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 geo-metrically 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 seman-tic 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.

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