Contextual Random Boolean Networks

dc.creatorGershenson, Carlos
dc.creatorBroekaert, Jan
dc.creatorAerts, Diederik
dc.date2003-03-10
dc.date2003-06-11
dc.date.accessioned2026-07-07T05:34:36Z
dc.date.available2026-07-07T05:34:36Z
dc.descriptionWe propose the use of Deterministic Generalized Asynchronous Random Boolean Networks [Gershenson, 2002] 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 non-deterministic in a specific way, namely introducing a non-Kolmogorovian quantum-like structure for the modelling of the network [Aerts, 1986]. 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.
dc.description10 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/nlin/0303021
dc.identifierhttp://arxiv.org/abs/nlin/0303021
dc.identifierIn Banzhaf, W, T. Christaller, P. Dittrich, J. T. Kim, and J. Ziegler, Advances in Artificial Life, 7th European Conference, ECAL 2003, Dortmund, Germany, pp. 615-624. LNAI 2801. Springer.
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/80427
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectDisordered Systems and Neural Networks
dc.subjectComputational Complexity
dc.subjectCellular Automata and Lattice Gases
dc.titleContextual Random Boolean Networks
dc.typetext

Files

Collections