Adaptive networks: theory, models and applications by Thilo Gross, Hiroki Sayama PDF

By Thilo Gross, Hiroki Sayama

ISBN-10: 3642012841

ISBN-13: 9783642012846

With adaptive, complicated networks, the evolution of the community topology and the dynamical methods at the community are both very important and infrequently essentially entangled.

Recent learn has proven that such networks can convey a plethora of recent phenomena that are eventually required to explain many real-world networks. a few of these phenomena comprise powerful self-organization in the direction of dynamical criticality, formation of complicated international topologies in response to basic, neighborhood principles, and the spontaneous department of "labor" during which an before everything homogenous inhabitants of community nodes self-organizes into functionally distinctive sessions. those are only a number of.

This ebook is a cutting-edge survey of these distinctive networks. In it, best researchers got down to outline the longer term scope and course of a few of the main complex advancements within the significant box of complicated community technological know-how and its applications.

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9, 186 (2007) 55. : Community dynamics in social networks. Fluctuation and Noise Letters 7, L273–L287 (2007) 56. : Preferential attachment of communities: The same principle, but a higher level. Europhys. Lett. 73, 478–484 (2006) 57. : Defining and identifying communities in networks. Proc. Natl. Acad. Sci. USA 101, 2658–2663 (2004) 58. : Social inertia in collaboration networks. Phys. Rev. E 73, 016122 (2006) 59. : Hierarchical organization of modularity in metabolic networks. Science 297, 1551–1555 (2002) 60.

Indicates, a typical small and stationary community undergoes minor changes, but lives for a long time. This is well illustrated by the snapshots of the community structure, showing that the community’s stability is conferred by a core of three individuals representing a collaborative group spanning over 52 months. While new co-authors are added occasionally to the group, they come and go. In contrast, a small community with high turnover of its members, (several members abandon the community at the second time step, followed by three new members joining in at time step three) has a lifetime of nine time steps only (Fig.

The opposite is seen for large communities: a large stationary community disintegrates after four time steps (Fig. 15c). In contrast, a large non-stationary community whose members change dynamically, resulting in significant fluctuations in both size and the composition, has quite extended lifetime (Fig. 15d). Indeed, while the community undergoes dramatic changes, gaining (Fig. 15e) or loosing a high fraction of its membership, it can easily withstand these changes. 3 Predicting Community Break Up The quite different stability rules followed by the small and large communities raise an important question: could an inspection of the community itself predict its future?

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Adaptive networks: theory, models and applications by Thilo Gross, Hiroki Sayama

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