Sieves for Selection of Genes According to Desired Behaviors - Systematic Design for Emergence in Cellular Nonlinear Networks - page 101

Fig. 6.6. Dynamics of the classic “Game of Life” CA (ID = 6152)
There is enough evidence to suggest that such “intelligent life” behaviors may
include systems to be further investigated in more depth to reveal applications
related to the field of computational intelligence.
6.3.3 Other Interesting Emergent Behaviors
As indicated above, it is found that interesting emergent behaviors (lets call
them highly complex) occur often for large transients and slow explosion (re-
ferred in Chap. 5 as “near edge but unstable” category). A crisp double sieve can
be established to locate these highly complex emergent phenomena, as shown in
Fig. 6.7.
Let simulate CAs for several of the 252 cells selected by the above double
sieve. The first example, shown in Fig. 6.8, is a run of the CA with ID = 7803.
Starting from a random initial state spatial cluster, the system evolves slowly into
a more organized family of clusters containing traveling gliders , which interact
producing novel types of gliders. The emergence of gliders is a significant phe-
nomena since an in depth study of the glider production and interaction would
often lead to the conclusion that all fundamental logic functions can be emulated
by spatial interaction of such gliders and therefore universal computation can be
demonstrated. Although, so far the “Game of Life” phenomena was the mostly
investigated for its gliders, the double sieve method reveals hundreds of similar
CA genes within the “2s9” family (Game of Life being itself a member of the
family) confirming recent findings that complex behaviors are actually much more
often present in cellular automata than initially assumed [74].