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.
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References
Serra, R., Zanarini, G.: Complex Systems and Cognitive Processes - A Combinatorial Approach. Springer (1990)
Haken, H.: Synergetics. Springer, Heidelberg (2004)
Tononi, G., McIntosh, A.R., Russell, D.P., Edelman, G.M.: Functional Clustering: Identifying Strongly Interactive Brain Regions in Neuroimaging Data. Neuroimage 7 (1998)
Villani, M., Serra, R.: On the dynamical properties of a model of cell differentiation. EURASIP Journal on Bioinformatics and Systems Biology 2013, 4 (2013)
Benedettini, S.: Identifying mesolevel dynamical structures ECLT (European Center for Living Technologies) technical report, Venice (2013)
Kauffman, S.A.: The Origins of Order. Oxford University Press, Oxford (1993)
Kauffman, S.A.: At Home in the Universe. Oxford University Press, Oxford (1995)
Serra, R., Villani, M., Semeria, A.: Genetic network models and statistical properties of gene expression data in knock-out experiments. Journal of Theoretical Biology 227, 149–157 (2004)
Shmulevich, I., Kauffman, S.A., Aldana, M.: Eukaryotic cells are dynamically ordered or critical but not chaotic. Proc. Natl. Acad. Sci. 102, 13439–13444 (2005)
Villani, M., Serra, R., Graudenzi, A., Kauffman, S.A.: Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data. J. Theor. Biol. 249, 449–460 (2007)
Serra, R., Villani, M., Barbieri, B., Kauffman, S.A., Colacci, A.: On the dynamics of random boolean networks subject to noise: attractors, ergodic sets and cell types. Journal of Theoretical Biology 265, 185–193 (2010)
Villani, M., Barbieri, A., Serra, R.A.: Dynamical Model of Genetic Networks for Cell Differentiation. PLoS ONE 6(3), e17703 (2011), doi:10.1371/journal.pone.0017703
Espinosa-Soto, C., Wagner, A.: Specialization Can Drive the Evolution of Modularity. PLoS Comput. Biol. 6(3) (2010)
Clune, J., Mouret, J.-B., Lipson, H.: The evolutionary origins of modularity. Proceedings of the Royal Society B 280, 20122863 (2013)
Benedettini, S., Villani, M., Roli, A., Serra, R., Manfroni, M., Gagliardi, A., Pinciroli, C., Birattari, M.: Dynamical regimes and learning properties of evolved Boolean networks. Neurocomputing 99, 111–123 (2013)
Packard, N.: Adaptation toward the edge of chaos. In: Kelso, J., Mandell, A., Shlesinger, M. (eds.) Dynamic Patterns in Complex Systems. World Scientific, Singapore (1988)
Chaos, A., Aldana, M., Espinosa-Soto, C., Ponce de Leon, B.G., Garay Arroyo, A., Alvarez-Buylla, E.R.: From Genes to Flower Patterns and Evolution: Dynamic Models of Gene Regulatory Networks. J. Plant Growth Regul. 25, 278–289 (2006)
Villani, M., Filisetti, A., Benedettini, S., Roli, A., Lane, D., Serra, R.: The detection of intermediate-level emergent structures and patterns. In: Proceeding of ECAL 2013, the 12th European Conference on Artificial Life. MIT Press (2013) ISBN: 9780262317092
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Villani, M., Benedettini, S., Roli, A., Lane, D., Poli, I., Serra, R. (2014). Identifying Emergent Dynamical Structures in Network Models. In: Bassis, S., Esposito, A., Morabito, F. (eds) Recent Advances of Neural Network Models and Applications. Smart Innovation, Systems and Technologies, vol 26. Springer, Cham. https://doi.org/10.1007/978-3-319-04129-2_1
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DOI: https://doi.org/10.1007/978-3-319-04129-2_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04128-5
Online ISBN: 978-3-319-04129-2
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