Information Technology Reference
In-Depth Information
with a number of heavy beads on it, the beads being joined together by elastic
strands to form an irregular network.” We are invited to think of the positions
and velocities of the beads as the variables which characterize the evolution of
this system in time, and we are invited also to pay attention to “the constants
of the network: the masses of the beads, the lengths of the strands, their ar-
rangement, etc. . . . These constants are the 'organization' [of the machine] by
definition. Any change of them would mean, really, a different network, and
a change of organization.” And it is important to note that in Ashby's concep-
tion the “constants” can change; the elastic breaks if stretched too far (Ashby
1945a, 15-16).
11
The essay then focuses on the properties of this machine. Suppose we start
it by grabbing one of the beads, pulling it against the elastic, and letting go;
what will happen? There are two possibilities. One is that the whole system
of beads and elastic will twang around happily, eventually coming to a stop.
In that case we can say that the system is in a state of dynamic equilibrium, as
defined in the 1940 essay, at least in relation to the initial pull. The system is
already adapted, as one might say, to that kind of pull; it can cope with it.
But now comes the clever move, which required Ashby's odd conception
of this machine in the first place. After we let go of the bead and everything
starts to twang around, one of the strands of elastic might get stretched too
far and break. On the above definition, the machine would thus change to
a different state of organization, in which it might again be either stable or
unstable. In the latter case, more strands would break, and more changes of
organization would take place. And, Ashby observed, this process can con-
tinue indefinitely (given enough beads and elastic) until the machine reaches
a condition of stable equilibrium, when the process will stop. None of the
individual breaks are “adaptive” in the sense of necessarily leading to equilib-
rium; they might just as well lead to new unstable organizations. In this sense,
they are
random
—a kind of nonvolitional trial-and-error process on the part of
the machine. Nevertheless, the machine is
ultrastable
—a technical term that
Ashby subsequently introduced—inasmuch as it tends inexorably to stable
equilibrium and a state of adaptedness to the kinds of pull that initially set it
in motion. “The machine finds this organization automatically if it is allowed
to break freely” (1945a, 18).
Here, then, Ashby had gone beyond his earlier conception of a servo-
mechanism as a model for an adaptive system. He had found the solution to
the question of how a machine might become a servo relative to a particular
stimulus, how it could learn to cope with its environment, just as the burned
kitten learns to avoid the fire. He had thus arrived at a far more sophisti-
