In this topical review, we present a brief overview of the different methods and measures to
detect the occurrence of critical transitions in complex systems. We start by introducing the …

Many systems in various scientific fields like medicine, ecology, economics or climate
science exhibit so-called critical transitions, through which a system abruptly changes from …

We study the multiscale structure of the Jain–Krishna adaptive network model. This model
describes the co-evolution of a set of continuous-time autocatalytic ordinary differential …

Studies on the possibility of predicting critical transitions with statistical methods known as
early warning signals (EWS) are often conducted on data generated with equation-based …

We present results of attempts to expand and enhance the predictive power of Early
Warning Signals (EWS) for Critical Transitions (Scheffer et al. 2009) through the deployment …

We trained a long-short-term-memory (LSTM)-neural network on time series generated with
an agent-based model that was designed to differentiate the drivers of its dynamics into …

In this topical review, we present a brief overview of the different methods and measures to
detect the occurrence of critical transitions in complex systems. We start by introducing the …

Résumé Les systèmes réels subissant des perturbations par l'interaction avec leur
environnement sont susceptibles d'être entraînés vers des transitions irréversibles de leur …

In the Digital Age companies and customers are increasingly embedded in rapidly
coevolving ecosystems characterized by high-speed digitally connected information flows …

This research takes place in an emerging paradigm of social computation that we name
social crowdsourcing communities (SCCs). These are moderated online communities where …