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.

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