Notes for the Lifebox, the Seashell, and the Soul - Rudy Rucker

Notes for The Lifebox, the Seashell, and the Soul, by Rudy Rucker
This approach produces a phenomenon called numerical instability, meaning that all
the cell values have a strong oscillation from generation to generation, producing artifacts
such as a persistent domain boundaries and a checkerboard pattern. Be that as it may, the
rule is computationally interesting. The unstable generational oscillations are more or less in
synch across all the cells, so patterns are in fact able to emerge. The figure in the text shows
scrolls in a version of this rule where each cell looks only at its four nearest neighbors, we
use a logistic growth factor A of 2.1 and a diffusion rate B of 0.8. (Note that our A value of
2.1 is what Ralph Abraham’s paper would call 0.5025, as he multiplies his A by a factor of
4.)
In the figure shown in the text, the checkerboard pattern has been reduced both by
showing the differences between cells and their neighbors and by coloring nearby values the
same. The domain boundaries are visible as looping lines. Over time these loops will shrink
and disappear, leaving one or more loops that wrap all the way “around” the simulation space
which, as usual, identifies the left and right edges and the top and bottom edges.
To me, the Kaneko-Abraham method seems unnatural in that the diffusion and
logistic operations are in some sense out of synch. Essentially each cell does a logistic
update and then does diffusion based on its values before the logistic update. I would have
expected better results from a rule in which all the cells diffuse their values first and only
then do a logistic update.
diffusion = B•(Average of neighboring population values - pop)
newpop = Logistic(A, pop + diffusion)
This approach does give smoother, somewhat less unstable patterns, but I’ve been
unable to find Zhabotinsky scrolls with it ⎯ at best I’ve come up with some Turing spots.
As I discuss in the text, when I use this second approach to the algorithm with two species, I
had good success.
Artificial Life
Vaucasson’s duck. The little writing manikins in the Neufchatel museum.
Alife lacks morphogenesis. The shapes really don’t arise naturally from the code.
A life lacks homeostasis.
Improve DNA-like genomes by fitness proportional reproduction. Fitness =
gnarliness?
The notion of evolution has been strongly used by computer scientists in attempts to
find good programs. Fitness function.
Telerobotics
(Lifted from my Artificial Life Lab manual.)
For many applications, the user might not need for a robot to be fully autonomous.
Something like remotely operated hand that you use to handle dangerous materials is like a
robot, in that it is a complicated machine which imitates human motions. But a remote hand
does not necessarily need to have much of an internal brain, particularly if all it has to do is
to copy the motions of your real hand. A device like a remote robot hand is called a telerobot.
Radioactive waste is sometimes cleaned up by using telerobots that have video
cameras and two robotic arms. The operator of such a telerobot sees what it sees on a video
screen, and moves his or her hands within a mechanical harness that send signals to the hands
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