The dynamics of critical Kauffman networks under asynchronous stochastic update
Florian Greil, Barbara Drossel
Abstract
We show that the mean number of attractors in a critical Boolean network under asynchronous stochastic update grows like a power law and that the mean size of the attractors increases as a stretched exponential with the system size. This is in strong contrast to the synchronous case, where the number of attractors grows faster than any power law.
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