AINeutralarXiv – CS AI · 10h ago6/10
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Hierarchical Causal Abduction: A Foundation Framework for Explainable Model Predictive Control
Researchers present Hierarchical Causal Abduction (HCA), a framework that makes Model Predictive Control decisions interpretable by combining physics-informed reasoning, optimization evidence, and causal discovery. The method achieves 53% higher explanation accuracy than existing approaches across industrial control applications, addressing a critical barrier to deploying AI in safety-critical infrastructure.