Cross-Disciplinary Views on Modelling Complex Systems Emma Norling 1 , Craig R. Powell 2 , and Bruce Edmonds 1 1 Centre for Policy Modelling Manchester Metropolitan University norling@acm.org, bruce@edmonds.name 2 Theoretical Physics The University of Manchester craig.powell@manchester.ac.uk Abstract. This paper summarises work within an interdisciplinary col- laboration which has explored different approaches to modelling complex systems in order to identify and develop common tools and techniques. We present an overview of the models that have been explored and the techniques that have been used by two of the partners within the project. On the one hand, there is a partner with a background in agent-based social simulation, and on the other, one with a background in equation- based modelling in theoretical physics. Together we have examined a number of problems involving complexity, modelling them using differ- ent approaches and gaining an understanding of how these alternative approaches may guide our own work. Our main finding has been that the two approaches are complimentary, and are suitable for exploring different aspects of the same problems. 1 Introduction The NANIA (Novel Approaches to Networks of Interacting Autonomes) project has brought together researchers from a variety of fields who are studying com- plex systems in which stability, robustness and fitness for purpose emerges through the interaction of evolving, interacting networks of diverse ‘autonomes’ (where ‘autonome’ is a term adopted by the project to refer to any interacting multi-state system which can encompass cellular automata, agent, organisms or species). The aim has been to determine global principles with which to describe or control complex autonome systems – an ambitious goal, which was acknowl- edged from the start was only likely to be partially fulfilled. In this paper, the work of two groups within the project is examined, par- ticularly the attempts that have been made by the group members to tackle common problems. On the one side, we have a group with a background in agent-based social simulation. On the other, a group with a background in the- oretical physics. The application areas studied by both groups are diverse, and the approaches to modelling have been quite different, with one group starting from the agent-based approach, and the other from an equation-based, or system