Three Steps at a Time: Learning Representations from Action Sequences in Contrastive RL
This work extends contrastive reinforcement learning (CRL), a prototypical self-supervised method, to operate over action chunks, and finds that this results in large, pervasive gains across established offline and online benchmarks: +31.7% and +93.1% across 18 and 11 environments respectively.
Michal Korniak, Kamil Dybek, Benjamin Eysenbach et al.
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