Explainable Planning for Hybrid Systems

Researchers present explainable AI planning (XAIP) for hybrid systems, addressing a critical challenge in autonomous technologies. As AI-driven planning becomes essential in safety-critical domains—from autonomous vehicles to healthcare and smart grids—the ability to explain system decisions grows increasingly vital. This work advances interpretable planning methods that accurately represent real-world problems, bridging the gap between powerful automated planners and human understanding in...