The paper derives theoretical connections between skill disentanglement metrics and downstream task adaptation cost, and proposes Wasserstein-based objectives that can discover more (or all) optimal initial skills.
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Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
The paper derives theoretical connections between skill disentanglement metrics and downstream task adaptation cost, and proposes Wasserstein-based objectives that can discover more (or all) optimal initial skills.