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Optimistic Natural Policy Gradient: a Simple Efficient ...
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由 Q Liu 著作2023被引用 8 次 — This paper proposes a simple efficient policy optimization framework -- Optimistic NPG for online RL. Optimistic NPG can be viewed as a simple ...
Optimistic Natural Policy Gradient: a Simple Efficient ...
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由 Q Liu 著作被引用 8 次 — This paper proposes a simple efficient policy optimization framework—OPTIMISTIC NPG for online RL. OPTIMISTIC. NPG can be viewed as a simple combination of the ...
Optimistic Natural Policy Gradient: a Simple Efficient Policy...
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2024年2月25日 — This paper presents a model-free policy optimization algorithm Optimistic Natural Policy Gradient for online and episodic MDPs. The authors present sample ...
Optimistic natural policy gradient - ACM Digital Library
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2024年5月30日 — This paper proposes a simple efficient policy optimization framework-OPTIMISTIC NPG for online RL. OPTIMISTIC NPG can be viewed as a simple ...
Optimistic Natural Policy Gradient: a Simple Efficient ...
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2024年9月4日 — Optimistic NPG can be viewed as simply combining of the classic natural policy gradient (NPG) algorithm [Kakade, 2001] with optimistic policy ...
Optimistic Natural Policy Gradient: a Simple Efficient ...
arXiv
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由 Q Liu 著作2023被引用 8 次 — OPTIMISTIC NPG can be viewed as a simple combination of the classic natural policy gradient (NPG) algorithm [13] and an optimistic policy ...
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[PDF] Optimistic Natural Policy Gradient: a Simple Efficient ...
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Optimistic NPG stands as the first policy optimization algorithm that achieves polynomial sample complexity for learning near-optimal policies in the realm ...
a Simple Efficient Policy Optimization Framework for Online RL
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本文介绍了一种新的在线强化学习策略优化框架OPTIMISTIC NPG，该框架提高了探索环境下的样本效率，实现了最优的维度依赖性和多项式样本复杂度保证，从而学习到近似最优策略。
a Simple Policy Optimization Algorithm for Online Learning ...
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A simple efficient policy optimization framework—O PTIMISTIC NPG for online RL—is proposed to encourage exploration in online RL where exploration is ...
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2023年5月19日 — Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL. (arXiv:2305.11032v1 [cs.
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