3 papers
cs.RO2026
ConceptTree: Bringing Semantic Transparency to Black-Box Decision Making for Robotic Manipulation
Yongyan Wen, Feifan Liu, Jinyi Chen +3
Establishing interpretable decision-making processes in long-horizon robotic manipulation is critical for enabling reliable human oversight and intervention. However, existing appr…
cs.LG2026
Curriculum reinforcement learning with measurable task representation learning
Yongyan Wen, Siyuan Li, Mingjian Fu +3
In curriculum reinforcement learning (CRL), an agent incrementally accumulates knowledge over a sequence of tasks (i.e., a curriculum), and the learning process is aimed at using t…
cs.LG2024
SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks
Yongyan Wen, Siyuan Li, Rongchang Zuo +3
Deep reinforcement learning (DRL) has achieved remarkable success in various research domains. However, its reliance on neural networks results in a lack of transparency, which lim…