Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies

Hiroki Sayama

doi:10.1109/ALIFE.2007.367799

Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies

Hiroki Sayama

Watson Dean's Office

Binghamton University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Scopus citations

Abstract

We propose a new modeling framework "Generative Network Automata (GNA)" that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical networks. GNA is formulated as an extension of existing complex dynamical network models to include a new set of generative update rules that determine how local network topologies will change based on the current local network states and topologies. This paper introduces basic concepts of GNA, its formal definitions, its generality to represent other dynamical systems models, and some preliminary results of an exhaustive sweep of possible dynamics found in elementary binary GNA with restricted updating rules.

Original language	English
Title of host publication	Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007
Publisher	IEEE Computer Society
Pages	214-221
Number of pages	8
ISBN (Print)	142440701X, 9781424407019
DOIs	https://doi.org/10.1109/ALIFE.2007.367799
State	Published - 2007
Event	1st IEEE Symposium on Artificial Life, Alife 2007, Part of the 2007 IEEE Symposium Series on Computational Intelligence, SSCI 2007 - Honolulu, HI, United States Duration: Apr 1 2007 → Apr 5 2007

Publication series

Name	Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007

Conference

Conference	1st IEEE Symposium on Artificial Life, Alife 2007, Part of the 2007 IEEE Symposium Series on Computational Intelligence, SSCI 2007
Country/Territory	United States
City	Honolulu, HI
Period	04/1/07 → 04/5/07

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10.1109/ALIFE.2007.367799

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Sayama, H. (2007). Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies. In Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007 (pp. 214-221). Article 4218889 (Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007). IEEE Computer Society. https://doi.org/10.1109/ALIFE.2007.367799

@inproceedings{5e03725b5f494abfab988f2fc8c1a39e,

title = "Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies",

abstract = "We propose a new modeling framework {"}Generative Network Automata (GNA){"} that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical networks. GNA is formulated as an extension of existing complex dynamical network models to include a new set of generative update rules that determine how local network topologies will change based on the current local network states and topologies. This paper introduces basic concepts of GNA, its formal definitions, its generality to represent other dynamical systems models, and some preliminary results of an exhaustive sweep of possible dynamics found in elementary binary GNA with restricted updating rules.",

author = "Hiroki Sayama",

year = "2007",

doi = "10.1109/ALIFE.2007.367799",

language = "English",

isbn = "142440701X",

series = "Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007",

publisher = "IEEE Computer Society",

pages = "214--221",

booktitle = "Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007",

note = "1st IEEE Symposium on Artificial Life, Alife 2007, Part of the 2007 IEEE Symposium Series on Computational Intelligence, SSCI 2007 ; Conference date: 01-04-2007 Through 05-04-2007",

}

Sayama, H 2007, Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies. in Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007., 4218889, Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007, IEEE Computer Society, pp. 214-221, 1st IEEE Symposium on Artificial Life, Alife 2007, Part of the 2007 IEEE Symposium Series on Computational Intelligence, SSCI 2007, Honolulu, HI, United States, 04/1/07. https://doi.org/10.1109/ALIFE.2007.367799

Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies. / Sayama, Hiroki.
Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007. IEEE Computer Society, 2007. p. 214-221 4218889 (Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - We propose a new modeling framework "Generative Network Automata (GNA)" that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical networks. GNA is formulated as an extension of existing complex dynamical network models to include a new set of generative update rules that determine how local network topologies will change based on the current local network states and topologies. This paper introduces basic concepts of GNA, its formal definitions, its generality to represent other dynamical systems models, and some preliminary results of an exhaustive sweep of possible dynamics found in elementary binary GNA with restricted updating rules.

AB - We propose a new modeling framework "Generative Network Automata (GNA)" that can uniformly describe both state transitions and autonomous topology transformations of complex dynamical networks. GNA is formulated as an extension of existing complex dynamical network models to include a new set of generative update rules that determine how local network topologies will change based on the current local network states and topologies. This paper introduces basic concepts of GNA, its formal definitions, its generality to represent other dynamical systems models, and some preliminary results of an exhaustive sweep of possible dynamics found in elementary binary GNA with restricted updating rules.

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DO - 10.1109/ALIFE.2007.367799

M3 - Conference contribution

SN - 142440701X

SN - 9781424407019

T3 - Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007

SP - 214

EP - 221

BT - Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007

PB - IEEE Computer Society

Y2 - 1 April 2007 through 5 April 2007

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Sayama H. Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies. In Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007. IEEE Computer Society. 2007. p. 214-221. 4218889. (Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007). doi: 10.1109/ALIFE.2007.367799

Generative network automata: A generalized framework for modeling complex dynamical systems with autonomously varying topologies

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