# Computing output

**URL:** <http://discourse.iapct.org/t/computing-output/2728>\
**Category:** CSG1997\
**Created:** [February 22, 1997, 5:16pm UTC](http://discourse.iapct.org/t/computing-output/2728 "1997-02-22T17:16:05Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Bill\_Powers1](http://discourse.iapct.org/letter_avatar_proxy/v4/letter/b/8e7dd6/32.png) [@Bill\_Powers1](http://discourse.iapct.org/u/Bill_Powers1)\
**Post date:** [February 22, 1997, 5:16pm UTC](http://discourse.iapct.org/t/computing-output/2728/1 "1997-02-22T17:16:05Z")

</div>

[From Bill Powers (970222.0843 MST)]

I'm afraid that the term "computing output" has become a code expression in  
PCT that threatens to substitute for thought. The PCT model, like any other  
model of behavior, "computes output." In a control system with an  
integrating output function, the computation is

output = k\*integral(error signal).

So if one rejects any model of behavior that computes output, the PCT model  
must be rejected, too.

What this expression was originally meant to refer to was the concept that  
cognitive systems deduce, by reasoning backward from the desired effect, the  
neural signals necessary to produce that effect, after which the deduced  
signals are emitted. That is a \_particular way\_ of computing output.

What I have objected to is not the computation of output, but the particular  
way proposed for computing it. If you want an accurate term for this way, it  
would be "computing inverse kinematics and dynamics." But even that is a  
code expression, because far more than that must be done to compute the  
neural output signals required to produce a specific result.

Consider a familiar act like feeding a new pack of z-fold paper into your  
printer. You remove the cover, flip up the tractor-feed guides, place the  
end of the paper into the slots, and hold the paper there with one hand  
while slowly turning the platen knob until the tractor pegs engage the feed  
holes in the margins of the paper sheet. Then, flipping back the hold-down  
rollers and retracting the print head, you slowly turn the knob until the  
leading edge of the paper is just above the plane of the print head. Then  
you restore the various movable parts to their original positions and put  
the cover back on.

OK, that's the plan. Now, what neural signals should be emitted to which  
muscles to bring about the above-described perceived results? To figure this  
out, we must begin by measuring the relative humidity and the thickness of  
the paper, because these (among other factors) will determine how the paper  
reacts to forces applied to it. What we want is for the paper to be flat and  
aligned with the sprockets, and advanced so that when the sprocket is  
turned, the next pair of pegs will fall into the first set of holes in the  
paper margins. Holding the paper by one edge requires exerting a small  
torque that applies equal forward pressure on both sides of the paper  
without buckling it, while the other hand moves to the position of the  
platen knob and grasps it in an orientation that will permit turning it the  
right way. Since movements through space are required, the dynamics of the  
arm must be known, and their inverse must be obtained to deduce the forces  
needed to produce the required motions. Accomplishing just this much  
requires that certain sets of muscles go through many series of relaxations  
and contractions, coordinated with each other, which, when applied to the  
levers of the upper and lower arm and the finger segments, will produce the  
correct torques and grasping forces. And for each muscle, the neural signals  
needed to create those muscle contractions must be computed. I am actually  
skipping over a lot of details here. But assuming that all this has been  
done, the next action has to be to turn the platen knob by the right number  
of degrees to bring the paper up from under the platen, between the platen  
and the print head, and to the right level for printing the first line.  
Finally, the arms must move to position the hands next to the movable parts  
and levers, and the hands exert the forces needed to restore them to their  
original positions.

It is clearly absurd to think of deducing the neural signals required to  
create this complex result -- yet this result is among the simplest things  
we do. The problem is that IF ALL THESE CALCULATIONS COULD BE DONE BY THE  
BRAIN WITH THE NECESSARY ACCURACY, and IF THE CORRECT NEURAL SIGNALS COULD  
BE GENERATED WITH THE NECESSARY ACCURACY, this model would actually work!  
When it is applied to artificial systems using a digital computer with  
18-decimal accuracy of computation, and employing precision machinery with  
constant properties, and for the purpose of achieving a very simple  
mechanical result, it can actually be demonstrated to behave as advertised.

Of course these elementary demonstrations come nowhere near approaching the  
complexity of the simplest human actions. The computations must be fed  
myriad facts about the properties of the environment and the motor equipment  
of the behaving system. And the environment must be carefully protected  
against disturbances that have not been taken into account in the computations.

THIS is what "computing output" is supposed to mean, and THIS is what is  
wrong with this concept.

People who propose this kind of model to explain behavior seem to lack the  
imagination needed to see what is actually entailed in any real application  
of it. Immense complexities are dismissed with a wave of the hand, if they  
are even noticed. Simple applications that produce simple results are taken  
to indicate that the same approach would work in any application of any  
degree of complexity -- notwithstanding the fact that even to accomplish the  
simple demonstrations, we must strain the capabilities of our best computing  
machines (and mathematicians). The brain, it is said, is so unimagineably  
more capable than even our best computers that such problems would be  
trivial for it. All this statement of faith does is change the spelling of  
"brain" to G-O-D.

There are plenty of complexities awaiting us in the future of PCT. We will  
have to face them honestly as they arise. But what we have now is a simple  
model that handles very well the complex problems involved in motor  
behavior, and even in certain visual-motor behavior, and it strains our  
capabilities so little that models of motor behavior have run on  
10-megahertz 286 desktop computers in real time, even taking into account  
the kinematics and dynamics (\_forward\_) of a 3-df arm. The rest of the world  
may think that the way to do this is through "computing output" in the full  
sense described above, but if that's true, the rest of the world is wrong.

Best,

Bill P.