Localized Dynamics-Aware Domain Adaption for Off-Dynamics Offline Reinforcement Learning

Researchers introduced Localized Dynamics-Aware Domain Adaptation (LoDADA) to improve off-dynamics offline reinforcement learning by addressing dynamics mismatches at a cluster level rather than globally or per sample. This approach allows for more efficient and effective reuse of source data, offering significant performance gains over existing methods while reducing computational costs.

Read the full article at arXiv cs.LG (ML)

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