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cs.LG2024
Reward-free World Models for Online Imitation Learning
Shangzhe Li, Zhiao Huang, Hao Su
Imitation learning (IL) enables agents to acquire skills directly from expert demonstrations, providing a compelling alternative to reinforcement learning. However, prior online IL…
cs.LG2024
Augmenting Offline Reinforcement Learning with State-only Interactions
Shangzhe Li, Xinhua Zhang
Batch offline data have been shown considerably beneficial for reinforcement learning. Their benefit is further amplified by upsampling with generative models. In this paper, we co…