Re: [-empyre-] self-modification, emergence
----- Original Message -----
From: "Mitchell Whitelaw" <email@example.com>
To: "soft_skinned_space" <firstname.lastname@example.org>
Sent: Tuesday, November 09, 2004 12:31 AM
Subject: [-empyre-] self-modification, emergence
> I'm going to have a go at self-modifying this tangent back in the
> direction of a-life. Self-modification might also be thought of as
> adaptation, learning, innovation... and depending on your view of
> biology and what constitutes a "self" then you might also find it in
> evolution. Lamarckian evolution theorises adaptive self-modification
> which can be passed on to the next generation. While it's been
> overtaken by Darwinian theories, it's not a done deal - there is some
> controversial science that suggests that parts of the immune system can
> pass on acquired traits (Ted Steele, Lamarck's Signature - see for eg
> http://www.abc.net.au/rn/science/ockham/stories/s14075.htm). If you
> stretch the idea of "self" out to a species (or in to a gene) then
> Darwinian evolution is self-modification too.
" A Darwinian theory for cell differentiation: in this theory, cell
differentiation results from stochastic behaviour of cells (notably in gene
expression) and natural selection inside organisms (notably, adaptation of
cells to metabolic gradients. " Jean-Jacques.Kupiec@ens.fr
Biology and Phylosophy of Sciences (research at CNRS and Ecole Normale
-> A probabilist theory for cell differentiation, embryonic mortality and
DNA c-value paradox. Specul. Sci. Technol. 1983, Volume 6, No 5, p.471-478.
Abstract: A probabilist theory for cell differentiation is proposed in
which it is postulated that differential gene expression is provoked by
random events. An analysis of determinist theories is made, and two
predictions based on the probabilist theory are compared to experimental
facts. A probabilist model of gene regulation is also given. This theory can
account for several phenomena : differential gene expression, embryonic
mortality, DNA c-value paradox; and it does not need to refer to a wide
diversity of specific regulators.
-> A probabilist theory for cell differentiation: the extension of Darwinian
principles to embryogenesis. Specul. Sci. Technol. 1986, Vol. 9, No1,
Abstract: The probabilist theory for cell differentiation is elaborated.
It is now proposed that chains of metabolic cooperation are the source of
order during embryogenesis and it is stressed that, in the framework of this
theory, natural selection the the ultimate biological law that allows us to
understand how the "differentiation program" can evolve.
-> Gene regulation and DNA c-value paradox: a model based on diffusion of
regulatory molecules. Med. Hypotheses, 1989, Volume 28, p.7-10.
Abstract:The general idea of the model is that regulatory molecules can
move stochastically from site to site along DNA and that according to their
chromosomal position, genes should have a more or less high probability to
be activated (or repressed) during differentiation. In this model the role
of non coding DNA is to maintain genes in a relative position that
determines what is usually called the "differentiation programme".
-> A chance selection model for cell differentiation. Cell Death and
differentiation, 1996, Volume 3, p.385-390.
-> Du génotype au phénotype: instruction ou sélection? Avec P Sonigo, 1997,
Médecine/Science (Bulletin de la Société Française de Génétique) Volume 13
-> A Darwinian theory for the origin of cellular differentiation, 1996, Mol
Gen Genet (1997) 255: p.201-208.
Abstract: In this theory, cell differentiation is a two-step mechanism
at each stage of development. In the first step, gene expression is
unstable. It occurs stochastically and produces different cell types. In the
second step gene expression is stabilized by means of cellular interactions.
However, this stabilization cannot occur until the combination of cell
phenotypes corresponding to the developmental stage is expressed. This
selection mechanism prevents disorganizing consequences of stochasticity in
gene expression and directs the embryo towards the adult stage. Instability
and stochasticity in gene expression are caused by random displacement of
regulators along DNA, whereas phosphorylation and/or dephosphorylation
transduction between cells are responsible for the stabilization of
stochastic gene expression. The origin of cellular differentiation is
explained as an adaptation off cells to metabolic gradients created by
substrate diffusion inside growing cell populations. This mechanism provides
cells with complementary metabolism, increasing their ability to use food
resources. Because the metabolic gradients are dependent on external
substrate concentrations, cellular differentiation can also be viewed as an
extension of natural selection inside organisms.
> A-life, and a-life art, involve the pursuit of the emergent moment of
> excess and surprise. Emergence is a knot unto itself, but the ongoing
> emergence that characterises biological life, requires adaptive
> self-modification. Thinking about self-modifying code (or other
> technological systems) quickly runs us into the problem of brittle
> grammars: basically, how likely is it that some random "mutations"
> applied to a bit of c++ code, are going to result in code that is even
> functional, let alone interesting / adaptive? Imagine a robot trying to
> self-modify by picking parts from the shelves of an electronics store.
> The predefined grammars of our technological forms are not an ideal
> substrate for self-modification. Most artificial evolution gets around
> this by creating a grammar of its own. Some grammars are very rich (eg
> Karl Sims' or Steven Rooke's image breeders) and some are more limited
> (eg Latham's virtual sculptures), but all are constructed and involve
> their own constraints.
> My favourite example of self-modification and emergence is the work on
> evolved circuit designs by Adrian Thompson of the COGS lab at Sussex
> (http://www.cogs.susx.ac.uk/users/adrianth/ade.html). Basically he used
> a programmable chip (a FGPA, field gate programmable array) to "breed"
> and automatically test thousands of electronic circuits, on a task such
> as distinguishing between two different frequencies at their inputs.
> Many many generations later, circuits were evolved that indeed
> fulfilled the task. But when the evolved circuits were analysed, they
> were found to operate according to no known principles of circuit
> design... for one thing they were tiny and incredibly efficient (using
> only a small portion of the array) but also they used no internal
> clock, and instead seemed to use the dynamics of interlinked feedback
> loops to analyse the input. Best of all, the circuits didn't work so
> well when the same design was transferred to another chip: the evolved
> design made use of the specific physical characteristics of its
> empyre forum
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