Causal Inference Robotics

Applying causal reasoning to robot learning: identifying cause-effect relationships (rather than correlations) between observations and outcomes. Causal inference helps robots generalize to new environments by learning causal structure (e.g., object color causes visibility but not graspability). Methods include causal discovery, do-calculus, and counterfactual reasoning.