The focus of the project is not on developing realistic applications but on Complexity Science modelling methods and tools for socio-technical systems. However modelling requires scenarios to be used as case studies. Such scenarios need to be realistic for two reasons. First, without realistic scenarios, it is impossible to assess the quality of our methods, tools and most of all approaches to prediction and predictability. Second, it is only with realistic scenarios that the project can result in useful recommendation and guidelines for policy makers and industrial decision makers. Our definition of ‘realistic’ does not imply a restriction to systems that are currently really deployed or even likely to be deployed soon on a large scale in the specific case studies. While the initial iteration of the investigation will start with such systems, overall the project will focus on ambient-intelligence based socio-technical scenarios that

• are large and complex enough to display properties and phenomena interesting from the Complexity Science point of view,
• are based on components and technologies currently demonstrated in the lab,
• provide functionality that would be useful from the point of view of the specific case studies under investigation.

In particular, we consider two specific case studies: a transportation scenario, and a disaster/emergency scenario.