Original_To:  BITNET%"csg-l@uiucvmd.bitnet"
Original_cc:  TBOURBON
Newsgroups: bit.listserv.csg-l
Date:         Mon, 21 Dec 1992 12:27:00 CDT
From:         Tom Bourbon <TBOURBON@UTMBEACH.BITNET>
Subject:      Re: Martin to Rick on Shannon

From: Tom Bourbon (921221  10:15 CST)


Re: [Martin Taylor 921218 18:30]
Replying to (Tom Bourbon 921218 14:38)
On: Martin to Rick on Shannon

Make a simple offer ...!

********************************************
   Portions of Tom's original message to Martin:
May I repeat and elaborate on an invitation I made about a year
ago?  I will send you one of my programs in which two systems (two
people, the two hands of one person, two models, or a person and a
model) interact and produce controlled relationships. ...

I invite you to add to the PCT model any features of information
theory that you believe must be there.  If necessary, use features
from information theory to replace those from PCT.

If your changes improve the predictions by the model, there will be
no argument and no complaint:  You will have demonstrated that a
person who does not understand Shannon or information theory does
not understand PCT.

********************************************
   Martin to Tom, after lengthy discussion:
Have I done that to your satisfaction?

********************************************
   Tom to Martin (in the present);
No.

********************************************
   More from earlier sections of Martin's reply to Tom:
I guess I'd better try to describe, as I did a year or so ago,
wherein information theory helps in the understanding of PCT.  I
didn't succeed in getting across then, and I'm not sure I'll do any
better now.  I should think that the prediction for your proposed
system would be no better and no worse than you would get without
it, because you are dealing with a transparent system of one
control level.  The understanding you get with information theory
is not at the level of setting the parameters.

If I were to try to develop a model to make predictions in your
experiment, I expect it would look essentially identical to yours,
because the key elements would be the gain and delays in the two
interacting loops.

********************************************
   Tom to Martin (in the present:
All you need do in the case of coordination between two systems is
show me how, working back from Shannon's principles, you end up
with two interacting PCT systems, each with the features Bill
postulated for a single system.  If the models that emerge from
Shannon's principles are identical to those presently envisioned in
PCT, your point is made.  But I expect to sit down in front of a
PC, grasp a control device, and interact with a Shannon-system in
real time, with results at least as good as those when I coordinate
with a PCT model.  And when, without warning to my virtual partner,
I alter my intentions in mid-run, I expect the Shannon-system to do
the things another person or a PCT model would do.  If the
situation for modeling coordination is all that transparent, the
task of working from first principles and creating the Shannon-
controller should not be terribly difficult.

As for the single control level, that is merely the form in which
I have published on interacting systems:  In several other programs
my interacting systems are hierarchical (two levels).  In ARM, Bill
and Greg have programmed a much more elaborate coordinated system,
with a hierarchy of PCT loops and with loops in parallel.

********************************************
    Martin continuing his reply to Tom:
An electricity meter reader does not need to understand the
principles of electromagnetism to get an accurate meter reading.
This challenge is misdirected.  If there are places where I think
the prediction would be improved, they are likely to be structural,
such as in the division of attention, monitoring behaviour or some
such.  What should be improved, in general, is understanding, not
meter reading.

I said that if you don't understand Shannon, you won't understand
PCT.  I didn't say you won't be able to use PCT to make
predictions. ================

********************************************
   Tom to Martin (in the present):
Let me be sure I follow you correctly:  Not only do PCT modelers
not understand PCT (your original claim); now modelers are akin to
meter readers and have no need to understand PCT.

********************************************
     More from Martin's reply to Tom (after a long discussion):
It is that kind of thing that I refer to as "understanding" PCT,
not the making of predictions for simple linear phenomena.  Linear
models are fine when you have found the right ECS connections and
have plugged in model parameters.  I am talking about seeing why
those models are as they are.

********************************************
   Tom to Martin (in the present):
Neither the model of the control system or the environmental
phenomena with which it interacts need be linear.  Bill has
published and posted on introducing nonlinearity into the PCT model
and into the environment.  So has Rick.  I haven't, but I have
tested the effects of nonlinearities in the coordinated systems:
The models continued to function at the same level of realism.  I
will try to put together a post on that topic, in the style of my
post a few days ago on adding disturbances to various signals in
the control system.

In the meanwhile, I wonder why so many people continue to assert
that PCT models are necessarily linear and cannot explain and
predict events when there are nonlinearities in the system or the
environment.  Where do these ideas come from?  Why won't they go
away?  (Dennis Delprato:  If you are starting a collection of false
assumptions and assertions about PCT, this certainly is one.  We
should compare collections -- mine goes back a few years.)
Everyone who clings to that assumption should read Bill's
"spadework" paper in Psych. Review (1978 -- 14 years ago folks)
where he discussed various blunders in the history of cybernetics.
That is also where he quantitatively demonstrated the ease with
which a PCT model maintains control in the presence of
nonlinearities.)

********************************************
    Martin replying to Bill Powers' reply to Martin's reply to Tom:
(TB: What tangled webs we weave ...!
[Martin Taylor 921218 19:45]
Bill to Tom Bourbon (921218.1438 CST) --

********************************************
   Bill quoting Tom:
In the past, both of us wondered how, specifically, Shannon's
ideas, or any of the major concepts from information theory, would
improve any of the quantitative predictions we make with our simple
PCT models.

********************************************
   Bill replying to Tom:>
This is the right question about information theory -- not "does it
apply?" but "what does it add?" The basic problem I see is that
information theory would apply equally well to an S-R model or a
plan-then-execute cognitive model -- there's nothing unique about
control theory as a place to apply it. Information theory says
nothing about closed loops or their properties OTHER THAN what it
has to say about information-carrying capacity of the various
signal paths.

********************************************
   Martin replying to Bill:
You are right, but that "OTHER THAN" is a pretty big place to hide
very important stuff.  I had not previously realized that you
wanted me to use Shannon to differentiate between S-R and Plan-
then-execute. I think I did incidentally make that discrimination
in my posting in response to the same posting by Tom.  At least I
think I showed how applying Shannon demonstrated that neither S-R
nor Plan-then-execute could be viable.  But we knew that already,
so I didn't play it up.

********************************************
   Tom to Martin (in the present):
Perhaps Bill and I both missed it, but I did not see where you used
Shannon to demonstrate that neither S-R or Plan-then-execute models
would be viable.  Your remark leads me to think that you also used
Shannon to demonstrate that a PCT model would be viable.  Was that
the case?

********************************************
   More of Bill replying to Martin's reply to Tom:
In all these cases, something has to be added to get a workable
system. And I don't think that this something comes from the
abstract principles involved, however convincingly one can prove
that they apply.

********************************************
   Martin replying to Bill:
Yes, that's absolutely right.  Natural laws are no use without
boundary conditions to describe particular situations.  But if you
understand the abstract principles, you can make better
[bridges/kettles/radios/control systems].

********************************************
   Tom to Martin  (in the present):
Your concluding remark brings us back to where we started.  That is
what I asked you to do in my original post:  Use Shannon's natural
laws to build a better PCT model of coordination among independent
systems acting in an environment where conditions change in ways
the systems cannot predict.  Do that and let me interact with one
of the systems in real time, then I might change my mind.


Until later,

Tom Bourbon                             e-mail:
Magnetoencephalography Laboratory       TBOURBON@UTMBEACH.BITNET
Division of Neurosurgery, E-17          TBOURBON@BEACH.UTMB.EDU
University of Texas Medical Branch      PHONE  (409) 763-6325
Galveston, TX 77550                     FAX    (409) 762-9961
USA
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