The von Neumann architecture for self-reproduction is based on
the idea of a `general constructive automaton''. I will denote
(an example of) such an automaton by .
is, in effect,
a programmable constucting machine. In a manner reminiscent of a
turing machine, if a ``tape'',
, is attached to
then
will interpret this tape as a description of some other
machine, which
is intended to construct. We require that
should also copy the attached description tape (and
attach this copy in turn to the constructed machine). We assume
that
is capable of successfully constructing a wide range
of such target machines (this is why it is termed a
general or programmable constuctive automaton). Let
denote a tape describing target machine
(relative to
the decoding conventions, or genetic language, realised by
). We then write:
Assuming that the set of machines that
can construct
includes
itself, it follows that:
This is the essential structure for a single self-reproducing
automaton which has been commonly identified as von Neumann's
``result''. But such an interpretation
seriously understates the true depth of von
Neumann's work. It completely misses the single most significant
aspect of this particular architecture, namely that this
core design in turn implies the existence of a whole infinite set
of general constructive automata which incorporate as a
subsystem:
With some limited assumptions about the interactions of and
the ``ancillary'' machinery
, it follows that there is an
infinite set of self-reproducing automata of the form:
It turns out that the elements of this set are connected by a
network of potential mutations (interpreted simply as
spontaneous perturbations of the description tape). Which means
that there are evolutionary pathways linking the simplest element
of this set (
) with arbitrarily complex
elements. Exhibiting the detailed design of a particular
in
a particular framework (which is what von Neumann actually did)
thus leads directly to an effective solution to von Neumann's
problem of the evolutionary growth of machine
complexity.1
Copyright © 2000 All Rights Reserved.
Timestamp: 2000-08-16