English(EN) Expected Sample Complexity in Multi-Armed Bandits

为多臂老虎机样本复杂度提出新指标

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 12:16

本文在称为“期望近似正确”（ACE）的框架内，为随机多臂老虎机问题介绍了一种名为预期样本复杂度的新指标。作者证明，与高概率保证不同，ACE保证可以收敛到最优预期回报。他们还表明，确定性算法不适用于有利的ACE界限，并分析了随机算法，为已知和未知的次优水平建立了近乎匹配的下界。 AI

影响引入了一种新颖的理论框架来分析序贯决策算法，可能影响未来在强化学习领域的研究。

排序理由该集群包含一篇学术论文，详细介绍了用于序贯决策问题的新指标和分析框架。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

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Newsworthiness bucket: Tool; 该集群包含一篇学术论文，详细介绍了用于序贯决策问题的新指标和分析框架。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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Hugging Face Daily Papers TIER_1 English(EN) · 2026-10-07 12:16

多臂老虎机中的预期样本复杂度

Sample complexity is a widely used metric in sequential decision-making problems, defined as the number of suboptimal decisions during the interaction between the agent and an environment. We study the sample complexity of stochastic multi-armed bandit problems and introduce the …