Copyright (c) 2012 John L. Jerz

Principles of the Self-Organizing System (Ashby, 1962)
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The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

 
"There is no getting of selection for nothing."
 

p.261 A "machine" is that which behaves in a machine-like way, namely, that its internal state, and the state of its surroundings, defines uniquely the next state it will go. [JLJ - Wikipedia says a machine is a powered tool consisting of one or more parts that is constructed to achieve a particular goal.]
 
p.264 I am prepared to assert that there is not a single mental faculty ascribed to Man that is good in the absolute sense.
 
p.265 When the environment's parts are not richly connected (when it is highly reducible, in other words), adaptation will go on faster if the brain is also highly reducible, i.e. if its connectivity is small (Ashby, 1960, d).
 
p.269 Since no system can correctly be said to be self-organizing, and since use of the phrase "self-organizing" tends to perpetuate a fundamentally confused and inconsistent way of looking at the subject, the phrase is probably better allowed to die out. [JLJ - yet Walker and Salt in Resilience Practice (2012) define complex adaptive systems as self organizing systems. Go figure.]
 
p.273 there is no difficulty, in principle, in developing synthetic organisms as complex, and as intelligent as we please. But we must notice two fundamental qualifications; first, their intelligence will be an adaptation to, and a specialization towards, their particular environment, with no implication of validity for any other environment such as ours; and secondly, their intelligence will be directed towards keeping their own essential variables within limits.
 
p.274 any quantity K of appropriate selection demands the transmission or processing of quantity K of information (Ashby, 1960, b.) There is no getting of selection for nothing.
  I think that here we have a principle that we shall hear much of in the future, for it dominates all work with complex systems.
 
p.274 I suggest that when the full implications of Shannon's Tenth Theorem are grasped we shall be, first sobered, and then helped, for we shall then be able to focus our activities on the problems that are properly realistic, and actually solvable.
 
p.277 the artificial generation of dynamic systems with "life" and "intelligence"... will the forms developed be of use to us? Here the situation is dominated by the basic law of requisite variety (and Shannon's Tenth Theorem), which says that the achieving of appropriate selection (to a degree better than chance) is absolutely dependent on the processing of at least that quantity of information. Future work must respect this law, or be marked as futile even before it has started.

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