involving sex, fighting, dominance, and other social activities. #CLICK03# We can also say that it was a long time coming, and that it has been around for several dozen million years.

As it evolved, reference standard inference in the social realm eventually enabled the recognition of individuals, empathy, so-called "theory of mind", and the emergence of the sense of self, beginning perhaps 10 million years ago.

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More to the point of our discussion here, it enabled imitation. #CLICK04#...

#SLIDE 28#. Imitation entails perceiving the actions of another, #CLICK01# inferring the reference standards being controlled to, #CLICK02# recognizing those standards in one's own repertory, #CLICK03# and evoking them to control one's own perceptions. #CLICK04# In our own primate family line, that capability began to evolve perhaps 10 million years ago, although it appears sporadically in quite a few other taxonomic groups.

#SLIDE 29#. About two million years ago, the genes modifying input functions to enable culture acquisition appeared and began to succeed. #CLICK01# Our ancestors were then able not only to infer each other's reference standards but actually to adopt them if they were not already in repertory.

Since the ability to store inferences from perceptions was present long before, it's rather puzzling that the emergence of culture acquisition took so long. Storing a perception-inference of a satisfactory behavior of one's own, during trial-and-error learning, goes way back in our phylogeny. Apparently storing a perception-inference of a behavior of another animal as one's own reference standard is a very different matter, but that's the essence of culture acquisition, as we shall see.

Finally, and parenthetically, the language instinct may well have evolved as a spectacular elaboration of the culture acquisition machinery. #CLICK02#

#SLIDE 30#. Individuals acquire culture largely through observational learning.

Descriptively, that means simply that an observer animal O observes the behavior of a demonstrator animal D #CLICK01# and

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later exhibits similar behavior, which he has never before exhibited. #CLICK02#

Without PCT, one is hard put to understand how culture-acquisition works, because it's difficult to conceptualize how O can copy an entire behavior of D, especially its motor elements, into his own nervous system. This difficulty is exacerbated because O may simultaneously modify the behavior to suit his own capabilities and circumstances. #CLICK03#

PCT nicely provides the mechanism for culture-acquisition, as per this definition:

#SLIDE 31#. Observing the behavior of a demonstrator animal D, #CLICK01# an observer animal O infers the reference standards to which D is controlling her perceptions, #CLICK02# and stores the inferred standards in the memory of one or more new CS Modules in his own brain. Then O's newly acquired CS Modules control their input perceptions by using existing and/or additional newly acquired lower-level Modules. #CLICK03#

To the extent that O's movements now seem to mimic D's, it is only because they now have a common modular CS hierarchy.

In the vernacular, O observes D's behavior and figures out what she is trying to do. Then he works out the means to that goal for himself.

Please note that the above discussion assumes that O does not already possess all of the reference standards in question; if he does, he is not acquiring culture from D. When he controls his perception to those standards, he is simply imitating her.

In support of this formulation, I offer an interpretation of a recent experiment involving imitation, and possibly culture acquisition, in dogs.

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#SLIDE 32#. Very briefly, the Demonstrator D was an animal who had been trained to pull on a stick with her paw to obtain a food reward. There were two groups of Observer dogs. When each O of Group 1 was exposed to D, D had a ball in her mouth.#CLICK01# Otherwise, what the members of the two O-groups saw was the same: D pulling on the stick with her paw and obtaining the reward.#CLICK02#...#CLICK03#

The result was remarkable: Most of the Group 2 Os, who saw D without the ball, pulled the stick, as she did, with their paws.#CLICK04# But the Group 1 Os, who saw her with the ball in her mouth, tended to use their mouths to pull the stick!#CLICK05#...#CLICK06#

The experimenters called this an example of "inferential, selective imitation", which indeed it is. I argue that PCT provides a mechanism for it and all instances of imitation. In the case of Group 2, it may also exemplify culture-acquisition.

