The identification of emergent structures in dynamical systems is a major challenge in complex systems science. In particular, the formation of intermediate-level dynamical structures is of particular interest for what concerns biological as well as artificial network models. In this work, we present a new technique aimed at identifying clusters of nodes in a network that behave in a coherent and coordinated way and that loosely interact with the remainder of the system. This method is based on an extension of a measure introduced for detecting clusters in biological neural networks. Even if our results are still preliminary, we have evidence for showing that our approach is able to identify these “emerging things” in some artificial network models and that it is way more powerful than usual measures based on statistical correlation. This method will make it possible to identify mesolevel dynamical structures in network models in general, from biological to social networks

Identifying emergent dynamical structures in network models / Villani, Marco; Stefano, Benedettini; Andrea, Roli; Lane, David Avra; Irene, Poli; Serra, Roberto. - STAMPA. - 26:(2014), pp. 3-13. (Intervento presentato al convegno 23rd Workshop of the Italian Neural Networks Society (SIREN), tenutosi a Vietri sul Mare, Salerno, Italy nel May 23-25) [10.1007/978-3-319-04129-2_1].

Identifying emergent dynamical structures in network models

VILLANI, Marco;LANE, David Avra;SERRA, Roberto
2014

Abstract

The identification of emergent structures in dynamical systems is a major challenge in complex systems science. In particular, the formation of intermediate-level dynamical structures is of particular interest for what concerns biological as well as artificial network models. In this work, we present a new technique aimed at identifying clusters of nodes in a network that behave in a coherent and coordinated way and that loosely interact with the remainder of the system. This method is based on an extension of a measure introduced for detecting clusters in biological neural networks. Even if our results are still preliminary, we have evidence for showing that our approach is able to identify these “emerging things” in some artificial network models and that it is way more powerful than usual measures based on statistical correlation. This method will make it possible to identify mesolevel dynamical structures in network models in general, from biological to social networks
2014
23rd Workshop of the Italian Neural Networks Society (SIREN),
Vietri sul Mare, Salerno, Italy
May 23-25
26
3
13
Villani, Marco; Stefano, Benedettini; Andrea, Roli; Lane, David Avra; Irene, Poli; Serra, Roberto
Identifying emergent dynamical structures in network models / Villani, Marco; Stefano, Benedettini; Andrea, Roli; Lane, David Avra; Irene, Poli; Serra, Roberto. - STAMPA. - 26:(2014), pp. 3-13. (Intervento presentato al convegno 23rd Workshop of the Italian Neural Networks Society (SIREN), tenutosi a Vietri sul Mare, Salerno, Italy nel May 23-25) [10.1007/978-3-319-04129-2_1].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1010520
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