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Not about simulating nature (was Re: [GP] MEP better than GEP)

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  • paulsnx2
    ... This is the heart of your last post. Stuff some words in my mouth, then argue with them. If it will help (but it isn t likely, given your apparent
    Message 1 of 45 , Jun 11, 2002
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      > Well, read the literature to see how the techniques have
      > been analysed and explored. The argument to which I am
      > responding is your assertion that close
      > modelling of nature is necessary.

      This is the heart of your last post. Stuff some words in
      my mouth, then argue with them.

      If it will help (but it isn't likely, given your apparent
      religious zeal to stomp out any discussion of biological
      mechanisms) I will restate my position:

      Where Biological systems address and resolve specific problems
      that both biological and computational systems share, there
      are likely to be mechansisms and algorithms that can be
      generalized and applied to computational systems.

      In that regard, I view genetic programming as a simulation of
      biological genetics. To take this statement and expand it
      into a call to simulatate every aspect of biological systems
      is a gross insult to logic.

      Anyone that knows anything about simulation will understand
      the levels of models that are possible. Sure, you can refine
      a model to such a complexity as to render the simulation totally
      useless. And even a very gross, simple simulation will often
      yield very useful results. But it is intellectually dishonest
      to claim that the later observation negates any need in
      the subject at hand to review the relationship between
      the simulations and the system.

      --Paul
    • Terry Soule
      Hi all, Gordon I can agree with your statement below: That [survival in a constraint environment]is not a goal, it is a tuatological outcome of the
      Message 45 of 45 , Jun 28, 2002
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        Hi all,

        Gordon I can agree with your statement below:
        "That [survival in a constraint environment]is not a goal, it is a
        tuatological outcome of the evolutionary process. Survivors, by definition,
        survive --- at least until the environment changes, and they go extinct,
        becoming non-survivors that by definition failed to survive."

        However, I would argue that this applies to our artificial evolutionary
        systems as well. The ability of an individual to meet the goal implicit in
        our imposed fitness function is a stong factor in survival. However, it is
        not the only factor determing an individual's (or more accurately their
        offspring's) chances of survival.

        The most obvious example is code growth. Put simply programs with more
        'introns' are less likely to be damaged by crossover and hence their
        offspring are less likely to have a fitness that is lower than their
        parents, a strong survival benefit. Thus, given two individuals one of
        which has a higher fitness, but fewer introns and the other of which has a
        lower fitness but more introns the offspring of the second individual are
        more likely to be seen in later generations. In this case survival trumps
        our imposed fitness function. Other similar examples exist.

        In artificial systems, just as in nature, survival is paramount. The 'goal'
        imposed by the fitness function is an important factor, but not the only
        factor in survival. In our evolutionary systems (just as in nature) all we
        see are the survivers, who may or may not have achived our imposed goal.

        Sincerely,
        Terry Soule
        Department of Computer Science
        University of Idaho
        Moscow, ID 82844
        tsoule@...

        -----Original Message-----
        From: pusch@... [mailto:pusch@...]On Behalf Of
        Gordon D. Pusch
        Sent: Thursday, June 27, 2002 12:40 PM
        To: genetic_programming@yahoogroups.com
        Subject: Re: Not about simulating nature (was Re: [GP] MEP better than
        GEP)


        > --- Martin Sewell <M.Sewell@...> wrote:
        > ...
        > >
        > > Evolution (e.g. Nature):
        > > A process without a goal.
        > > Stochastic process.
        > > No explicit fitness function.
        > ...
        >
        > Evolution has a goal, as simple as tough: survival in
        > a constraint environment.

        That is not a goal, it is a tuatological outcome of the evolutionary
        process.
        Survivors, by definition, survive --- at least until the environment
        changes,
        and they go extinct, becoming non-survivors that by definition failed to
        survive.
        There is nothing of ``purpose'' or ``goal'' in this process; it is merely a
        description of what happens --- and to talk of evolution as having a
        ``goal''
        is to commit a teleological fallacy.

        What we observe as ``evolution'' is simply the result of a random series of
        pointless ``Red Queen's races'' --- positive feedback loops chasing their
        own
        tails, because they are all that is left after the negative feedback loops
        have damped out. There is no ``goal'' to it --- it simply *is*.


        -- Gordon D. Pusch

        perl -e '$_ = "gdpusch\@...\n"; s/NO\.//; s/SPAM\.//; print;'


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