AI-Assisted Discovery of Quantitative and Formal Models in Social Science. (arXiv:2210.00563v2 [cs.SC] UPDATED)

In social science, formal and quantitative models, such as ones describing
economic growth and collective action, are used to formulate mechanistic
explanations, provide predictions, and uncover questions about observed
phenomena. Here, we demonstrate the use of a machine learning system to aid the
discovery of symbolic models that capture nonlinear and dynamical relationships
in social science datasets. By extending neuro-symbolic methods to find compact
functions and differential equations in noisy and longitudinal data, we show
that our system can be …

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