µ = N$_{T}$ , i.e. a single module, so there is no possible combination of attractors. Case 4 has the lowest A of all five cases. The extreme case 5 has a minimum µ = 1 N$_{T}$ , i.e. N = 1, giving the highest A of all five cases. Notice that in case 5 A decreases for K$_{T}$ > 2. This is because even when κ is constant in theory, in practice κ decreases as K$_{T}$ increases, given the fact that if K > N is equivalent in practice to K = N because of fictitious inputs ( N = 1 in this case, see Table A.5 in Appendix A). The effect of κ on Le seems to be minimal, as the average attractor lengths is very similar for cases 1, 2, and 3, exponentially increasing with K$_{T}$ , as it can be seen in Figure 7. The effect of µ on Le is seen in Figure 8. For K ≥ 3, classical RBNs ( µ = 1) have a higher Le 14 4.1.2 Attractor Lengths Figure 6: Number of Attractors for different K$_{T}$ for cases 4, 5 & 1 ( M = 1, N = 1, and K = L , respectively). Notice logarithmic scale. K$_{T}$ Number of Attractors 1 2 3 4 1 5 10 50 100 500 1000 M=1 N=1 K=L M=1 N=1 K=L M=1 N=1 K=L M=1 N=1 K=L