Re: [asa] Parameterized Evolution

On Sat, Aug 23, 2008 at 5:18 PM, Rich Blinne <rich.blinne@gmail.com> wrote:

>
> On Aug 23, 2008, at 8:29 AM, Dave Wallace wrote:
>
>
>> http://www.uncommondescent.com/biology/thoughts-on-parameterized-vs-open-ended-evolution-and-the-production-of-variability/
>>
>> I found this post on UcD somewhat interesting however, I have only a vague
>> idea as to what Parameterized Evolution is. Can anyone point to a simple
>> definition. As best I can tell it involves a predetermination/limitation of
>> biological evolutionary search space.
>> Dave W (ASA member)
>>
>
> The reason why engineers are more prone to recognize this is because
>> engineers have to develop systems repeatedly, and know how much trouble it
>> is to get parts to play well together. Adjusting the system requires
>> adjusting multiple parts simultaneously, which can't be accomplished without
>> a guiding information system (which, in ID circles, is termed front-loaded
>> evolution - which requires the action of an intelligent agent at the
>> beginning) or the creativity and intervention of an intelligent agent at
>> each step.
>>
>
> This is such utter B.S. Speaking as an engineer, they don't have a clue on
> how it works. If you change everything simultaneously you get chaos. Rather,
> you make small revisions to working designs.

I don't think it's complete B.S. - in fact I originally thought that your
statement about changing everything simultaneously leading to chaos was also
utter B.S., though I think I can see where you're coming from, and it's not
the same place as the ID'er is coming from. I think ID folk tend to see
evolution as a bit like the mathematical problem of trying to optimize an
objective function of multiple variables, to find the correct combination.
The final value of the objective function (which in a genetic algorithm
would be the "fitness function") is dependent simultaneously on all the
variables. Whether or not the problem can be solved by a genetic algorithm
depends entirely on how tightly the variables are coupled together. For
most of the problems I've worked on ( optimisation of weights in a neural
network; optimisation of large chemical plants) the variables are always
highly coupled. So the approach to take is to compute the gradient vector
of the objective function with respect to all the variables that are to be
tuned; then you make small steps in the direction of the gradient vector
(or in a search direction based on the gradient vector, as in Conjugate
Gradients or Quasi-Newton methods). In general most of the elements of the
gradient vector are going to be non-zero, and hence you do indeed change
everything simultaneously, and it does not lead to chaos, but allows the
solution to be found in an iterative fashion. By contrast, if you vary one
variable at a time, in turns, then you get an absolutely useless
optimisation algorithm, unless the variables are decoupled. For example if
you are trying to find the minimum of x^2 + y^2 + z^2 then the variables are
decoupled, and you can change one at a time. But if you had xy + yz + zx
then you could not.

I think that is where the ID people are coming from; possibly influenced by
misleading metaphors such as Dawkins's "Climbing Mount Improbable". I know
this too, because I was misled by this analogy, and could easily see that
such problems weren't easily soluble via a classical genetic algorithm. It
was the main reason why I was attracted to ID originally - essentially the
notion of "Irreducible Complexity" explained clearly to my why genetic
algorithms (of the classical type of optimising parameter sets derived from
mutating, and naturally selected bit strings), had so few examples where
they worked. [ I now think whole "hill climbing" analogy is quite false -
for a start the peak of the hill doesn't always stay in the same place!]

However, I think you are looking at it from a different perspective; you
start with a good working design - one of the hallmarks of which is going to
be modularity - it would be designed so that you could indeed change small
bits without affecting the others. In such a case, you are indeed right in
suggesting that changing everything at once would be chaotic.

Iain

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Received on Sat Aug 23 14:43:12 2008