Another 'm' estimate
We continue exploring the new definition of health = v*m. Particularly the role of the m-factor in health. Previously we used the correlation coefficient to estimate m, which was somewhat crude and will be replaced with a better estimate.
delivery activation: [state[1,
set point = p[1] - 0.1, state[0,k]];{k,1,46}
change state: [state[1, i+1]
= state[0, k], state[1,k]]; {k,1, 46}
The following parameters were estimated:
1. Tolerance velocity was estimated with regression.
2. Min[velocity] and Max[velocity].
Health
The m-factor is defined: m = Min[velocity]/[Max velocity], and
health = v * m.
The parameters were estimated in 46 CA. Each was triggered
by a different CA-0 state, using the change state function.
Some CA have a distinct core (CA-1) while other,
like CA-2 lack it. When the core vanishes its velocity v = 0, health
= 0 whereupon the CA-2 dies and is replaced with a new zygote.
The figure depicts health in CA triggered by the 46 CA-0 states. Most of the CA remain isolated and like CA-1 occupy the central line. Their health is about 2.4.
CA product
The main task of a CA is to accumulate tolerance (resources). Resources generated at one instant (step) are called product (input). One part of the product becomes CA structure (CA core). The other part, or output (CA rim), is supplied to their environment. Core and rim width are controlled by the m-factor.
Output[CA-2] = 1.000
Output[CA-3] = 0.703
Output[CA-4] = 0.854
First argument: CA receiving the delivery.
Second argument: Delivering CA.
Third argument: Delivery condition.
Fourth argument: Delivery amount.
p[j]: daily production.
First argument: state transfer.
Second argument: the state k of CA-0 which activates the change.
First argument: state augmentation.
Second argument: Delivery condition.
p[j]: daily production.