Phase Transitions in Logic Networks

Randomly connected networks of Boolean logic functions of fixed in-degree ("Kauffman Nets") are analyzed using an annealed approximation. While these nets originated as models of genetic regulatory networks, the conclusions and observations obtained by treating them as a complex type of spin system are relevant beyond the purview of genetics and have applications in the construction and control of certain complex dynamical systems. Preliminary results are presented on the properties of nets incorporating bias and redundancy.