GeoGraph Computational Laboratories

Human interactions of all kinds are increasingly structured by networks of transportation and communication spatial technologies. Yet our tools to model, understand, and predict dynamic human interactions and behavior on spatial networks and geographic landscapes have lagged far behind. Even recent progress in social network modeling has not yet offered us any capability to model dynamic processes among mobile agents who interact at all scales on small-world and scale-free geographic networks. Computational laboratory modeling of dynamic human interactions on richly structured landscapes is important for understanding the sometimes counter-intuitive dynamics of such loosely coupled systems of non-linear interactions. Deeper understanding is more important than ever not only because the stakes are so much higher, but because we now have greater strategic control over the structural design and therefore the effects of our networks of organizational and spatial technologies.

Our GeoGraph extensions to the RePast agent-based simulation platform support models in which mobile agents interact on network and other interesting geographic landscapes. GeoGraphs contribute to spatially integrated social science research by allowing us to develop models that include not only heterogeneous site-specific characteristics, but also the complementary organizational and spatial-technology networks that mediate each agent's mobility, communications, and encounters. GeoGraph computational laboratory tools are designed to support controlled experiments for agent-based geographic science through their ability to generate richly structured parameterized families of synthetic geographic landscapes or of complementary GIS-derived geographic landscapes. GeoGraphs support building and testing simulation models grounded in interesting spatial structures such as spatial small-worlds, geographic scale-free networks, hybrids between the two, or GIS representations of real-world landscapes; homogeneous or heterogeneous distributed mobile agents, including their social networks; and context-specific behaviors.

Preliminary GeoGraph Models

GeoGraph models have been developed for:

• epidemiological studies of infectious disease transmission among mobile agents,
• epidemiological studies of domestic US malaria risk in conjunction with climate models of global warming,
• settlement patterns, sector migration, and long-run regional development,
• the effects of globalization processes on both epidemiology and regional development,
• visualization and modeling of dynamic social networks and spatial games on geographic landscapes, and
• civil violence and effective strategies for preventing or controlling riots and related civil unrest.

GeoGraph Teams of Mobile Heterogeneous Agents

GeoGraphs have a series of classes that allow for the creation and observation of teams of agents that behave as social hierarchies. For each layer of responsibility in the organization, there can be a specific type of "Hierarchy Agent" that fits that role. The simulation can show visualizations of these communication links in a variety of contexts, ranging from lines drawn between the members of the group, to group coloration, to tree views that show the hierarchy by group member name, message, and status. These displays are linked; selecting an agent in one display highlights the same agent in different displays.

GeoGraph Usage

GeoGraphs are designed from the ground up to handle the additional levels of complexity involved in creating, viewing, and interacting with such hierarchical simulations. GeoGraphs do this by breaking the creation and simulation process into three distinct stages: Creation, Modification, and Simulation. XML files containing progressively more sophisticated representations are initialized and then pipelined through the process, until they are ready for the simulation to read them in and run. In this manner, the complexity of the modelÕs development is constrained to small, understandable steps. For example, a simple population of generic agents is initially created through an interactive tool. Later, that population of agents is modified and extended through the use of subsequent interactive tools until the user has created a hierarchal network of agents, each with its own tasks and responsibilities, where each has the capability to move through either an abstract or a GIS-derived urban or regional landscape, and to interact with other agents in the landscape.

Once the file is loaded into the simulation, the user can fly through the running simulation, select individual agents to view their internal states, and view the interaction of the agents with each other or with their environment by choosing which landscape they wish to view through the use of dropdown menus. Finally, data from the simulation is displayed as charts or recorded to text files for further analysis.