Web: http://arxiv.org/abs/2206.07570

June 16, 2022, 1:11 a.m. | Joel Dyer, Patrick Cannon, J. Doyne Farmer, Sebastian M. Schmon

cs.LG updates on arXiv.org arxiv.org

Calibrating agent-based models (ABMs) to data is among the most fundamental
requirements to ensure the model fulfils its desired purpose. In recent years,
simulation-based inference methods have emerged as powerful tools for
performing this task when the model likelihood function is intractable, as is
often the case for ABMs. In some real-world use cases of ABMs, both the
observed data and the ABM output consist of the agents' states and their
interactions over time. In such cases, there is a …

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