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Partially observable Markov decision processes and performance sensitivity analysis
Partially observable Markov decision processes and performance sensitivity analysis
PulseAugur coverage of Partially observable Markov decision processes and performance sensitivity analysis — every cluster mentioning Partially observable Markov decision processes and performance sensitivity analysis across labs, papers, and developer communities, ranked by signal.
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New framework synthesizes POMDP policies using sampling and model-checking
Researchers have developed a new framework to synthesize policies for Partially Observable Markov Decision Processes (POMDPs), which are used for decision-making under uncertainty. This approach combines sampling-based …
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新的MCTS分析为POMDP规划提供理论保证
研究人员开发了一种新的有限时间分析方法，用于蒙特卡洛树搜索（MCTS）在部分可观察马尔可夫决策过程（POMDPs）中的应用。这项工作为离散和连续观测空间提供了概率集中界，填补了像POMCP这样的MCTS风格求解器在理论保证方面的空白。所提出的方法Voro-POMCPOW使用Voronoi单元自适应地划分连续观测空间，以维持有限的分支因子，同时提供理论保证。