2025
Towards Safe Reinforcement Learning with Reduced Conservativeness: A Case Study on Drone Flight Control
IROS 2025
Incorporating formal methods into reinforcement learning (RL) has the potential to result in the best of both worlds, combining the robustness of formal guarantees with the adaptability and learning capabilities of RL, though careful design is needed to balance safety and exploration. In this work,