Variants of a random boolean network of binary gates called the Kauffm
an net are studied. Each gate receives two random inputs from the othe
r gates in the network and is assigned a transition function from a no
n-uniform distribution. Fine upper bounds on the attractor and transie
nt lengths as the behavioral characteristics of the network are determ
ined for large net size, N, and different transition function distribu
tions. The effects of these distributions on the localization property
of the net is shown. Analysis of nets with N > 1000 was shown to be v
ery difficult. We also determine the scaling properties of attractors
and transients with the net size. Our results exhibit strong ''anticha
os'' behavior even for very large N for some of the networks.