ABSTRACT
As part of the long term quest to develop more disaggregate, temporally dynamic models of spatial behaviour, micro-simulation has evolved to the point where the actions of many individuals can be computed. These multi-agent systems/simulation (MAS) models are a consequence of much better micro data, more powerful and userfriendly computer environments, and the generally recognised need in spatial science to model temporal processes. In this chapter, we develop a series of multi-agent models which operate in cellular space. These demonstrate the well-known principle that local action can give rise to global pattern but also how such pattern emerges as a consequence of positive feedback and learned behaviour. We first summarise the way cellular representation is important in adding new process functionality to GIS, and the way this is effected through ideas from cellular automata (CA) modelling. We then outline the key ideas of multi-agent simulation. To set the scene, we discuss models based on agents whose purpose is to explore geographic space, and then illustrate these notions with three applications.
