Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning

Research article (Information and Inference A Journal of the IMA, 2022) · cited 11× · AI/ML
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Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning

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Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning. Retrieved May 24, 2026, from https://4ort.xyz/entity/breaking-the-sample-complexity-barrier-to-regret-optimal-model-free-reinforcement-learning
MLA “Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/breaking-the-sample-complexity-barrier-to-regret-optimal-model-free-reinforcement-learning.
BibTeX @misc{4ortxyz_breaking-the-sample-complexity-barrier-to-regret-optimal-model-free-reinforcement-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning}}, year = {2026}, url = {https://4ort.xyz/entity/breaking-the-sample-complexity-barrier-to-regret-optimal-model-free-reinforcement-learning}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Breaking the sample complexity barrier to regret-optimal model-free reinforcement learning — https://4ort.xyz/entity/breaking-the-sample-complexity-barrier-to-regret-optimal-model-free-reinforcement-learning (retrieved 2026-05-24)

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