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Constrained representation learning for recurrent policy optimisation under uncertainty
Adaptive Behavior ( IF 1.2 ) Pub Date : 2019-12-30 , DOI: 10.1177/1059712319891641
Viet-Hung Dang 1 , Ngo Anh Vien 2 , TaeChoong Chung 3
Affiliation  

Learning to make decisions in partially observable environments is a notorious problem that requires a complex representation of controllers. In most work, the controllers are designed as a non-lin...

中文翻译:

不确定性下循环策略优化的约束表示学习

学习在部分可观察的环境中做出决策是一个臭名昭著的问题,需要复杂的控制器表示。在大多数工作中,控制器被设计为非线性...
更新日期:2019-12-30
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