Emergency Medical Services (EMS) are vital to public health and safety, providing life-saving care before patients reach a hospital. Yet EMS systems operate under intense pressure, making rapid decisions about ambulance deployment, dispatch, and transport in the face of constant uncertainty—from unpredictable emergency call volumes to traffic conditions. These decisions are often made using simple, rule-based approaches that can fall short under real-world complexity.