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Agent based models have been shown to be powerful tools in describing processes and systems centered on individual behaviors and local interactions (i.e. "bottom-up") between specific entities. Current application areas tend to be focused within the business and social science arenas, although their usefulness has been demonstrated in the modeling of various chemistry and physics-based systems. Conversely, many highly process-oriented systems, such as manufacturing environments, tend to be modeled via "top-down" methods, including discrete or continuous event simulations among others. As a result, potentially critical attributes of the entities or resources modeled with these methods (spatial properties, "learning curve" or adaptability) may not be adequately captured or developed.