Data-driven discovery and control of multi-scale interacting artificial agent systems

The main goal of the project consists in developing sustainable and flexible next-generation frameworks for data-driven modelling, optimization, and simulation of multi-scale interacting agent systems of utmost importance in industrial applications and socio-economic life. As scientific aim, we investigate several approaches relying on learning-based mathematical methods to build and control physical data-driven models. The proposal is timely since learning-based methods have recently attracted the attention of the scientific community to fully exploit HPC hardware and the abundance of data, demanding new unifying concepts to address grand challenges.