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English(EN) Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs

新的miss-MDP框架弥合了缺失数据理论与POMDPs的差距

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员引入了一个名为缺失MDPs (miss-MDPs) 的新框架，该框架将缺失数据理论整合到部分可观察马尔可夫决策过程 (POMDPs) 中。这种新颖的POMDPs子类专门处理观测函数缺失的场景，详细说明了各个状态特征未被观测到的概率。该工作侧重于通过从轨迹数据中学习来计算具有未知缺失函数的miss-MDPs的近优策略，并提供PAC算法，以高概率产生epsilon-最优策略。 AI

影响 为处理顺序决策问题中的缺失数据引入了新的理论框架，有可能提高AI代理在现实场景中的鲁棒性。

排序理由 介绍新颖理论框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

新的miss-MDP框架弥合了缺失数据理论与POMDPs的差距

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介绍新颖理论框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Nils Jansen ·

    Missingness-MDPs：连接缺失数据理论与POMDPs

    We introduce missingness-MDPs (miss-MDPs), a novel subclass of partially observable Markov decision processes (POMDPs) that incorporates the theory of missing data. A miss-MDP is a POMDP whose observation function is a missingness function, specifying the probability that individ…

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