arXiv Machine Learning
Three Steps at a Time: Learning Representations from Action Sequences in Contrastive RL
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Hugging Face Trending Papers
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Offline RL with Hierarchical Action Chunking
Offline goal-conditioned reinforcement learning (RL) holds the promise of learning general-purpose policies from static datasets. However, scaling these methods to long-horizon tasks remains a challenge due to the curse of horizon, where value estimation errors can compound through long chains of bootstrapped Bellman backups.