[...]
WRE>A population size of 100 and mutation rate of 6% seems to
WRE>provide similar results to those reported by Dawkins.
SJ>This "mutation rate of 6%" seems to agree with one of ReMine's
SJ>criticisms of Dawkins "Methinks it is like a weasel" simulation
SJ>that has an unrealistically high mutation rate:
SJ>"Dawkins did not say, but he must have chosen the mutation rate
SJ>to optimize the speed of evolution. If he had chosen a low
SJ>mutation rate, (such as 10^-8 as in humans) then the simulation
SJ>would require roughly 50 million generations. On the other
SJ>hand, if he had chosen too high a mutation rate, then it would
SJ>cause error catastrophe and the target phrase would never be
SJ>reached. Dawkins picked the mutation rate that produced the
SJ>fastest evolution." (ReMine W.J., "The Biotic Message", 1993,
SJ>p233)
If Dawkins' purpose had been to simulate human evolution
accurately, then you might have had a point. However, Dawkins
makes clear in "The Blind Watchmaker" that a strict analogy
with biology was not his intent for the "weasel" demo. I
suggest that you fire up Interlibrary Loan.
WE>The executable is available via anonymous ftp at
>inia.tamug.tamu.edu in the pub directory as "weasel00.exe".
>
>I think that I can easily demonstrate an interest in the "live"
>issue of test by computer simulation.
SJ>The question is whether it is a realistic "simulation" of the
SJ>biological world.
No, it is not. Read, or better yet buy, the book.
SJ>If Dawkins' simulations really did simulate
SJ>real-world evolution, they would be included in every biology
SJ>book, but they are simply ignored.
If cucumbers had anti-gravity, sunsets would be more interesting.
Dawkins' purpose for the "weasel" demo was to show the relative
advantage of a genetic search over a random search. It does
that quite well.
SJ>The following are some criticisms of Dawkins' "weasel"
SJ>simulation from non-Darwinists (apart from ReMine):
SJ>Berlinski calls it "an achievement in self-deception" because
SJ>it uses "a target phrase":
Dawkins brings up this criticism himself on p. 50, so I hardly
see how Berlinski can call it "self-deception". Maybe
Berlinski just has reading comprehension problems.
[Berlinski's purple, though unresearched, prose deleted.]
[Further quotes trimmed]
William Dembski brought up essentially the same points that
Behe made in your quotes when Dembski was at the NTSE
conference. Dembski's analysis (and Behe's by extension) are
correct that when no information can be obtained from a
population, genetic algorithms are reduced to random search.
The assertion at issue there is whether biological search
spaces have such binary fitness landscapes. Dembski had
asserted that one could get non-complex information from random
search, but complex specified information appearing in
algorithms was either already inherent in the inputs or was
infused by intelligence. I challenged Dembski to explain where
information infusion occurred in a 500 city TSP tour solved by
genetic algorithm. The searchspace size eliminated
"non-complex" and the specification of the TSP eliminated
"non-specified", leaving only "infusion" as a means of getting
a good solution, according to Dembksi. Dembski responded that
operating systems and programs had intelligent authors, and
that one did not get information for free. Perhaps you can do
better.
Wesley