JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.
Composable safety-filter and auditability layer for tensor-parallel reinforcement learning. CBF safety filters, watchdog registries, pre-registration artifacts, failure forensics.
🔥 Datasets and env wrappers for offline safe reinforcement learning
🚀 A fast safe reinforcement learning library in PyTorch
🤖 Elegant implementations of offline safe RL algorithms in PyTorch
