【5分鐘 Paper】Dueling Network Architectures for Deep Reinforcement Learning
論文題目：Dueling Network Architectures for Deep Reinforcement Learning 所解決的問題？ 主要貢獻是提出了一種新的應用於強化學習的神經網絡框架。 背景 之前對強化學習的改進主要是集中在對現有的網絡結構的改變，像什麼引入卷積神經網絡，LSTM和Autoencoder這些。而這篇文章是提出了一種新的神經網絡結構更好地去適應model-
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相關文章
- 1. 【5分鐘 Paper】Asynchronous Methods for Deep Reinforcement Learning
- 2. 【5分鐘 Paper】Continuous Control With Deep Reinforcement Learning
- 3. RL論文閱讀【三】Dueling Network Architectures for Deep Reinforcement Learning
- 4. 【5分鐘 Paper】Playing Atari with Deep Reinforcement Learning
- 5. 【5分鐘 Paper】Deep Reinforcement Learning with Double Q-learning
- 6. 【5分鐘 Paper】Deep Recurrent Q-Learning for Partially Observable MDPs
- 7. Deep Reinforcement Learning for Dialogue Generation
- 8. Paper reading: Playing Atari with Deep Reinforcement Learning
- 9. Paper Reading:Wide & Deep Learning for Recommender Systems
- 10. Deep Reinforcement Learning with Iterative Shift for Visual Tracking