【5分钟 Paper】Continuous Control With Deep Reinforcement Learning
论文题目：Continuous Control With Deep Reinforcement Learning 所解决的问题？ 这篇文章将Deep Q-Learning运用到Deterministic Policy Gradient算法中。如果了解DPG的话，那这篇文章就是引入DQN改进了一下DPG的state value function。解决了DQN需要寻找maximizes actio
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- 1. Continuous control with Deep Reinforcement Learning
- 2. 【5分钟 Paper】Playing Atari with Deep Reinforcement Learning
- 3. 解读continuous control with deep reinforcement learning（DDPG）
- 4. 【5分钟 Paper】Asynchronous Methods for Deep Reinforcement Learning
- 5. 【5分钟 Paper】Deep Reinforcement Learning with Double Q-learning
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- 7. DDPG，CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING 论文阅读
- 8. Paper: Continuous Deep Q-Learning with Model-based Acceleration
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相关文章
- 1. Continuous control with Deep Reinforcement Learning
- 2. 【5分钟 Paper】Playing Atari with Deep Reinforcement Learning
- 3. 解读continuous control with deep reinforcement learning（DDPG）
- 4. 【5分钟 Paper】Asynchronous Methods for Deep Reinforcement Learning
- 5. 【5分钟 Paper】Deep Reinforcement Learning with Double Q-learning
- 6. 【5分钟 Paper】Dueling Network Architectures for Deep Reinforcement Learning
- 7. DDPG，CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING 论文阅读
- 8. Paper: Continuous Deep Q-Learning with Model-based Acceleration
- 9. Paper reading: Playing Atari with Deep Reinforcement Learning
- 10. PR17.10.2:Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control