A local behavior identification algorithm for generative network automata configurations

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Date

2011

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Department of Business
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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. © 2011 Springer-Verlag.

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Hungarian Academy of Science; Aitia International, Inc.

Keywords

Automata Networks, Discrete Dynamical Systems, Generative Network Automata, Identification, Inverse Problem

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0

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Source

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -- 10th European Conference of Artificial Life, ECAL 2009 -- 13 September 2009 through 16 September 2009 -- Budapest -- 85428

Volume

5778 LNAI

Issue

PART 2

Start Page

191

End Page

199

URI

https://doi.org/10.1007/978-3-642-21314-4_24
 https://hdl.handle.net/20.500.14411/3646

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Scopus