ICAs and global ICAs have been explored previously by Stephen Wolfram and others. ICAs choose a random rule to apply to all the cells at each step, while global ICAs choose the rule to apply at each step based on the global state of the automaton. The difference between these previous investigations and fully random ICAs (FRICAs) is that FRICAs choose a different rule to apply at every individual cell from the set of rules defined by the user. The sliders on the left let you explore the space of rule combinations quickly. Expanding the slider controls allows for a more dynamic search.

The results of FRICAs are inherently random, but many combinations of rules produce persistent and identifiable structures. Many of the most interesting rule combinations include a mixture of CA from different classes (S. Wolfram, A New Kind of Science, Champaign, IL: Wolfram Media, Inc., 2002 pp. 231–249). One possible application of FRICAs is a more refined classification system based on, for instance, how damaging the inclusion of a given rule is to the universal behavior of rule 110. It is also possible that systems in nature mimic the process of choosing randomly for each operation from a limited set of functional rules.