读论文-DARLA:Improving Zero-Shot Transfer in Reinforcement Learning

时间 2021-01-13

标签 zero-shot transfer learning reinforcement learning 繁體版

原文原文链接

DARLA:Improving Zero-Shot Transfer in Reinforcement Learning这篇文章发表于ICML2017，主要讲Reinforement learning算法在不同数据分布上的迁移。鉴于实验室讲论文讨论的要求，将该论文做成了ppt，供大家分享。总结，这篇文章关键点在于使用DAE将real world的state转换为latent state。另外，

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1. 【论文阅读】Discovering Reinforcement Learning Algorithms
2. 迁移学习论文阅读：Transfer Learning via Learning to Transfer
3. 论文阅读14：Reinforcement learning approach towards effective content recommendation in MOOC environments
4. Policy in Reinforcement Learning
5. 论文阅读：A Survey on Transfer Learning
6. Transfer Learning[论文合集]
7. RL论文阅读【四】Deep Reinforcement Learning with Double Q-learning（Double DQN）
8. 论文笔记：Learning how to Active Learn: A Deep Reinforcement Learning Approach
9. transfer learning
10. Policy Gradient Methods in Reinforcement Learning

>>更多相关文章<<