Infrastructure systems play a crucial role in delivering social and economic wellbeing but radical transformation is required to ensure their sustainability and resilience to social and environmental change. This is particularly important in cities where infrastructure is most dense and interdependencies between infrastructures, economies and society are most profound. However, taking decisions to transform urban infrastructure is extremely difficult because it is a highly complex socio-technical system; there are many, profound uncertainties in both how the physical infrastructure will change but also in how people make decisions; and there isn’t one organisations responsible for its transformation.

Because of this we need an approach which incorporates decisions taken by multiple actors, at multiple levels and in different infrastructure systems; addressing the links between decision makers, not just economic and technical links between infrastructure systems. A number of approaches exist, which aim to help decision makers to understand and manage deep uncertainties associated with long-term decisions in complex systems, which go beyond classical risk assessment (often referred to as Decision Making Under Deep Uncertainty or DMDU approaches – http://www.deepuncertainty.org/). These approaches offer real advantages in enabling (virtual) experimentation and building robustness or flexibility, which are crucial to accommodate the nature of deep uncertainty.

However, most approaches and supporting models assume that there is one decision maker with clearly defined objectives and stable preferences. The need for co-ordinated action from decision makers with differing motivations and agency, and the influence of the institutional, organisational and individual context on decision making processes, are rarely taken into account when developing or applying decision support tools.

This project will develop new approaches to capture the benefits that DMDU tools offer but which are more relevant and applicable to decision makers in reality and which can reflect the multi-actor context of infrastructure decision making.