3#1

Classification of Random Boolean Networks

Carlos Gershenson,
School of Cognitive and Computer Sciences
University of Sussex
Brighton, BN1 9QN, U. K.
C.Gershenson@sussex.ac.uk
http://www.cogs.sussex.ac.uk/users/carlos
Center Leo Apostel, Vrije Universiteit Brussel
Krijgskundestraat 33, B-1160 Brussels, Belgium

Abstract:

We provide the first classification of different types of Random Boolean Networks (RBNs) . We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena.