Superpolynomial growth in the number of attractors in Kauffman networks (conference report)
Publikation/Tidskrift/Serie: Acta Physica Polonica B
Ytterligare information: Conference report: Workshop on Random Geometry Optimization of Network Flows, MAY 15-17, 2003 KRAKOW, POLAND
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. This work is based on an earlier paper where we introduced a novel approach to analyzing attractors in random Boolean networks. Applying this approach to Kauffman networks, we prove that the average number of attractors grows faster than any power law with system size.
- Biology and Life Sciences
- Physics and Astronomy
- ISSN: 1509-5770
- ISSN: 0587-4254