Information Processing in Dynamical Systems
Third Annual RICH Lecture

A network of dynamical units can generate a complex systemic behavior. Examples include human cognition emerging from a network of neural cells, ecosystems from food webs, and cellular regulatory processes from protein-protein interactions.

A first important question is: which agents are the ‘drivers’ of the systemic behavior? A second question is: can we detect emergent phenomena, such as susceptibility to certain perturbations while being resilient to other perturbations? We attempt to address these questions in a domain-free way using information theory.

As an example, surprising findings is that the most influential nodes are not the most well-connected or central nodes. We also find that strategic multi-interventions may be far more effective than local interventions, and that achieving tipping points may even require a sequence of interventions. These insights have important consequences for many applications. I will present work on addressing the above questions through analytical results, computational modeling, and data analysis.