Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models

A primary goal of science is to learn mechanistic world models from limited experimental data, both to explain observations and to predict novel interventions. We introduce the Model Discovery Agent (MDA), which combines LLM proposals for $\mathcal M$-open model discovery, experiment design based on