From welsberr Mon Oct 9 11:38:11 2000
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Date: Mon, 9 Oct 2000 11:38:11 -0500 (CDT)
From: "Wesley R. Elsberry"
Message-Id: <200010091638.e99GcBg25785@inia.cls.org>
To: dembski@discovery.org
Subject: Information request re: Dawkins' "weasel" algorithm
Cc: evolution@calvin.edu, welsberr
Information request to William Dembski:
[Quote]
He starts with a target sequence taken from Shakespeares
Hamlet, namely, METHINKS IT IS LIKE A WEASEL. If we tried to
attain this sequence by pure chance (for example, by randomly
shaking out scrabble pieces), the probability of getting it on
the first try would be around 1 in 10^40, and correspondingly
it would take on average about 10^40 tries to stand a better
than even chance of getting it.12 Thus, if we depended on pure
chance to attain this target sequence, we would in all
likelihood be unsuccessful. As a problem for pure chance,
attaining Dawkinss target sequence is an exercise in
generating specified complexity, and it becomes clear that
pure chance simply is not up to the task.
But consider next Dawkins' reframing of the problem. In place
of pure chance, he considers the following evolutionary
algorithm: (1) Start with a randomly selected sequence of 28
capital Roman letters and spaces (thats the length of METHINKS
IT IS LIKE A WEASEL); (2) randomly alter all the letters and
spaces in the current sequence that do not agree with the
target sequence; (3) whenever an alteration happens to match a
corresponding letter in the target sequence, leave it and
randomly alter only those remaining letters that still differ
from the target sequence. In very short order this algorithm
converges to Dawkinss target sequence. In The Blind
Watchmaker, Dawkins recounts a computer simulation of this
algorithm that converges in 43 steps.13 In place of 10^40
tries on average for pure chance to generate the target
sequence, it now takes on average only 40 tries to generate it
via an evolutionary algorithm.
[End Quote - WA Dembski, "Can Evolutionary Algorithms Generate
Specified Complexity", "Nature of Nature" conference, Baylor
University]
There are several issues that this text brings up. Of the three
steps listed as comprising Dawkins' algorithm, only step (1) has
anything like it in the pages of "The Blind Watchmaker". Steps
(2) and (3) appear to be inventions rather than descriptions.
What is the basis for claiming that steps (2) and (3) represent
Dawkins' "weasel" algorithm?
Further on, the issue of "tries" it takes to find a solution
is raised. For "pure chance", a figure of ~10^40 "tries" is
given, which would correspond to individual candidate
solutions tested. For "weasel", though, only ~40 "tries" are
given, but in this case the number 40 derives from the number
of generations taken by the "weasel" algorithm rather than the
number of candidate solutions examined. It seems to me that
for the purpose of comparison, a "try" ought to mean the same
thing for both approaches. I would like to see a restatement
of the section concerning "tries" that takes this into
account.
Wesley
cc: Calvin Reflector, evolution@calvin.edu