Causal Atlases from Entropic Inference: Bayesian Networks Beyond Optimal DAGs

arXiv·low signal

This paper introduces 'causal atlases' derived via entropic inference, moving beyond single optimal-DAG Bayesian networks to represent richer causal structure in complex systems. Robust causal modeling underpins agents that must reason about interventions and consequences. Niche but relevant to research and scientific-discovery agents.