Vitality
and Health-1
We continue to explore the health equation:
health = v m
v : tolerance accumulation rate.
m : remains undefined for a while.
In the isolated CA
v rises linearly, m
equals approximately to 1, and health = v. Both
variables can be estimated with linear regression of v. b
is the slope of v, and k its
correlation coefficient, which will be taken as an m estimate. In the
isolated state, v = b = 0.0443 and m = k = 0.994. Once CA start to interact
both variables change, and m < 1.
m might be regarded as an interaction indicator.
Roughly the more intensive CA interaction, the smaller k. Nevertheless,
since m is non-linear it is not entirely (negatively)
proportional to CA interaction.
The parameter set remains the same as in the previous
experiment except that the change state functions vary:
change state: [state[1, i+1] = state[0. 1],
state[0, k]];
change state: [state[2, i+1] = state[0. 1], state[0, k]];
change state: [state[3, i+1] = state[0. 1], state[0, k]]; {k,
1, 46}
Most CA-0 states accelerate CA-2 above the
velocity of CA-1. However not all CA-3 are faster than CA-2.
On the right side of the diagram CA accelerate faster. This segment
is highlighted in the next
diagram.
The black line is the velocity of an isolated CA-0,
which is faster than CA-1. Thus CA-1 decelerates in relationship to
CA-0, and is less healthy.