Explainable Causal Reinforcement Learning for smart agriculture microgrid orchestration with zero-trust governance guarantees

This article details a developer's epiphany while debugging a black-box Reinforcement Learning agent failing to synchronize smart agriculture microgrids. The realization that the agent lacked causal understanding led to exploring Explainable AI and causal inference frameworks to prevent cascading power failures.