A.E. Wilder-Smith wrote:
"Thus Neodarwinian thought requires basically the prebiotic
autoorganization of raw matter (which the second law categorically
excludes), the creation of information by random deviations (which
information theory categorically forbids), the encoding of
information by chance (without the help of exogenous code
conventions), the storage of information by chance and its
retrieval also by chance. The Darwinian hypothesis sets out to
explain the origin and the replication of a biological organism (a
super machine), immensely more complex than a modern automobile, by
means of random deviations. If we were to accept such an
hypothesis, we would have to be willing to in principle to accept
the origin and the development of any other teleonomic machines
solely exclusively by means of the molecular deviations of iron
molecules and by selection on the car market in the game of supply
and demand, but without the aid of any teleonomic construction
mechanisms, blueprints, or concepts.
"According to this scheme, competition plus chance would
suffice to explain the development and origin of all cars. Thus
engineers, machines, and workshops would no longer be required to
produce cars."~A. E. Wilder-Smith, The Natural Sciences Know
Nothing of Evolution, (San Diego: Master Books, 1981), p. 65
Maybe engineers are on their way out. Below is an excerpt from this month's
Scientific American:
"Brian Howley of Lockheed Martin Missiles and Space
guided the evolution of a program that can figure out
how to maneuver a spacecraft from one orientation to
another within 2 percent of the theoretical minimum
time--10 percent faster than a solution hand-crafted by
an expert. And researchers at University College in
Cork, Ireland, grew a system that can convert regular
programs, which execute instructions one at a time, into
parallel programs that carry out some instructions
simultaneously.
"To create their software, Fernandez and Howley did
not have to divine insights into neurophysiology or
rocket science. The task of the genetic programmer is
simpler. First, build an environment that rewards
programs that are faster, more accurate or better by
some other measure. Second, create a population of
seed programs by randomly combining elements from a
"gene pool" of appropriate functions and program
statements. Then sit back and let evolution take its
course. Artificial selection works just like the natural
variety: each program is fed data and then run until it
halts or produces a result. The worst performers in each
generation are deleted, whereas the best reproduce and
breed--that is, swap chunks of code with other
attractive programs. Occasionally, a random mutation
changes a variable here or adds a command there.
"The technique can generate solutions even when the
programmers know little about the problem. But there is
a price: the evolved code can be as messy and
inscrutable as a squashed bug. Fernandez's
gesture-predicting program consists of a single line so
long that it fills an entire page and contains hundreds of
nested parenthetical expressions. It reveals nothing
about why the thumb moves a certain way--only that it
does.
"Just as in the real world, evolution is not necessarily the
fastest process either. Howley's speedy workstation
churned for 83 hours to produce a satellite-control
program that beat human ingenuity in eight test cases.
And when it was presented with situations it had never
encountered, the program failed, a common problem
with evolved software. (Of course, the human expert's
program failed on the new cases as well.)"~W. Wayt Gibbs, "Programming with
Primordial Ooze", Scientific American cot 1996, pp 48-50
Notice that the evolved programs were better than the intentionally designed
programs. The interesting thing to me is that in a real sense both types of
programs are designed. The traditional algorithm is well thought out by an
intelligent agent with each part intricately designed. The other is designed
by designing an environment in which solutions to various problems can be
found via random mutation. Design can take several forms. It does not have
to be the traditional form of design.
For those who have been on the reflector for a couple of years, you will
remember those programs I offered to demonstrate this process. My program
would mutate itself at certain locations and a huge, almost infinite variety
of screen shapes (which I likened to species) could be generated by that
process. I designed the system, the environment which produces these
pictures. Because I chose which mathematical system to place into the
computer, I therefore, also designed each and every picture.
Wayt concludes his article with a more interesting example. Evolving
hardware:
"Ultimately, evolved software may lead to evolved
hardware, thanks to the recent invention of circuit
boards that can reconstruct their circuit designs under
software control. Adrian Thompson of the University of
Sussex turned a genetic programming system loose on
one such board to see whether it could produce a
circuit to decode a binary signal sent over an analog
telephone line. Using just 100 switches on the board,
the system came up with a near-perfect solution after
3,500 generations. Although the task is simple, "it
would be difficult for a designer to solve this problem in
such a small area and with no external components,"
Thompson says.
"Hardware evolution demands a radical rethink of what
electronic circuits can be," he argues, because evolution
exploits the idiosyncratic behavior that electrical
engineers try to avoid. Although genetic programs are
largely still fermenting in their primordial ooze, it seems
just a matter of time until they crawl out to find their
niche."~W. Wayt Gibbs, "Programming with
Primordial Ooze", Scientific American cot 1996, p 50
Christians should be aware that design via evolution is a coming field.
glenn
Foundation,Fall and Flood
http://members.gnn.com/GRMorton/dmd.htm