 DAGs enable one to systematically map the relationship between causal hypotheses and joint probability distributions. They overlap with and build on techniques in the literature on probabilistic causality, but provide significantly stronger tools and results. See the entries on  causal models,  causation and manipulability and  counterfactual theories of causation  for detailed introductions to causal inference with DAGs.