【5分鐘 Paper】Deep Reinforcement Learning with Double Q-learning
論文題目：Deep Reinforcement Learning with Double Q-learning 所解決的問題？ Q-Learning算法中存在動作值函數過估計(overestimate action values)的問題(因爲其更新方程中包含一個maximization動作值函數的一項)，那這樣的過估計問題是否會對其算法性能有所影響呢？能不能去避免這樣的一種過估計問題呢？ 背景
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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】Asynchronous Methods for Deep Reinforcement Learning
- 4. 【5分鐘 Paper】Dueling Network Architectures for Deep Reinforcement Learning
- 5. Paper reading: Playing Atari with Deep Reinforcement Learning
- 6. RL論文閱讀【四】Deep Reinforcement Learning with Double Q-learning（Double DQN）
- 7. Paper Reading:NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
- 8. 【強化學習】Deep Reinforcement Learning with Double Q-learning（2015）
- 9. Paper: Continuous Deep Q-Learning with Model-based Acceleration
- 10. Playing atari with deep reinforcement learning