AGILE

The AGILE project develops new tools and methodologies for understanding, anticipating, and managing High Impact Low Probability (HILP) events. This is crucial because new and emerging risks caused by climate change, cyber threats, infectious diseases and terrorism have changed the risk landscape for unexpected events and call for better disaster risk management. While risk-based approaches remain a "gold standard" for the evaluation of well-characterized threats, they fall short in dealing with "High Impact Low Probability" (HILP) events. Within the project, we develop a reference library and knowledge base. From there, we leverage the power of AI and machine learning to understand the patterns that drive the occurrence of extreme disasters. To better prepare for disasters, we also co-design a new stress testing methodology to support decision-makers. By using methods from decision-theory we aim to understand crucial intervention points and coordination mechanisms to avoid that events spiral out of control.