2002/08/01 by Carlos Gershenson, Gershenson, Carlos
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · #B.6.1 #C.1.3 #Cellular Automata and Applications #Cellular Automata and Lattice Gases (nlin.CG) #Computational Complexity (cs.CC) #Discrete Mathematics (cs.DM) #Dynamical Systems (math.DS) #F.1.1 #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Gene Regulatory Network Analysis #Protein Structure and Dynamics #cs.CC #cs.DM #math.DS #nlin.CG
paper · pdf · doi:10.48550/arxiv.cs/0208001
8 pages, 11 figures, 5 tables. To be published in Standish, Abbass and Bedau (eds.) Artificial Life VIII
arxiv created 2002/08/01 · openalex publication_date 2002/08/01 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.