Abstract
In this paper we consider a multi-cellular sensing and communication network, embedded in an ageless aerospace vehicle, that is expected to detect and react to impact location, intensity and damage over a wide range of impact energies. In particular, we investigate self-organization of impact boundaries enclosing critically damaged areas, and measure their spatiotemporal robustness. The presented quantitative information-theoretic techniques clearly identify phase transitions, separating chaotic dynamics from ordered and robust patterns.
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Foreman, M., Prokopenko, M., Wang, P. (2003). Phase Transitions in Self-Organising Sensor Networks. In: Banzhaf, W., Ziegler, J., Christaller, T., Dittrich, P., Kim, J.T. (eds) Advances in Artificial Life. ECAL 2003. Lecture Notes in Computer Science(), vol 2801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39432-7_84
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DOI: https://doi.org/10.1007/978-3-540-39432-7_84
Publisher Name: Springer, Berlin, Heidelberg
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