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Yet if biology samples underlying genetic programs essentially at random, why should these programs behave anything like programs that are derived from specific laws of physics?
And in the case where there is very little damping the last two pictures show that at least for a while elements can form at fairly random angles.
In the previous section I argued that for the most part such rules will not be carefully chosen by natural selection, but instead will just be picked almost at random from among the possibilities.
The next two pages [ 438 , 439 ] show examples of the behavior of such cellular automata with both random and simple initial conditions.
One still has a
The behavior of rules (a) and (b) from the facing page when replacements are performed at random.
The basic idea is to have a sequence of layers of nerve cells—much as one knows exist in the brain—with each cell in each successive layer responding only if the inputs it gets from some fixed random set of cells in the layer above form some definite pattern.
And what this means is that such rules will typically show the same features as rules chosen at random from all possibilities—with the result that presumably they do in the end exhibit universality in almost all cases where their overall behavior is not obviously simple.
If one chooses generalized mobile automata at random, most of them will produce simple behavior, as shown in the first few pictures on the facing page .
So in the end the patterns we obtain can look just as random as what we have seen in systems like cellular automata.
This quantity is -1 for all nonzero m for PN sequences (so that all but the first component in Abs[Fourier[(-1) list ]] 2 are equal), but has mean 0 for truly random sequences.