线,使

概括

离线强化学习 (RL) 代理可以通过解决数据稀疏性来改进,这是估计错误的关键因素. 我们的IEEDS方法使用V-nets和状态意识的稀疏性马尔科夫决策流程 (MDP) 来减轻这些错误以获得更好的性能.

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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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Types of Errors: Detection and Minimization01:12

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