The Os in both groups inferred immediately that D was trying to move the stick; i.e., that she was controlling a perception of Stick Moving.#CLICK07#

Pulling or Tugging with the Mouth is a well-established CS Module in dogs, the standard Module invoked by an error signal from Stick Moving. As soon as a Group 1 O saw that Stick Moving was the goal, the rest of the hierarchy kicked in. #CLICK08# The ball in D's mouth was ignored, or perhaps not even noticed, by most of the Group 1 Os. This is an apparent case of simple imitation.

Only a few of the Group 2 Os, on the other hand, made that inferential leap. It didn't make sense to the rest of them that D's perceptual goal was only Stick Moving, so they inferred that D must be trying to pull the stick with her paw; i.e., that she was controlling a perception of Pulling the Stick with the Paw.#CLICK09# If a Group 2 O was familiar with that perception, that is if he already had it stored as a reference standard, he invoked it and simply imitated. If not, he stored Pulling the Stick with the Paw in a new

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Module as a reference standard and proceeded to control his perception accordingly -- a case of culture-acquisition.

#SLIDE 33#. As I said at the beginning of Part One, CSes are the units of behavioral organization. The PCT-derived understanding of culture acquisition therefore solves, in my opinion, the problem of the elemental units of culture. Control modules or reference standards so acquired are what I once called “cultural instructions” and Richard Dawkins renamed “memes”. #CLICK01# In fact, the only difference between a meme and any other control module is the means by which the carrying organism acquired it.

Equipped with a full complement of memes, encompassing every level of the CS hierarchy, a people can build a whole culture, complete with ethos, rituals, social organizations and structures, child-rearing patterns, and artifacts.

In Part Three, upcoming, I will analyze a simple skill task and its execution, using PCT tools. In doing so, I will demonstrate another vital feature of PCT.

#SLIDE 34#.

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Part Three

#SLIDE 35#. The task to be analyzed was as follows. 12 young men from the same cultural milieu were brought into a laboratory setting one at a time. Each found himself in front of a table, on which was a small sheet of plywood, on which were arranged two boards, two nails, and a hammer, as shown.

#SLIDE 36#. Each subject heard an identical tape recording: "Please nail the boards together in the form of an X." Filming commenced immediately, and terminated about when the subject began to drive a nail home. Every subject completed the task successfully.

The resulting film negatives were printed on long strips of paper and subjected to frame by frame comparison,

#SLIDE 37#. whereby certain similarities and differences were noted in the subjects' approach to the task.

Before presenting the PCT analysis, I will give you a run-through of all twelve film-clips. Please note the following commonalities as you watch the clips:

#SLIDE 38#.1) All twelve subjects manipulate the boards into position before driving the first nail; #CLICK01# that is, none start one or both nails first, although the recorded voice command seems to suggest proceeding that way.

2) Some subjects form the X by drawing both boards into the workspace and using one hand on each; #CLICK02# the others simply use one hand to turn the top board.

3) All twelve subjects remove the hammer from the workspace as or before they begin to handle boards. #CLICK03#

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4) After forming the X, all twelve subjects exhibit the same nailing technique: #CLICK04# hold the nail against the formed boards, tap the nail until it will stand alone, and then drive it home with more vigorous blows of the hammer. Now here are the clips. Running at half speed, they last a little under six minutes.

#SLIDE 39#. {Wait for end of clip – Subject No. 4 is last}

OK, now let's undertake a PCT analysis of what we've just seen.

#SLIDE 40#.At the system level, every subject is controlling a perception of being an upper-division undergraduate, #CLICK01# enrolled in my introductory anthropology course, #CLICK02# and voluntarily participating in an experiment in cultural anthropology. #CLICK03#

At the level of principle, everyone is controlling for the value of conforming to the experimenter/professor's wishes, #CLICK04# conveyed by the presented display and the recorded voice, to nail the boards together in the form of an X.

Each controls to the same program-level module: forming the boards into an X and then nailing them together. #CLICK05#

And in the end, each follows the same pre-written program/meme for the nailing process. #CLICK06#

It is in the execution of the "forming boards" part of the program that the subjects appear to diverge.

