Safe Flow Q-Learning: Offline Safe Reinforcement Learning with Reachability-Based Flow Policies

Researchers introduce Safe Flow Q-Learning (SafeFQL), a new offline safe reinforcement learning method that combines Hamilton-Jacobi reachability with flow policies for safety-critical real-time control. The method achieves better safety performance with lower inference latency compared to existing diffusion-based approaches, making it more suitable for real-time deployment.