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DROP: Dynamics-aware representation learning for offline reinforcement learning
DOI:10.1016/j.asoc.2025.114525.png)
Abstract
En 中文
• DROP learns dynamics-aware joint state–action representations for offline RL. • Jointly predicts rewards and next-state embeddings to capture transition structures. • Incorporates behavior cloning regularization directly into Q-function learning.
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W

