Chinese contentRACER:用风险敏感目标与Critic一致性正则改进对抗强化学习
做强化学习的可以看看:RACER 用自适应扰动和 critic 一致性正则,解决了对抗训练里对手太狠把智能体带偏的问题,连续控制实验效果确实比老基线稳。
做强化学习的可以看看:RACER 用自适应扰动和 critic 一致性正则,解决了对抗训练里对手太狠把智能体带偏的问题,连续控制实验效果确实比老基线稳。
Compared with L2D-Pop and IFD, RACER captures instance-level expert specialization without class-identity shortcuts, a practical design for medical AI triage systems that must route chest X-rays between models and radiologists.