Approaches for resolving the dilemma between model structure refinement and parameter calibration in agent-based simulations

摘要

Agent-based simulations form a valuable tool for learning about real world societies and global behaviors of systems emerging from microscopic relationships. Calibration of model parameters for detailed agent-based models is a big problem for standard calibration techniques, due to the large parameter search spaces, long simulation run times, uncertainties in the structural model design and different observation levels upon which the model needs to be calibrated. In this paper we propose several methods to improve the calibration process of agent-based simulations.