Emergence, Locating and Measuring It - Systematic Design for Emergence in Cellular Nonlinear Networks - page 52

from 0.5, usually towards 1, indicating a shift from complete disorder ( C=0.5 or
white noise) to perfect order ( C=1, or C=0 ). The presence of gliders in the above
examples is detectable, particularly in Fig. 4.3b-d, i.e. exactly in those cases with
long transients and where the exponent of growth is larger than one but not reach-
ing the largest possible value.

(a) (b) (c)

(d) (e) (f)

Fig. 4.3. Different behaviors of CAs belonging to Wolfram's Class III

Note the example in Fig. 4.3b, run for 150 iterations, visually representing a
Class III behavior. Further simulation for 4,000 iterations indicate that after a very
long transient of 2,739 iterations the system enters a low periodic state, specific
for Class II. The lesson learned is that for those behaviors susceptible of high
complexity, longer simulations are needed to detect their exact nature. But, looking
at the exponent of growth complex behaviors may be detectable even after a shorter
time simulation. This is the case for to ID=133 depicted in Fig. 4.3b. The scenario
for emergence of gliders is similar with what we found for the previous examples
belonging to different Wolfram classes.