In my previous analysis of these data, I made the mistake of assuming that each variation in the final orientation of the X, and each variation in the way the boards were manipulated to get there, was the outcome of controlling to a specific meme. I think now that it makes more sense to regard those variations as essentially fortuitous; that is, the subjects all controlled to a rather hazy reference standard of one rectangular object lying at an angle atop another. #CLICK07#

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And all the subjects began by controlling a perception of one or both boards moving into the workspace. #CLICK08#

From there, each subject essentially ad libbed, choosing reference standards and controlling his perceptions to them as he went along. Some were clearly more adept than others, reflecting past experience; that is to say, they had pre-acquired and honed CS Modules, and more ably accessed them when needed.

In addition, the subjects varied in the extent to which they applied imagination to the Forming Boards phase of the task. That is, in the extent to which they rehearsed their behavior in their heads before executing it on the ground.

The way PCT handles imagination is well illustrated by variations in the handling of the hammer before its actual use in driving the nail. In every case the subject moved the hammer as, or before, he drew one or more boards closer to himself, into the workspace.

#SLIDE 41#. {Transition Slide}#SLIDE 42#. It seems pretty obvious that everyone moved

the hammer to avoid perceiving a collision. As a base line, consider the case of Subject No. 5, who shows no imagination. #CLICK01#

Before the recorded voice, the workspace is still. The Input Function of the Moving Boards module is inferring the presence of the boards, #CLICK02# the Input Function of the Removing Hammer module is inferring the presence of the hammer, #CLICK03# and the Input Function of the Boards Moving module is combining their perceptual signals to infer the presence of the boards and hammer close together. #CLICK04#

Now comes the Address Signal to Boards Moving, #CLICK05# which in turn addresses the memory of Moving Boards. #CLICK06# That Memory sends a reference signal to the Comparator #CLICK07# which, perceiving that the boards are not moving, sends an Error Signal to the Output Function, #CLICK08# which

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addresses lower-level control modules down to muscles, #CLICK09# and we observe the boards moving. #CLICK10 does “environment” and starts the clip# ... #CLICK11 stops the clip when the boards meet the hammer#

When Boards Moving infers that the boards are striking the hammer, #CLICK12 # it acts to eliminate the disturbance by invoking Removing Hammer, #CLICK13# and the situation is immediately resolved. #CLICK14 when hammer has been removed #

In summary, Subject No. 5 moves the boards only when we observe the boards actually striking the hammer. In the vernacular, he fails to anticipate the collision and only reacts to it; he lacks imagination. In PCT terms, his control modules are in control mode the whole time.

#SLIDE 43#. Now consider Subject No. 8, who does use imagination to anticipate the boards striking the hammer. #CLICK01# Again, before the voice command the workspace is still, the input sequences the only ones active. #CLICK02#

When the address signal comes to No. 8's Boards Moving module, #CLICK03# it too addresses the memory of Moving Boards, #CLICK04# and that Memory propagates a reference signal. #CLICK05# But Subject No. 8's Moving Boards module is in imagination mode. For the time being, the signal is diverted across a shunt that carries it directly to the path of Boards Moving's input perceptual signal. #CLICK06# The control sequence down the hierarchy of modules to muscles, and the feedback sequence from sensors back to Moving Boards and Boards Moving, are cut out of the loop. So Moving Boards' reference standard becomes one of Boards Moving's input perceptions.

Boards Moving therefore infers that the boards are striking the hammer, and invokes Removing Hammer. #CLICK07# ...and we observe the hammer being removed ... #CLICK08 stops movie when hammer is removed#.

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Then the Moving Boards module switches from Imagination Mode to Control Mode, #CLICK09 ... and we observe the boards moved and then formed and nailed together

#SLIDE 44#.You probably noticed that several of the subjects, including No. 5 and No. 8, once they have the hammer in hand keep it there, whereas others put it down while they form the X with the boards, as if it hasn't occurred to them that they'll need the hammer again immediately. #CLICK01# Those who keep the hammer apparently run the whole task in imagination mode, at least to the point of starting the nailing program, before beginning. #CLICK02

It's not too much of a stretch to assert that all exercises of imagination and anticipation are products of control modules acting in imagination mode. #CLICK03# That would even including lower-case intelligent design or creativity -- what Donald Campbell dubbed "evolutionary epistemology": blind variation and selective retention inside the nervous system. #CLICK04#

#SLIDE 45#.#SLIDE 46#. Part Four. The Evolution of Cultural Features by

means of Natural Selection

In Part Two we showed how Input Functions of Control Modules may have evolved as inference engines. Initially they were simply interpreters of observable conditions. Later they became interpreters of others' intentions, and finally they became acquirers of others' intentions, in other words culture acquisition mechanisms.

