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Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning
By: Chaitanya Kaligotla, Jonathan Ozik, Nicholson Collier, Charles M. Macal, Kelly Boyd, Jennifer Makelarski, Elbert S. Huang, Stacy T. Lindau, Volume 23 (4)
Abstract: This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. The diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is ite ...

Multimodal Evolutionary Algorithms for Easing the Complexity of Agent-Based Model Calibration
By: Juan Francisco Robles, Enrique Bermejo, Manuel Chica, Óscar Cordón, Volume ()
Abstract: Agent-based modelling usually involves a calibration stage where a set of parameters needs to be estimated. The calibration process can be automatically performed by using calibration algorithms which search for an optimal parameter configuration to obtain quality model fittings. This issue makes the use of multimodal optimisation methods interesting for calibration as they can provide diverse solution sets with similar and optimal fitness. In this contribution, we compare nine competitive multimodal evolutionary algorithms, both classical and recent, to calibrate agent-based models. We analys ...