Abstract
Agent-based models simulate simultaneous actions and interactions of multiple agents, in an attempt to re-create and predict the appearance of complex phenomena. We propose to use global sensitivity analysis as a tool for analyzing and evaluating agent-based models. A general approach for applying the global sensitivity analysis to agent-based models is presented and tested on the example of a socio-cultural agent-based model we developed earlier [45]. We identify the most significant parameters in the model and uncover their contributions to the outputs of interest. Methodology of model reduction for agent-based models is discussed and demonstrated for the aforementioned model.
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