Strategic Aim: Developing modelling, simulation and analytical methods for understanding large complex systems and ensuring their resilience through new approaches to optimisation, decision-making and control and human-like intelligence.
Uncertainties have always existed in areas ranging from the nature of material bonding to the unpredictability of the weather. Humans in the loop have forever added to the uncertainty – what are they saying, what did they mean to say and what is their real intent? The challenge now is the increasingly constrained conditions under which these uncertainties must be managed, as we demand greater efficiency and performance from ever more complex and interconnected systems. For example, there are drives to reduce conservative structural safety factors, adopt leaner manufacturing, and reduce the levels of human supervision and control. All these initiatives can yield very positive results, but they also generally limit the ability of the associated systems to absorb variations naturally, which heightens the risk of these systems failing. There is a growing urgency to find a new understanding of uncertainty and risk, so that we can develop deliberate strategies for increasing resilience of the systems on which we depend. Solutions draw on the latest advances in signal processing, control and human-like computing to find the intelligent, adaptive, robust approaches needed.
The theme ultimately aims to create a new understanding and a practical toolkit for engineering systems that can deliver solutions with assured levels of performance, reliability and resilience, while accommodating: uncertainty; incomplete knowledge; sparsity, or high volumes, of data; and humans in the loop.
The theme comprises three missions, which are detailed below with their challenges, ambitions and activities: