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cs.LG2026
Representation Learning Enables Scalable Multitask Deep Reinforcement Learning
Johan Obando-Ceron, Lu Li, Scott Fujimoto +3
Scaling reinforcement learning (RL) to diverse multitask settings remains a central challenge. While recent advances in model-based RL achieve strong performance, they rely on plan…
cs.LG2023
Distance-rank Aware Sequential Reward Learning for Inverse Reinforcement Learning with Sub-optimal Demonstrations
Lu Li, Yuxin Pan, Ruobing Chen +4
Inverse reinforcement learning (IRL) aims to explicitly infer an underlying reward function based on collected expert demonstrations. Considering that obtaining expert demonstratio…