Sieves for Selection of Genes According to Desired Behaviors - Systematic Design for Emergence in Cellular Nonlinear Networks - page 100

As in the previous case, many other sieves can be used to locate similar behaviors.
In all cases it is important to tune the parameters of the sieves such that the result
is a manageable list of IDs with at most tens of CA cells. By further simulation of
these cells one may infer conclusions that can be used to improve the definition of
sieves with respect to an identifiable behavior. A similar “game of life” behavior
is observed for another member selected by the sieve, namely the ID = 44223, as
seen in Fig. 6.5.
Fig. 6.5. The dynamics of another CA (ID = 44223) selected by the “Similar to Game of
Life” sieve. Note the emergence of gliders with a higher frequency during the first iterations.
After several thousands of iterations the CA evolves to a more ordered global state
For reference, the dynamic evolution of the “Game of Life” CA (ID = 6,152) is
given in Fig. 6.6 for the same initial state.
Note that although there is a slow evolution with a lot of activity among the
emerging gliders, after enough iterations (here more than 2,000), unlike in the case
of “intelligent life” behaviors, the CA system enters in a highly ordered global
state. Such ordered global states can be metaphorically described as remains of a
civilization which was not capable to maintain the “living” state for ever, as
opposed to “intelligent life” where such living pattern appears to be maintained
for ever. So far, using the sieve method combined with experiments, suggests that
the key ingredient in reaching “intelligent life” behaviors is a “slow growth” as
described previously.