Abstract: The present invention relates to a method for the automatic identification of at least one informative data filter from a data set that can be used to identify at least one relevant data subset against a target feature for subsequent hypothesis generation, model building and model testing. The present invention describes methods, and an initial implementation, for efficiently linking relevant data both within and across multiple domains and identifying informative statistical relationships across this data that can be integrated into agent-based models. The relationships, encoded by the agents, can then drive emergent behavior across the global system that is described in the integrated data environment.

Abstract: The present invention provides a means for performing scalable, computationally efficient and rapid simulations of complex or complex adaptive systems realized through the dynamic interaction of multiple modeling components to generate outputs suited to decision support, analysis and planning. In the context of disease modeling, these outputs can be used for analyzing the impact of disease and the potential value of the use of pharmaceutical and non-pharmaceutical interventions.