This work aims to study off-policy evaluation (OPE) under scenarios where two key reinforcement learning (RL) assumptions – temporal stationarity and individual homogeneity are both violated. To ha...

中文翻译：

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双非均匀环境中的离策略评估


这项工作旨在研究在两个关键的强化学习（RL）假设（时间平稳性和个体同质性）都被违反的情况下的离策略评估（OPE）。至哈...