【5分鐘 Paper】Asynchronous Methods for Deep Reinforcement Learning
論文題目：Asynchronous Methods for Deep Reinforcement Learning 所解決的問題？ 在強化學習算法中agent所觀測到的data是 non-stationary和strongly correlated的。通過設置memory的方式可以 reduces non-stationarity and decorrelates updates，但是會限制這
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相關文章
- 1. 【5分鐘 Paper】Continuous Control With Deep Reinforcement Learning
- 2. 【5分鐘 Paper】Playing Atari with Deep Reinforcement Learning
- 3. 【5分鐘 Paper】Dueling Network Architectures for Deep Reinforcement Learning
- 4. 【5分鐘 Paper】Deep Reinforcement Learning with Double Q-learning
- 5. 論文筆記之：Asynchronous Methods for Deep Reinforcement Learning
- 6. 【5分鐘 Paper】Deep Recurrent Q-Learning for Partially Observable MDPs
- 7. 【5分鐘 Paper】(TD3) Addressing Function Approximation Error in Actor-Critic Methods
- 8. Deep Reinforcement Learning for Dialogue Generation
- 9. Deep Reinforcement Learning
- 10. [Reinforcement Learning] Policy Gradient Methods