Seemingly very different complex systems may actually display the same kind of behavior. For instance, so-called ‘criticality’ is a useful type of instability to rapidly respond to external stimuli in the brain, gene-regulatory networks, bacterial colonies, and the flocking of birds, among others. From this the picture emerges that the mechanistic details of complex systems may be irrelevant for generating such cross-domain phenomena as criticality. However, the young field of complexity science currently lacks a unified framework to study emergent phenomena without recourse to studying mechanistic details of particular complex systems, which complicates the matter and limits the rates of scientific progress. Information theory has already solved a similar problem in communication science a few decades ago, for which it was originally created. Here we argue that information theory – or an appropriately generalized version – may bring a similar revolution in the form of a unified theoretical framework in complexity science.
I also wrote an introductory page about information synergy.
Recent and current.
DynaNets Project, EU FP7 FET Open, 2009—2012.
Sophocles Project, EU FP7 FET Proactive, 2013—2016.
Topdrim Project, EU FP7 FET Proactive, 2013—2016.
Awarded to Linda Geerligs for a collaboration on information synergy in fMRI recordings, 2016—2017.
ZonMw Grant 531003015 ("DiNAMICS"), led by Karien Stronks (AMC), on understanding fundamental causes and effects of socio-economic inequalities in health using a systems science approach. 2018—2022.
RIEC grant (1.2M), led by myself, Paul Duijn, and Thijs Vis, on analyzing police and intelligence network data for information positions, driver positions, and value chains. 2019—2023.