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News/Sample-Efficient Neurosymbolic Deep Reinforcement Learning
arxiv
PublishedApril 13, 2026 at 4:00 AM
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Sample-Efficient Neurosymbolic Deep Reinforcement Learning

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Publisher summary· verbatim

arXiv:2601.02850v2 Announce Type: replace Abstract: Reinforcement Learning (RL) is a well-established framework for sequential decision-making in complex environments. However, state-of-the-art Deep RL (DRL) algorithms typically require large training datasets and often struggle to generalize beyond

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