[Haskell-cafe] [Haskell] ANNOUNCE: genprog-0.1
Alberto G. Corona
agocorona at gmail.com
Wed Dec 8 16:51:32 CET 2010
2010/12/8 Mitar <mmitar at gmail.com>
> On Wed, Dec 8, 2010 at 3:39 PM, Alberto G. Corona <agocorona at gmail.com>
> > DNK? I think you mean DNA.
> Sorry. In my native language it is DNK. ;-)
> > the genotype program that develips the fenotype is much more smooth and
> > granular than a computer program. A chante un a gen does not make you to
> > have a extra bone. It can make you to have your hand slighltly longer. or
> > shorter.
> Because we are using very small programs. A change of one constant in
> a Linux kernel would also be a very small change in general. Maybe
> some esoteric device would not function anymore, but this is it. Of
> course there would be also changes which would make whole kernel
> Of course there are smooth zones in the fitness landscape of any code. what
is necessary is to direct the process by avoiding absurd replacements
(mutations that goes straight to dead zones) and rules for changing from a
smooth to another smooth area once the local maximum is not satisfactory. Or
to detect them as early as possible (that is, rules again). That is what I
> > In fact there are metalevels of selection that discard abrupt changes.
> > example, when females ovulate there are a strong selection where
> > of candidate cell ovules are tested and discarded. This is one of the
> > reasons why anomalous mutations are scarce.
> I doubt that. Aren't female eggs made while she is still a fetus? And
> they do not divide anymore later on?
This selection of candidate eggs happens each month within each ovulation
period. It is mentioned in this superb conference series by Yale university.
It is a very good introduction. I don´t remember the exact chapter. sorry:
Moreover, the genetic code has evolved to evolve. For many reasons. Neither
Haskell nor any conventional language has. One of the safety measures of the
genetic code is protectin itself against undesired mutations. This is
something vital for life. Cancer is one consequence. but another
consequences are more deadly: If a mother spend nine months to produce an
unfit child this is a dead end for the mother´s genome line. For this
reason, undesired mutations, specially in reproductive cells are either
repaired or discarded. This selection is more strong in females than in
males (for investment reasons) .
The rate of mutations in living beings is equal to the theorical optimum for
procariots and eucariouts. This is another examople of how finely tuned the
DNA has evolved for evolution. The molecular bonds are strong enough just to
permit the right rate of mutation . But the DNA i´m sure, has much more
secrets to learn and discover.
So in conclusion there are much details to learn and to implement to have
sucessful general genetic algorithms for genetic programming. But the
research promises a lot of fun.
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