The lecture by Leonhard Horstmeyer from the Medical Univerity of Vienna and CSH Vienna will take place at the Complexity Science Hub Vienna in Room 201.
If you are interested in participating, please email to email@example.com
Adaptive co-evolving dynamic networks play a key role in ecological, epidemiological, social or financial systems. In adaptive network models the node states and the network topology are dynamically coupled, i.e. they co-evolve. These models have in common that they can collapse. We would like understand these collapse transitions and their precursors in adaptive network models. Structural information about the network is of crucial importance for this task. These models differ strongly with respect to the level of aggregation at which this information is required. On one side there are systems whose collapse depends solely on a very particular network configuration and on the other side there are systems whose collapse depends on aggregated structural variables, such as the overall density of certain network motifs. In this talk I contrast two representative models that differ in this respect: The Jain-Krishna model and the adaptive SIS model.
In the first model the collapse occurs when cycles are broken. We show that this collapse can be predicted accurately purely from information of the nodes, even though it relies crucially on a particular network topology. In the second model we show that a prediction may be systematically off, even in the presence of aggregated knowledge of the network topology.