Complex networks of dynamical agents are widely used to model the behavior of large physical or virtual systems. Unfortunately, due to the often abstract nature of such networks or the size thereof, it is sometimes difficult to assess correctly their structure and parameters. With the ever increasing amount of data accessible nowadays, it is natural to attempt to recover structural information of the system from measurements.
Altogether, there are two overlapping questions that we would like to treat in this symposium:
* What networks characteristics can be recovered from time-series measurements of its agents?
* How to identify and locate disturbances from time-series measurements?
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