On Sun, 06 Oct 1996 14:44:29, Glenn Morton wrote:
GM>Which is a better design technique, rational design or random
>evolution? Creationists often cite the supposed inability of random
>mutation to create new information and its inability to perform
>better than a human designer.
Sorry, but one thing that "random mutation" cannot do is to "create
new information":
"Darwinian transformism demands spontaneously increasing genetic
information. The information on the chromosomes of the primitive
cell must become greater for the primeval cell to become a human one.
Just as mere molecular movements are incapable of producing
information de novo (they can modify already existing information),
neither can they produce new information, as will be shown in the
text later. NeoDarwinian theory does not enlighten us as to how a
primeval cell can energetically finance the production of new
information, so that it becomes a higher plant or a higher animal
cell. Transformism demands a very large increase in information, the
principle behind which Neo-Darwinian thought is incapable of
explaining." (Wilder-Smith, A.E., "The Natural Sciences Know Nothing
of Evolution", T.W.F.T. Publishers: Costa Mesa CA, 1981, p.vi)
GM>A.E. Wilder-Smith wrote: "...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...."~A. E. Wilder-Smith, The
>Natural Sciences Know Nothing of Evolution, (San Diego: Master
>Books, 1981), p. 65)
In my copy of Wilder-Smith's book this is at p72.
Wilder-Smith does admit that intelligence can be programmed into
machines:
"...Computer scientists are actively working on the problem of
artificial intelligence and have already thrown a good deal of light
on some of the basic functions of the biological nervous system.
Computer science has widely succeeded in electronically simulating
the biological nervous system. Although the mechanism by which a
suitable computer achieves its artificial intelligence is different
from that by which the brain achieves its intelligence, yet the end
results are in some cases very similar, as we shall see later. It is
important to realize that processes which simulate human thought are
no longer bound to biological nervous tissue and oxyhemoglobin. They
can ride on entirely inorganic electrical systems. For the first
time in history, intelligence has been experimentally separated from
biology. Artificial intelligence, created by man, is riding on
entirely inorganic systems of an apparently impersonal nature."
(Wilder-Smith, A.E., "The Creation of Life: A Cybernetic Approach to
Evolution", T.W.F.T. Publishers: Costa Mesa CA, 1988, p.xxvi)
GM>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.
Note: "guided the evolution of a program".
GM>"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.
Note: "To create their software..."
GM>"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.
Rather a downer on "blind-watchmaker" Neo-Darwinism, I would have
thought! :-)
GM>"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
And this too! :-)
GM>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.
Agreed. Wilder-Smith's "The Creation of Life" covers this point well.
But as to "the evolved programs were better than the intentionally
designed programs" the above does not say it. Berlinski points out
regarding other "evolved programs":
"Citing with satisfaction the work of John Koza ("Genetic
Programming: A Paradigm for Genetically Breeding Populations of
Computer Programs to Solve Problems," Technical Report STAN-
CS-901314, Department of Computer Science, Stanford University), Mr.
Wessel would argue that genetic algorithms embody the abstract
properties of robustness in the face of randomness that I claim could
not be a feature of livings systems. In fact, I made no such claim.
As their name suggests, genetic algorithms are structures designed to
incorporate (or mimic) certain biological operations. Typically,
strings or sets of strings are introduced as fundamental data
structures and manipulated by operators that reproduce the effects of
random variation, genetic crossing, and natural selection. Work in
this area was initiated in the 1970's by John Holland in Adaptation
in Natural and Artificial Systems.
Mr. Wessel's claim that "[m]any of these evolved programs perform
their optimizing tasks better than the best intentionally designed ones"
is surely not incontrovertible; some computer groups argue that
genetic algorithms do not outperform hill-climbing algorithms
(Proceedings of the Second International Conference on Genetic
Algorithms and Their Applications, ed. J.J. Grefenstette, 1987). But
let that pass. I do not for a moment deny the possibility that a
controlled random search might be an effective way in which to
explore a large space. In referring to the Face Print algorithm in my
essay, I said as much. What is at issue is the nature of the controls.
