Complexity in Foresight: experiences with INTERSECTIONS: an agent-based simulation workbench to help achieve adaptiveness in strategic planning

“Complexity in Foresight” is a new synthetic paradigm that crosses areas in strategic planning and the complexity sciences. It connects the fields of agent-based simulation and complex adapative systems, and provides the overall blueprint for the construction of a new generation of toolkits. The plan is ambitious: to help achieve adaptiveness in strategic planning. My proposal is to start the construction of an agent-based simulation workbench with the ingredients: would-be worlds, building-block approaches and learning-action networks. The workbench will be designed to support learning-action networks; the informal networks of scientists, policy-makers and stakeholders that have a critical role for sustainable development. Their interactions and learning will be facilitated by would-be worlds; agent-based simulation models that function as “laboratories”, which the used to generate crude images of transitional change. These images will be treated as thought experiments, designed to make it easier for the planners to switch between observable realities and possible realities. Building-block approaches help to organize the modeling, experimentation and learning processes in a very flexible way, so that the overall process becomes adaptive. In this thesis I present the “Framework for Synthesis” designed to facilitate a unifying process to the development and use of would-be worlds. I build tools and methods and integrate them into the “INTERSECTIONS” workbench. I apply different combinations of these tools and methods in two case studies. I evaluate the potential usefulness of the Framework for Synthesis to support learning-action networks. I present the Framework on the CD-ROM included with this thesis, so that the reader can interact with the tools and methods

Modelling socio-technical transition patterns and pathways

We report on research that is developing a simulation model for assessing systemic innovations, or 'transitions', of societal systems towards a more sustainable development. Our overall aim is to outline design principles for models that can offer new insights into tackling persistent problems in large-scale systems, such as the European road transport system or the regional management of water resources. The systemic nature of these problems is associated with them being complex, uncertain and cutting across a number of sectors, and indicates a need for radical technological and behavioural solutions that address changes at the systems level rather than offering incremental changes within sub-systems. Model design is inspired by recent research into transitions, an emerging paradigm which provides a framework for tackling persistent problems. We use concepts from the literature on transitions to develop a prototype of a generic 'transition model'. Our prototype aims to capture different types of transition pathways, using historical examples such as the transition from horse-drawn carriages to cars or that from sailing ships to steam ships. The model combines agent-based modelling techniques and system dynamics, and includes interactions of individual agents and sub-systems, as well as cumulative effects on system structures. We show success in simulating different historical transition pathways by adapting the model's parameters and rules for each example. Finally, we discuss the improvements necessary for systematically exploring and detailing transition pathways in empirical case-study applications to current and future transitions such as the transition to a sustainable transport system in Europe