Abstract
In this paper, we show that the theory of information offers some tools to detect changes in the interaction topology of a dynamical system defined on a graph. As an illustrative example, the system we consider is a probabilistic voter model defined on a scale-free network. We show that, using time-delayed mutual-information, the interaction topology of an unknown graph can be reconstructed to some level. We apply this approach on a sliding time window to detect possible changes in the interaction topology over time.
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Toupance, PA., Chopard, B., Lefèvre, L. (2021). Detection of Topology Changes in Dynamical System: An Information Theoretic Approach. In: Gwizdałła, T.M., Manzoni, L., Sirakoulis, G.C., Bandini, S., Podlaski, K. (eds) Cellular Automata. ACRI 2020. Lecture Notes in Computer Science(), vol 12599. Springer, Cham. https://doi.org/10.1007/978-3-030-69480-7_4
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