Non linear control
We continue the previous
experiment . where three CA exchange resources (age). None is injured,
yet CA-1 differentiates. When its cells reach max age = 110, their age is set to zero
and they are secreted into the environment. CA-1 differentiation initiates cell production. The present experiment
explores how the exchange of resources in the system affects cell production.
In the second
experiment max age of CA-1 was set to 110 (compare with
ch-61). Initially all cells were younger than max age. Somewhat later,
they reached max age and their
age was set to zero. These cells were then secreted into the environment.
All together, during this experiment, CA-1 produced 15 cells.
The other two CA aged as above.
In the third experiment. CA-2 contributed its resources
to CA-1 whereupon CA-1 started deteriorating and died at t = 20. It
produced 11 cells. The same
outcome was observed when both
CA-1 and CA-2 exchanged resources.
In the fourth experiment below, CA-3 contributed its resources. The system started oscillating and produced 35 cells
In the last experiment, resources were freely distributed between all CA. Nevertheless
CA-1 died after producing 13 cells. CA-2 and CA-3 remained alive yet their
resources (ages) were completely depleted.
Aging velocity
The amount
of resources produced by a CA depends on its aging velocity. As CA transfers
its resources its aging
decelerates.
Health
is defined here as production / total age.
Apparently the system tested
in the fourth experiment was the healthiest.
The behavior of this simple system beats any intuition.
One would expect that adding resources to CA-1, like in the second experiment
, might be beneficial, nonetheless CA-1 died. The response is unpredictable. In small systems one might
evaluate all possible links between the CA. and find an
optimal configuration. (solution). With a larger CA set such is unthinkable, and may not be necessary.
Why not let the system itself come
up with its optimal solution?