RobustRLlib: A Unified Library and Benchmark for Robust Reinforcement Learning Algorithms

RobustRLlib is a unified library and benchmark that consolidates 17 robust reinforcement learning algorithms, providing a single interface to improve reusability. It includes an evaluation platform covering diverse real‑world shifts and advanced tasks such as humanoid and vision‑language‑action scenarios. Systematic tests across 273 perturbation configurations map the current capabilities of robust RL methods, highlighting both effective areas and remaining robustness gaps.

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• reinforcement-learning
• multimodal
• benchmarks