This project (2020-1-SE01-KA203-077872) has been funded with support from the European Commission. This web site reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Taming Complexity: From Network Science to Controlling Networks

Area
Natural Scienc

Thematic Area
Artificial intelligence (computer science and mathematics), Simulations of physical behaviors (computer science, biomedicine, mathematics, mechanics)

Description
The lecture presents a method on identifying the controlling nodes in the complex systems presented as networks. The lecturer mentions that although the engineers work with the direct problem and design a complex system, scientists in other disciplines, business stakeholders try to understand complex systems as networks and to identify parts which govern the behavior of the system. The theoretical conditions to define whether the system is controllable were presented. However, these conditions cannot be used in practice because of the size. Thus, the steps based on known matching algorithm were presented to identify the controlling nodes. Analysis of network that controls C.Elegans locomotion led to assumptions which were verified by the biological experiments.


Points of Strength
The strength of this lecture is the synthesis of mathematical algorithms, complex system as network, and biological experiments.