Re: [asa] Parameterized Evolution

On Mon, Aug 25, 2008 at 9:12 AM, Randy Isaac <randyisaac@comcast.net> wrote:

> This is an interesting and valuable discussion, I think. Could some of
> you comment on how this applies to specific observations? I'm particularly
> thinking of the all-too-common arguments along the lines of "there must be a
> designer because abc is so well tuned" or "there can't be a designer because
> xyz isn't optimized." Neither path seems reasonable to me but these
> arguments continue.
>

These arguments do indeed get tiresome. There are at least two responses to
them. One is that if optimization is being carried out by a designer (God
IMO) we don't know what criterion He is optimizing, nor do we know all the
variables He is perturbing to achieve the optimization. Suppose God is
optimizing all of nature for example. The second is, as Rich and others have
pointed out, evolution is not optimization. It is simply a process that
finds solutions that are good enough to ensure survival. It seems to me that
the real design in nature consists of designing enough variability into
living organisms to enable populations of them to adapt to changing
environmental conditions.

There are many specific examples but I'm especially intrigued by the
> trade-off examples. For instance:
>
> 1. genetic anomaly in which having one copy protects from malaria but two
> copies leads to sickle cell anemia
> 2. juxtaposition of the larynx and the pharynx which occurs uniquely in
> humans, enabling speech on one hand but inducing susceptibility to choking
> on the other
> 3. relative position of the retinal cells and optical nerves in the human
> eye
>

I'm not an expert on any of these subjects. However, look at how the human
brain deals with the blind spot caused by thye topoloogy fo the optic nerve.
You need to do a special exercise to be able to detect the blind spot. Yes,
we have the blind spot, but our brains have adapted beautifully to its
presence -- and perhaps the presence of the blind spot has contributed to
the evolution of the brain to carry out such wonderful processing tricks.

>
> Are these examples of local minima as opposed to optimized states? What are
> some others?
>
> It is often assumed in discussions that a particular feature in a species
> exists because it has proven to be successful through a long period of
> evolutionary development. How can one tell whether a feature is a local
> minimum or an optimized state? Does it really matter?
>
>
I don't think you can tell. In fact I suspect that few if any features of
living creatures are optimal, for the simple reason that the environment
changes and the creatures have to evolve to track it. Any solution that is
in some neighborhood of the previous solution and works is going to be good
enough. My 2 cents worth.

>
>
>
Randy
>
> Iain wrote:
>
>
>
>
>> I am actually quite sceptical about the ability of genetic algorithms to
>> avoid local minima. They often exhibit a phenomenon called "premature
>> convergence" where the entire population is clustered around the local
>> minimum. Now although the GA has the ability to make large jumps via
>> crossovers, in a high dimensional space it is extremely unlikely that a big
>> jump will increase the fitness. This is due to a well known problem called
>> "the curse of dimension" ie the exponential increase in the volume of the
>> search space with dimension.
>>
>

-- 
William E (Bill) Hamilton Jr., Ph.D.
Member American Scientific Affiliation
Rochester, MI/Austin, TX
248 821 8156
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