Abstract
Relation between the part and the whole is investigated in the context of complex discrete dynamical systems. For that purpose, an algorithm for local behavior identification from global data described as Generative Network Automata model configurations is developed. It is shown that one can devise a procedure to simulate finite GNA configurations via Automata Networks having static rule-space setting. In practice, the algorithm provides an automated approach to model construction and it can suitably be used in GNA based system modeling effort.
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Özdemir, B., Kılıç, H. (2011). A Local Behavior Identification Algorithm for Generative Network Automata Configurations. In: Kampis, G., Karsai, I., Szathmáry, E. (eds) Advances in Artificial Life. Darwin Meets von Neumann. ECAL 2009. Lecture Notes in Computer Science(), vol 5778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21314-4_24
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DOI: https://doi.org/10.1007/978-3-642-21314-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21313-7
Online ISBN: 978-3-642-21314-4
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