A framework for the optimization and analysis of agent-based models

OptAgent is a new framework which enhances the practical applications of agent-based models by giving them an optimization and analysis capability. Embedding such an ability within agent-based systems greatly expands their usefulness and applicability. Developed through an Army Research Office SBIR Phase II grant, OptAgent is built on our existing OptQuest engine to create a system that can be used alike with agent-based and other complex simulation models. Important components of the OptAgent system include new predictors based on Markov blankets and satisfiability data mining that speed the search for high quality solutions. OptAgent is structured to assist with the verification, validation, and accreditation process for a new model and can also be used to enhance the analysis accomplished with a more mature model.