Abstract
A new perspective on analysis of large-scale Multi-Agent Dynamic Systems is presented. The aim is to capture the global trends at a glance, by the use of dynamic data mining techniques, which group agents according to similar characteristics or behavior, measuring and recording how the different trends evolve through time. This methodology is presented and an example with a simulated dynamic Multi-Agent System is included.
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