The Number of Attractors in Kauffman Networks
Abstract
Description
The Kauffman model describes a particularly simple class of random Boolean networks. Despite the simplicity of the model, it exhibits complex behavior and has been suggested as a model for real world network problems. We introduce a novel approach to analyzing attractors in random Boolean networks, and applying it to Kauffman networks we prove that the average number of attractors grows faster than any power law with system size.
4 pages, 2 figures, to appear in Physical Review Letters. Version 3 changes: Made focus clearer, added ref to Socolar/Kauffman
4 pages, 2 figures, to appear in Physical Review Letters. Version 3 changes: Made focus clearer, added ref to Socolar/Kauffman