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RS-Diffuser 提出了一种风险敏感的离线扩散规划框架，结合扩散轨迹生成和分布值批评器，通过尾部感知目标在推理时灵活调整风险偏好，在安全关键任务中提升了回报和鲁棒性。
This paper introduces a simple yet powerful methodology for Utility-Constrained MDPs (UCMDPs) that enables risk-sensitive constraints without fixing constraint limits in advance, outperforming baselines on Safety Gymnasium benchmarks.