2 papers
cs.RO2026
UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning
Haoyuan Deng, Yitong Gao, Yudong Lin +3
Human-in-the-loop reinforcement learning (HiL-RL) has emerged as an effective paradigm for real-world robotic manipulation, enabling online policy improvement with human guidance.…
cs.RO2026
E2HiL: Entropy-Guided Sample Selection for Efficient Real-World Human-in-the-Loop Reinforcement Learning
Haoyuan Deng, Yudong Lin, Yuanjiang Xue +5
Human-in-the-loop guidance has emerged as an effective approach for accelerating online reinforcement learning (RL) in real-world manipulation. However, existing human-in-the-loop…