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 International Conference on Complex Systems (ICCS2007)

Computational exploration of binary-state GNA dynamics

Hiroki Sayama
Department of Bioengineering, Binghamton University, SUNY

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     Last modified: June 26, 2007

A variety of modeling frameworks have been proposed and utilized in complex systems studies, including dynamical systems models that describe state transitions within a system of fixed topology, and complex networks models that describe topological transformations of a network with little attention paid to dynamical state changes. However, many real-world complex systems exhibit both of these two dynamics simultaneously. We recently proposed a novel modeling framework, "Generative Network Automata (GNA)", that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical systems as a generative process realized by repetitive local subnetwork rewritings [1]. In this talk, we will present our latest results of extensive computational experiments that exhaustively swept over possible rewriting rules of simple binary-state GNA (which are much less restricted than assumed in [1]) and revealed several distinct classes of the GNA dynamics. Possible applications of GNA for complex systems modeling will also be discussed.

[1] Hiroki Sayama, Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies, Proceedings of the First IEEE Symposium on Artificial Life (IEEE-CI-ALife '07), Honolulu, HI, 2007, IEEE, pp.214-221.

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