#SLIDE 47#. This was all of course through genetic evolution; each of these capabilities was built on the preceding ones, and each capability was refined constantly, always by the mechanism of natural selection. That means simply that genes which made more accurate and otherwise

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useful input functions thereby enabled themselves to propagate at the expense of competing genes, and eventually to replace the latter.

In the case of culture acquisition engines, selection has clearly favored those that made more faithful copies of the demonstrator's reference standards, for exactly the same reasons that, starting millions of years before, selection favored mechanisms that copied genes faithfully. #CLICK01# If having a cultural repertory is valuable, then being able to propagate that culture accurately must also be valuable.

So one should not be terribly surprised that humans, particularly the very young, are extremely adept at culture acquisition.

And the more accurate the copying, the more powerfully natural selection can operate on that which is copied.

So memes which are better adapted to their environment will succeed at the expense of those less well adapted, where "adapted" refers to the ability to cooperate and compete with other memes in that environment. #CLICK02# Memes controlling to which makes their carriers better able than others to acquire resources, avoid predation and other dangers, form social bonds, enjoy sexual opportunities, and so forth, will succeed. #CLICK03#

The operative word here is "better". We don't expect perfection from genetic selection, far from it, and we shouldn't expect it from culture selection. But selection for the better can, and has, produced some remarkable results. #CLICK04#

Thank you for viewing “Perceptual Control Theory and the On-Going Evolution of Culture”

END

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Notes(XX,YY means #SLIDEXX#,#CLICKYY#)

02,02 Dawkins 1976, 1982; Cloak 1975; Williams 196602,04 Powers 1973; for up-to-date information about PCT, see

http://www.perceptualcontroltheory.org/04,00 Powers 1973: 57-8104,01-14 Powers 1973: Figure 15-3, p. 22111,00-11 Powers 2004: 135ff.30,00-01 Bandura and Walters 196332,00-07 Range et al.40,06 Cloak 1974/200743,05 Powers 1973: 222-644,03 Campbell 1960

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Bandura, A. (1965). Behavioral modifications through modeling procedures. In Krasner, L., and Ullmann, L. P. (eds.), Research in Behavioral Modification, Holt, Rinehart and Winston, New York, pp. 310-340.

Bourbon, W.T., Copeland, K.E., Dyer, V.R., Harman, W.K. and Mosley, B.L. (1990). On the Accuracy and Reliability of Predictions by Control System Theory. Perceptual and Motor Skills 71: 1331-1338.

Campbell, D. T. (1960). Blind variation and selective retention in creative thought as in other knowledge processes. Psychological Review 67: 380-400.

Cloak, F. T., Jr. (1974/2007). Cultural ethology experiment number one. Paper presented at 73d Annual Meeting of American Anthropological Association, Mexico City. Available (2007) as a narrated PowerPoint presentation from the author.

Cloak, F.T., Jr. (1975). Is a cultural ethology possible? Human Ecology 3: 161-182.

Dawkins, R. (1976). The Selfish Gene. Oxford University Press, Oxford.Dawkins, R. (1982). The Extended Phenotype: The Gene as the Unit of

Selection. Freeman, Oxford.Powers, W. T. (1973). Behavior: The Control of Perception, Aldine,

Chicago.Powers, W. T. (2004). Making Sense of Behavior: The Meaning of Control.

New Canaan, CT., Benchmark Publications.Range, F., Z. Viranyi and L. Huber. (2007). Selective Imitation in Domestic

Dogs. Current Biology 17: 868–872Williams, G. C. (1966). Adaptation and Natural Selection: A Critique of

Some Current Evolutionary Thought, Princeton University Press, Princeton, N.J.

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