[FRIAM] goal/function/robots

[Eric Charles]

" As soon as the machine produces the outcome we desire, we stop designing."

Oddly, in this crowd that is not true at all. Computer programming is
largely an effort to increase efficiency in things that already do what we
want them to do.  Whole areas of computer science are dedicated to
determining the theoretical limits of efficiency at tasks that are easy to
program. Search optimization and list sorting might be the most obvious
contexts for this, but a lot of agent based modeling is focused in this
direction as well.

There are MANY projects I work on where I write a program that does a task
in whatever way I think is easiest to write, and then spend 10 times longer
rewriting to do the task in some other way (usually to run more quickly,
but other times for the aesthetic pleasure of seeing the code get more
"elegant").



-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
<echarles at american.edu>


On Fri, Jul 24, 2020 at 6:06 PM <thompnickson2 at gmail.com> wrote:

> Here’s the example I was trying to lay out for the zFriam Leftovers when
> my house got flooded. It concerns simple robots, “didabots”, that if
> unleashed in a room full of randomly placed Styrofoam cubes, will tidy up
> the room by herding the cubes into clusters.
>
>
>
> http://www.verena-hafner.de/teaching/didabots.pdf
>
>
>
> Here is what Louise Barrett’s BEYOND THE BRAIN says about the example:
>
>
>
> It should be clear that this “clustering” is not the “goal” of the
> individual didabots … .  Clustering is an emergent property (=consequence?)
> … this complex behavior is produced, not only by a very simple mechanism,
> but also by a mechanism that bears absolutely no relation to the behavioral
> outcome produced when that mechanism operates in the real world…. .  Poking
> around inside a didabot to identify the nature of this mechanism won’t tell
> us anything about didabot [herding] behavior because it makes sense only
> after we have taken into account the interaction of the internal mechanisms
> with the physical structure of the didabot and the structure of the
> environment. (p49)
>
>
>
> It seems to me that understanding the distinction between goal and
> function, we have to look at the same behavior, simultaneously from two
> different points of view.   The first is what outcome the behavor is
> directed toward (avoiding obstacles on the side) and the outcome robot
> (organism) has been designed to produce (the herding of the blocks) within
> its
> ecological” context.  The seagull is a robot whose goal is to remove shiny
> things from the nest;  natural selection has designed that seagull  so that
> it avoids predation by vision-using predators. That this behavior
> constitutes a design is demonstrated by widening the lens still further and
> showing that shell removal is characteritic of surface nesting gulls but
> NOT of the closely related kitiwake gulls which nest on cliffs that ground
> searching predators cannot reach.
>
>
>
> This is an old story that has no doubt been altered by time, but the logic
> of attribution of goal, selection mechanism, and design remains the same.
>
>
>
> It is these sorts of examples that lead me to think that the decoupling
> between goal and function or design is an essential feature of control
> systems generally.  Designers, human and natural, are all the same.  As
> soon as the machine produces the outcome we desire, we stop designing.
>
>
>
> Nick
>
>
>
> Nick
>
>
>
> *Nicholas Thompson*
>
> *Emeritus Professor of* Ethology and Psychology
>
> Clark University
>
> ThompNickSon2 at gmail.com
>
> https://wordpress.clarku.edu/nthompson/
>
>
>
>
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