Improving Offline Goal-Conditioned Reinforcement Learning via Selective Reward Stimulation
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arXiv:2609.19414v1 Announce Type: new Abstract: Goal-conditioned reinforcement learning aims to learn policies that reach specified goals, but remains challenging in offline settings with sparse rewards and long-horizon dependencies. In such settings, goal-completion information can be temporally d…
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- 2026-09-18 04:00 · arXiv cs.LG
Improving Offline Goal-Conditioned Reinforcement Learning via Selective Reward Stimulation