 At a first approximation, the Edge of Chaos hypothesis is confirmed: three of the eight neighbors are Class3, three are Class2, two are Class1: Rule 110 is the only Class4 in the table. To generalize these findings to the entire class of rules for one-dimensional CA, Langton introduced a parameter, \(\lambda\), that applies to each \(\phi\): for \(k = 2\), \(r = 1\) (binary-state, unary-range) CA, \(\lambda(\phi)\) can be computed as the fraction of entries of the transition rule table that are mapped to a non-zero output (see Langton 1990: 14 for the general definition). In our case this means: \(\lambda(\phi)\) will be equal to the number of ones in the rule column—e.g., \(\lambda(\phi) = 5/8\) for \(\phi\) = Rule 110 and \(\lambda(\phi) = 1/2\) for \(\phi\) = Rule 46. Langton’s major finding was that a simple measure such as \(\lambda\) correlates with the system behavior: as \(\lambda\) goes from 0 to 1, the average behavior of the systems goes from freezing to periodic patterns to chaos. Langton singled out 1/2 as the value of \(\lambda\) at which the average behavior first shows evidence of chaos: rules \(\phi\) with \(\lambda(\phi) \sim 1/2\) were highlighted as being on the Edge (see Miller &amp; Page 2001: 133).