I think some help is needed by Alan to clarify what you are referring
Nevertheless I give it a try:
Apparently more complex biological systems live from less complex
ones. Take care: complex in the eye of the human observer. But
Cybernetics has learned me to look in a more cyclical way. More
complex organizations are also more fragile than less complex ones.
When they break down, they break down in less complex systems. Eg:
worms are feeding on the remains of mammals. This is the reason I
write that even if the human species disappears from the earth, life
shall go on. Again, the tendency to greater complexity is in the eye
of the observer. And not a natural law, although the ideas of Teilhard
de Chardin are very seductive. Nevertheless this cyclical nature of
the feeding chain is a humbling experience.
Op 9-mrt-11, om 12:39 heeft Vladimir het volgende geschreven:
> I ask you to reflect upon a model described above.
> In "Decision and Control" Stafford Beer wrote a chapter under a
> title "Self-organizing systems". This chapter describes a situation
> where more organized system must feed and grow at the expense (and
> in the direction) of less organized one , because less organized
> system has not consumed its energy to organize itself, so entropy
> evens out this rest of energy between these systems. Thus energy
> flows from MOS to LOS.
> Sometimes I hear from people about energetic vampirism and feel how
> this happens with myself while interacting with others.
> We also have Beer's model of CHRONIC Societary Triage, where he
> describes inability of some categories of people to become more
> organized due to their complex identities oppressed by ideology. He
> also wrote in this article about stable flow of resources from less
> organized people to more organized ones and mentioned existance of
> many intermediate categories of people between described in details
> basic A, B, and C.
> Thus we can imagine self-organizing network of people fixedly
> organized in various degree minimizing social vampirism along
> relations which this network consists of.
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