牛哥精选 · 半年

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📝 深度技术 arXiv AI 2026-06-10

Bellman-Taylor Score Decoding for Markov Decision Processes with State-Dependent Feasible Action Sets

提出贝尔曼-泰勒分数解码方法，解决状态依赖可行动作集下MDP的优化难题，为强化学习提供新视角。

arXiv:2606.10979v1 Announce Type: new Abstract: Many Markov decision processes (MDPs) in operations research have feasible actions that are state depe…

马尔可夫决策过程贝尔曼-泰勒分数解码状态依赖动作集强化学习优化算法

📝 深度技术 arXiv 机器学习 2026-05-26

A Contractive Feedback Semantics for Reinforcement Learning

从封闭马尔可夫决策过程跳脱，用组合视角打造强化学习的新型收缩反馈语义。

arXiv:2605.24759v1 Announce Type: new Abstract: Discounted reinforcement learning is usually presented through Bellman equations on closed Markov deci…

强化学习收缩反馈语义学马尔可夫决策过程组合视角

📝 深度技术 arXiv 机器学习 2026-05-19

Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes

提出首个在重尾MDP上同时实现随机与对抗环境最优遗憾的BoBW算法，突破保守局限。

arXiv:2602.01295v3 Announce Type: replace Abstract: We investigate episodic Markov Decision Processes with heavy-tailed losses (HTMDPs). Existing appr…

强化学习马尔可夫决策过程重尾分布 best-of-bo 遗憾界

📅 日期

2026-05-20 2026-05-19

🐂 牛哥精选

Bellman-Taylor Score Decoding for Markov Decision Processes with State-Dependent Feasible Action Sets

A Contractive Feedback Semantics for Reinforcement Learning

Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes

📅 日期