Adapting RFRL objectives as auxiliary tasks with preference-guided exploration outperforms prior MORL methods in performance and data efficiency on MO-Gymnasium tasks.
Zero-shot whole-body humanoid control via behav- ioral foundation models
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A Reward-Free Viewpoint on Multi-Objective Reinforcement Learning
Adapting RFRL objectives as auxiliary tasks with preference-guided exploration outperforms prior MORL methods in performance and data efficiency on MO-Gymnasium tasks.