 
Summary: Contextual Random Boolean Networks
Carlos Gershenson, Jan Broekaert, and Diederik Aerts
Centrum Leo Apostel, Vrije Universiteit Brussel, Krijgskundestraat 33,
Brussels, 1160, Belgium
{cgershen, jbroekae, diraerts,}@vub.ac.be
http://www.vub.ac.be/CLEA
Abstract. We propose the use of Deterministic Generalized Asynchro
nous Random Boolean Networks [1] as models of contextual deterministic
discrete dynamical systems. We show that changes in the context have
drastic effects on the global properties of the same networks, namely
the average number of attractors and the average percentage of states
in attractors. We introduce the situation where we lack knowledge on
the context as a more realistic model for contextual dynamical systems.
We notice that this makes the network nondeterministic in a specific
way, namely introducing a nonKolmogorovian quantumlike structure
for the modelling of the network [2]. In this case, for example, a state of
the network has the potentiality (probability) of collapsing into different
attractors, depending on the specific form of lack of knowledge on the
context.
1 Introduction
