>> From: Brian D Harper [mailto:email@example.com]
>> I'm glad to see that you accept results of computer simulations.
>Of course. Without human input, a computer program is just a structure
>where natural forces duke it out. Getting a computer to print "hello" is
>just as natural as dropping a rock and watching it fall.
>> Perhaps the best (or at least best known) simulation of Darwinian
>> evolution is Tom Ray's Tierra World. For a summary I invite you
>> to point your web browser at:
>Several years ago I downloaded and tried to compile the Tierra project, but
>I didn't have much luck.
>The quote you provided talks about a creature with a genome of size 36 from
>a parent of genome size 80 (after millions/billions of generations). I
>won't dispute that nature can optimize, simply, and destroy complexity
We're still lacking a definition of complexity from your point
of view. May I assume from the above that part of your definition
of complexity is sub-optimality and an increase in complexity is
a decrease in optimality?
>that small creature still have the creator-given ability to read from other
>genomes?). And, I'll wager that's what you'd see if you could compare the
>original parent with the size 36 creature. The last creature may have do
>things a little differently because of changes to its code, but it certainly
>doesn't do any new kinds of things.
According to Tom Ray it actually does do new kinds of things.
If you want a really good yet enormously simple example of
doing new things you can try Langton's ant. Here there are
very simple deterministic laws for what an "ant" can do.
Imagine a screen composed of simply white and black dots.
As the "ant" moves around this screen it follows two
simple rules: (1) if it lands on a black spot it changes
it to white and then turns left (2) if it lands on a
white spot it changes it black and turns right. One would
expect that such behavior would just result in chaotic
jostling of the ant around the screen and indeed this is
what happens for awhile. But eventually the ant will
start to display a very organized behavior where it actually
constructs a pattern which looks very much like a bridge.
The bridge description is very apt for another reason in
that it allows the ant to move slowly in a preferential
direction eventually going off the screen. The actual
bridges formed may be elaborate or very simple depending
on the initial conditions. Yet, even though the rules are
exceedingly simple, no one can predict (mathematicians
have spent a lot of time trying) what kind of bridge
will form nor can they even predict *whether* a bridge
Oh, I almost forgot. Here we're talking about simulations
but Ami was kind enough to remind us about real mechanism
for increasing complexity. See details in my response to
her post. Using a precise definition of complexity from
algorithmic information we can establish beyond any doubt
that complexity increases. Any comments?
>Without regard to the prize creature of the size 36 genome, but about all
>the creatures. There's no real competition between them, thus no way to
>test fitness. Creatures die only by failing to copy legal code some
>arbitrary number of times. Thus, the result is brute force with no concern
>for non-viable (unfit) stages (e.g. if the creatures were furniture, there
>would be no problem with a chair having only two legs on the path to
>becoming a legless seat). The brute force technique also means that there's
>no appreciation of whatever complexity that might appear by luck (brute
>force, any combination of instructions will eventually be reached --
>millions of mutations to a genome that started and ended in the double-digit
>genome size is the example from what you quoted), so whatever comes along
>can go just as easily (ie., put it in an environment where it will be tested
>for fitness and see how fast it's destroyed, like a sandcastle on a beach).
>Brute force doesn't demonstrate that nature has any creative ability.
I hope you won't take this the wrong way :), but the above
description of Tierra World is just wrong.
>>Not only does this show an example of increasing complexity
>>arising from "random bit flips", the final result is also
>>irreducible: "...as every component of the code must be in
>>place in order for the algorithm to function."
>Because this minimal size code "evolved" down, not up, being irreducible
>isn't a problem (and neither is non-viable intermediate steps, see above).
What do you mean by evolving down? BTW, you are the one who says
evolution *has* to go toward increasing complexity. Whether
down or up (whatever that means) it is still evolution.
If by down you mean simpler then this is incorrect unless of
course part of your definition of complexity is shorter=simpler.
Let's recall, however, what Ray said "...it has packed a much
more complex algorithm into less than half the space". According
to Ray, it is both shorter *and* more complex.
>The issue is how the creature's required functions formed in the first
>place -- it was directly created by an intelligent programmer (the program
>didn't create the individual functions).
Once again this is incorrect according to what Tom Ray wrote. The
optimization technique "unrolling the loop" was *discovered*.
>And, it again took an intelligent
>programmer to appreciate the size 36 genome (i.e. this creature was no more
>successful than any other).
It was more successful than those that died.
>Actually, there is a very crude fitness test provided by a program and I bet
>dollars to donuts that the size 36 creature would be judged highly unfit.
>Because it's irreducible, there's a high probability that "mutations" will
>create illegal or non-reproducing code making it quickly win the race for
Well, the "organisms" passed this test.
>Any attempt to demonstrate evolution on a computer results in either garbage
>or simplification. The Terria, underneath all the smoke and mirrors, is
>just another demonstration that nature doesn't create complexity.
Talk about smoke and mirrors .............. ;-)
The Ohio State University
"All kinds of private metaphysics and theology have
grown like weeds in the garden of thermodynamics"
-- E. H. Hiebert