AI Lab Seminar | Complexity, Networks and Systems Thinking

Complex Systems exhibit emergent system-wide properties that cannot be deduced from the behavior of their components, e.g., the whole is greater than the sum of its parts. Modern science has developed sets of tools that allow tackling complex challenges where interdependencies play a key role. Here, we provide an overview of the above mentioned techniques and show that the use of network and data sciences and mathematical modeling could provide novel insights and new perspectives to deal with scenarios in which a given system is subject to multiple -both in time and space- stresses. To illustrate the potentiality of the methodologies discussed, we present a specific application: how to optimize the distribution of individuals in tasks, or clients to portfolios, given a set of constraints?

Seminar held by

Yamir Moreno (PhD in Physics, 2000) is the Director of the Institute for Biocomputation and Physics of Complex Systems and Professor of Physics at the University of Zaragoza