JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.

🚀 A fast safe reinforcement learning library in PyTorch

🤖 Elegant implementations of offline safe RL algorithms in PyTorch

🔥 Datasets and env wrappers for offline safe reinforcement learning

PyTorch implementation of Constrained Reinforcement Learning for Soft Actor Critic Algorithm

A Survey Analyzing Generalization in Deep Reinforcement Learning

A Multiplicative Value Function for Safe and Efficient Reinforcement Learning. IROS 2023.

Official Code Repository for the POLICEd-RL Paper: https://www.roboticsproceedings.org/rss20/p104.html

[AAAI 2024 (Oral)] Safety-MuJoCo Environments.

Correct-by-synthesis reinforcement learning with temporal logic constraints (CoRL)

Author implementation of DSUP(q) algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"

Poster about Curriculum Induction for Safe Reinforcement Learning

SAFIRL: Shielded RL with CBF/MPC on Franka-MuJoCo — reproducible training/evaluation, STL-based verification, benchmarks, Docker/CI.

[ECAI-2025] SPOWL: A JAX-based Safe RL framework that adaptively combines planning and policy learning with dynamic safety thresholds.

Blog Post about Curriculum Induction for Safe Reinforcement Learning

Official implementation of C-TRPO

sTRPO: Safe, Trust Region Policy Optimization for Constrained Reinforcement Learning

Alternative (torch) author implementation of algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"