AINeutralarXiv – CS AI · 15h ago6/10
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Exploiting Local Dynamics Regularity for Reusable Skills in Offline Hierarchical RL
Researchers introduce CARL, a hierarchical reinforcement learning algorithm that discovers reusable skills by exploiting local dynamics regularity—the observation that similar action sequences solve similar local transitions across different contexts. When integrated with existing HRL methods like HIQL, CARL demonstrates improved performance on complex tasks and meaningful skill clustering in humanoid environments.