Spatial Embedding and Complexity: The Small-World is Not Enough
Spatial Embedding and Complexity: The Small-World is Not Enough
The “order for free” exhibited by some classes of system has been exploited by natural selection in order to build systems capable of exhibiting complex behaviour. Here we explore the impact of one ordering constraint, spatial embedding, on the dynamical complexity of networks. We apply a measure of functional complexity derived from information theory to a set of spatially embedded network models in order to make some preliminary characterisations of the contribution of space to the dynamics (rather than mere structure) of complex systems. Although our measure of dynamical complexity hinges on a balance between functional integration and segregation, which seem related to an understanding of the small-world property, we demonstrate that smallworld structures alone are not enough to induce complexity. However, purely spatial constraints can produce systems of high intrinsic complexity by introducing multiple scales of organisation within a network.
complexity, networks, information theory, theoretical neuroscience
986-995
Buckley, Christopher L
68a32d02-6b88-4796-a8d9-719ea6076832
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Almeida e Costa, Fernando
2007
Buckley, Christopher L
68a32d02-6b88-4796-a8d9-719ea6076832
Bullock, Seth
2ad576e4-56b8-4f31-84e0-51bd0b7a1cd3
Almeida e Costa, Fernando
Buckley, Christopher L and Bullock, Seth
(2007)
Spatial Embedding and Complexity: The Small-World is Not Enough.
Almeida e Costa, Fernando, Rocha, Luis M., Costa, Ernesto, Harvey, Inman and Coutinho, António
(eds.)
In Advances in Artificial Life: Proceedings of the Ninth European Conference on Artificial Life.
Springer Berlin.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The “order for free” exhibited by some classes of system has been exploited by natural selection in order to build systems capable of exhibiting complex behaviour. Here we explore the impact of one ordering constraint, spatial embedding, on the dynamical complexity of networks. We apply a measure of functional complexity derived from information theory to a set of spatially embedded network models in order to make some preliminary characterisations of the contribution of space to the dynamics (rather than mere structure) of complex systems. Although our measure of dynamical complexity hinges on a balance between functional integration and segregation, which seem related to an understanding of the small-world property, we demonstrate that smallworld structures alone are not enough to induce complexity. However, purely spatial constraints can produce systems of high intrinsic complexity by introducing multiple scales of organisation within a network.
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Published date: 2007
Additional Information:
Event Dates: September 10-14, 2007
Venue - Dates:
The 9th European Conference on Artificial Life, Lisbon, Portugal, 2007-09-10 - 2007-09-14
Keywords:
complexity, networks, information theory, theoretical neuroscience
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 264282
URI: http://eprints.soton.ac.uk/id/eprint/264282
PURE UUID: b5d28369-96e7-4646-b19e-a226a05fa679
Catalogue record
Date deposited: 07 Jul 2007
Last modified: 14 Mar 2024 07:46
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Contributors
Author:
Christopher L Buckley
Editor:
Fernando Almeida e Costa
Editor:
Luis M. Rocha
Editor:
Ernesto Costa
Editor:
Inman Harvey
Editor:
António Coutinho
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