The control of complex networks is of paramount importance in areas as diverse asecosystem management, emergency response and cell reprogramming. A fundamentalproperty of networks is that perturbations to one node can affect other nodes, potentiallycausing the entire system to change behaviour or fail. Here we show that it is possible toexploit the same principle to control network behaviour. Our approach accounts for thenonlinear dynamics inherent to real systems, and allows bringing the system to a desiredtarget state even when this state is not directly accessible due to constraints that limit theallowed interventions. Applications show that this framework permits reprogramming anetwork to a desired task, as well as rescuing networks from the brink of failure—which weillustrate through the mitigation of cascading failures in a power-grid network and theidentification of potential drug targets in a signalling network of human cancer.
展开▼
