Adaptive networks

Adaptive networks refer to a class of network models where the structure co-evolves with (or in response to) a dynamical process occurring on the network. Think for example about a teacher staying home sick, such that all connections with students are rewired to a substitute teacher. The network is adapting to the contagion dynamics and trying to avoid further spread.

In this setting, dynamical correlations between the states of different nodes are critical. Classic mean-field approach that fail to take those into account will fail to capture the adaptive mechanisms! Master equations can help, but given that networks tend to be large and complex, approximate master equations are the best tool for the job!

Adaptive networks with node-based AMEs

Coming soon! How much better are AMEs than the pairwise description used in The effect of a prudent adaptive behaviour on disease transmission [Scarpino et al., 2016]? We will soon see.