The Face Print algorithm may be a fine method for prompting a crime
victim's memory; It may, in fact, be far superior to traditional
methods in which the victim offers a police artist a description of the
malefactor (Uh, let me see, big nose, yes, it was a big nose, I think,
but no, not that big...); but the algorithm fails to capture an essential
feature of a Darwinian mechanism, for fitness is evaluated in terms of
an ever-progressing match between what the algorithm produces and
what the crime victim remembers, with the crime victim's memory
functioning as-once again-a forbidden design or template.
The larger question posed by genetic algorithms is whether they can
reach any interesting lifelike structures. Although genetic algorithms
are new, they make use of an old mathematical concept, a Markov
chain. It is worth noting that mathematical models based on Markov
chains cannot in principle generate the sentences of a natural
language. This is something known since the 1950's; I offer it as an
observation....I am unimpressed by computer models demonstrating
punctuated equilibrium, whether elegantly or not. A typical problem
in applied mathematics is to discover an equation that will describe
a set of data points. A good deal depends on what the mathematician
permits himself. As Enrico Fermi noted long ago, with five free
parameters, an equation may be made to represent data points
resembling an elephant So, too, with computer models."
(Berlinski D., "Denying Darwin: David Berlinski and Critics",
Commentary, September 1996, pp31-33)
GM>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.
Yes, this is intelligent design, not Neo-Darwinian,
"blind-watchmaker" evolution.
GM>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.
This is not so strange as it may seem. Having lots of brain-power is
not necessarily a help in solving some problems. I remember when I
studied psychology, being amazed when the lecturer said that rats
can solve some maze problems as fast as a human being.
GM>"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
This is (as usual) a play on the word "evolution". That a human
intelligent designer (or a divine Intelligent Designer) could design
"software" that could in turn produce "hardware" by an pre-programmed
"genetic programming system" that might beat a human designer, is not
controversial. What "blind watchmaker" evolution claims is that there
is *no* intelligent design anywhere in the process:
"All appearances to the contrary, the only watchmaker in nature is
the blind forces of physics, albeit deployed in a very special way.
A true watchmaker has foresight: he designs his cogs and springs,
and plans their interconnections, with a future purpose in his mind's
eye. Natural selection, the blind, unconscious, automatic process
which Darwin discovered, and which we now know is the explanation for
the existence and apparently purposeful form of all life, has no
purpose in mind. It has no mind and no mind's eye. It does not plan
for the future. It has no vision, no foresight, no sight at all. If
it can be said to play the role of watchmaker in nature, it is the
blind watchmaker." (Dawkins R., "The Blind Watchmaker", Penguin:
London, 1991, p5)
GM>Christians should be aware that design via evolution is a coming
>field.
Watch out Bill! General Motors cars will in the future be designed
by a random algorithm, not by engineers. In fact some would say they
already were! :-) (Bill knows that I drive a 1980 General Motors
Commodore which I have owned since 1986).
What this really demonstrates (yet again) is what a vacuous, delusory
word "evolution" has become. When "evolution" (which is usually
claimed to be the very antithesis of "design"), can be coupled
together to produce "design via evolution", it shows that the word
"evolution" has no real meaningful content anymore:
"Similarly for neo-Darwinism, `with a little ingenuity any
observation can be made to appear consistent with it," Saunders and
Ho conclude. Even Mayr admitted that `Popper is right; this model is
so good that it can explain anything, as Popper has rightly
complained.' Gould has compared it `to the "Blob," of movie fame,'
in that `it could be manipulated to account for all data in its
path,' "" ref. p2:144 (Bird W. R., "The Origin of Species Revisited",
Vol. II, Regency: Nashville, 1991, p89)
God bless.
Steve
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