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Spatial cognitive simulation using informed virtual geographic environments

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In this paper, we address two challenging issues underlying spatial cognitive simulation using software agents immersed in Virtual Geographic Environments (VGE). First, the way to describe virtual VGE models using accurate spatial decomposition approaches structured using graph theory techniques. Second, the use of graph abstraction techniques to realistically support advanced navigation and path planning capabilities for software agents | International Journal of Computer Networks and Communications Security VOL. 4, NO. 8, AUGUST 2016, 242–251 Available online at: www.ijcncs.org E-ISSN 2308-9830 (Online) / ISSN 2410-0595 (Print) Spatial Cognitive Simulation Using Informed Virtual Geographic Environments Mehdi Mekni St. Cloud State University, Department of Computer Science & Information Technology, St. Cloud, Minnesota, United States mmekni@stcloudstate.edu ABSTRACT In this paper, we address two challenging issues underlying spatial cognitive simulation using software agents immersed in Virtual Geographic Environments (VGE). First, the way to describe virtual VGE models using accurate spatial decomposition approaches structured using graph theory techniques. Second, the use of graph abstraction techniques to realistically support advanced navigation and path planning capabilities for software agents. In order to illustrate our contributions to the growing field of spatial simulations, we present and discuss a case study involving an urban VGE model populated with agents who autonomously and differently interact with multiple abstractions of the same physical environment. Keywords: Virtual Geospatial Environments, Multi-Agent Systems, Spatial Cognition, Environment Abstraction. 1 INTRODUCTION During the last decade, the Multi-Agent GeoSimulation (MAGS) approach has attracted a growing interest from researchers and practitioners to simulate phenomena in a variety of domains including traffic simulation, crowd simulation, urban dynamics, and changes of land use and cover, to name a few [1]. Such approaches are used to study phenomena (i.e. car traffic, mobile robots, sensor deployment, crowd behaviors, etc.) involving a large number of simulated actors (implemented as software agents) of various kinds evolving in, and interacting with, an explicit description of the geographic environment called Virtual Geographic Environment (VGE) [15]. A critical step towards the development of MAGS is the .

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