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Contextual Random Boolean Networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We propose the use of Deterministic Generalized Asynchronous 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 non-deterministic in a specific way, namely introducing a non-Kolmogorovian quantum-like 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.

Original languageEnglish
Title of host publicationAdvances in Artificial Life
EditorsWolfgang Banzhaf, Jens Ziegler, Thomas Christaller, Peter Dittrich, Jan T. Kim
PublisherSpringer Verlag
Pages615-624
Number of pages10
ISBN (Print)3540200576, 9783540200574
DOIs
StatePublished - 2003
Event7th European Conference on Artificial Life, ECAL 2003 - Dortmund, Germany
Duration: Sep 14 2003Sep 17 2003

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2801

Conference

Conference7th European Conference on Artificial Life, ECAL 2003
Country/TerritoryGermany
CityDortmund
Period09/14/0309/17/03

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