**Maximize resources**

The CA is controlled by the following buttons:

**Shorter:** Makes CA shorter.

**Longer:** Makes CA longer.

**
Hide CA-2
Plant CA-1: **CA-1 is planted.

ycoord CA-1 down:

ycoord CA-2 up:

Resources=

**Before starting
inspect the the previous two experiments.
**When the experiment starts the two CA start moving.
Their resources decline and they get thinner when dropping below -40
(resources < -40) they turn toward each other. When they touch or
overlap, resources are replenished to a maximum of 20, and the CA get
wider. Each CA senses where the other is. Both bounce back from the
borders.

You may desynchronize the CA by replanting one of them.
With time CA become more and more attracted to each other, and their
resources increase. They become wider and their movement more sluggish.
Finally they take up the structure of the isolated (default) CA with
resources = 20. You may now replant them, and change their initial
position. The system will converge to the same final solution. It may
happen that a CA becomes wide and asymmetric while its resources = 20.
This is not yet the final solution, but it will come.

This system is a non linear maximizer (optimizer) with **one maximum**
{width = 24; resources = 20} which has some interesting properties:

1. The two zygotes controlled by their rule = #600
generate a set of states. The **set is closed** in the
sense, that each of its members will converge to the one and only maximum{width
= 24; resources =20}. In other words when planting a CA you may choose
a state instead of the usual zygote and the outcome will be the same.

2. While other artificial life constructs, e.g., neural nets, or genetic
algorithms, converge to their optima asymptotically, here convergence
is absolute.

3. Although the system is bounded it seems that the same holds also for an unbounded system.

4. As the system converges its members become wider,
and the probability p1 of resource accumulation rises.

5 As the system converges movement of its members becomes more and
more sluggish, and their probability p2 to meet declines. Yet p1 increases
faster than the decline rate of p2.