4 papers · 1 filter
TOUR: A Trajectory-Level Unlearning Benchmark for Offline Reinforcement Learning
Chaofan Pan, Lingfei Ren, Xiangyu Jiang +6
Offline Reinforcement Learning (RL) agents are trained on fixed behavioral trajectories, which makes trajectory-level deletion important when selected data must be removed after tr…
A Survey of Continual Reinforcement Learning
Chaofan Pan, Xin Yang, Yanhua Li +4
Reinforcement Learning (RL) is an important machine learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in this field…
Action-Adaptive Continual Learning: Enabling Policy Generalization under Dynamic Action Spaces
Chaofan Pan, Jiafen Liu, Yanhua Li +4
Continual Learning (CL) is a powerful tool that enables agents to learn a sequence of tasks, accumulating knowledge learned in the past and using it for problem-solving or future t…
Multi-granularity Knowledge Transfer for Continual Reinforcement Learning
Chaofan Pan, Lingfei Ren, Yihui Feng +4
Continual reinforcement learning (CRL) empowers RL agents with the ability to learn a sequence of tasks, accumulating knowledge learned in the past and using the knowledge for prob…