A Multi-Agent Geosimulation Infrastructure for Planning

Urban planning is confronted with multifaceted complexities, related to the complex nature of phenomena, dynamics and processes it has to deal with. We argue that good tools for planning must be informed by these complexities, and therefore must have specific characteristics, in terms of modularity, flexibility, user-friendliness, generality, adaptability, computational efficiency and cost-effectiveness. In this chapter we present and try to make the case for a multi-agent geosimulation infrastructure framework called MAGI, showing how it delivers as such a tool for planning. The modelling and simulation infrastructure MAGI possesses characteristics, features and computational strategies particularly relevant for strongly geo-spatially oriented agent-based simulations. The infrastructure is composed of a development environment for building and executing simulation models, and a class library based on open source components. Differently from most of the existing tools for geosimulation, both raster and vector representation of simulated entities are allowed and managed with efficiency. This is obtained through the integration of a geometry engine implementing a core set of operations on spatial data through robust geometric algorithms, and an efficient spatial indexing strategy for moving agents.