Semantically-Enhanced Virtual Geographic Environments for Multi-Agent Geo-Simulation

Multi-Agent Geo-Simulation (MAGS) is a modeling and simulation paradigm which aims to study various phenomena in a variety of domains involving a large number of heterogeneous actors (implemented as software agents) evolving in, and interacting with, a Virtual representation of the Geographic Environment (VGE). A critical step towards the development of advanced MAGSs is the creation of semantically-enhanced and geometrically accurate virtual geographic environments called Informed VGE (IVGE). In this chapter we propose a novel approach to automatically build an accurate IVGE using an exact decomposition of realistic spatial data provided by Geographic Information System (GIS). The IVGE model relies on a hierarchical topologic graph structure built using geometric, topologic, and semantic abstraction processes and enhanced by spatial semantic information represented using Conceptual Graphs (CGs). We demonstrate how we take advantage of the IVGE description in order to provide an accurate 2D/3D visualization tool of the space partitioning as well as to support situated reasoning such as path planning with respect to both agents and environments’ characteristics.