【5分鐘 Paper】Continuous Control With Deep Reinforcement Learning
論文題目：Continuous Control With Deep Reinforcement Learning 所解決的問題？ 這篇文章將Deep Q-Learning運用到Deterministic Policy Gradient算法中。如果瞭解DPG的話，那這篇文章就是引入DQN改進了一下DPG的state value function。解決了DQN需要尋找maximizes actio
相關文章
- 1. Continuous control with Deep Reinforcement Learning
- 2. 【5分鐘 Paper】Playing Atari with Deep Reinforcement Learning
- 3. 解讀continuous control with deep reinforcement learning（DDPG）
- 4. 【5分鐘 Paper】Asynchronous Methods for Deep Reinforcement Learning
- 5. 【5分鐘 Paper】Deep Reinforcement Learning with Double Q-learning
- 6. 【5分鐘 Paper】Dueling Network Architectures for Deep Reinforcement Learning
- 7. DDPG，CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING 論文閱讀
- 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
- 更多相關文章...
- • ASP.NET HtmlSelect Control - ASP.NET 教程
- • SVN分支 - SVN 教程
- • Git五分鐘教程
- • JDK13 GA發佈：5大特性解讀
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
最新文章
- 1. 「插件」Runner更新Pro版，幫助設計師遠離996
- 2. 錯誤 707 Could not load file or assembly ‘Newtonsoft.Json, Version=12.0.0.0, Culture=neutral, PublicKe
- 3. Jenkins 2018 報告速覽，Kubernetes使用率躍升235%！
- 4. TVI-Android技術篇之註解Annotation
- 5. android studio啓動項目
- 6. Android的ADIL
- 7. Android卡頓的檢測及優化方法彙總（線下+線上）
- 8. 登錄註冊的業務邏輯流程梳理
- 9. NDK(1)創建自己的C/C++文件
- 10. 小菜的系統框架界面設計-你的評估是我的決策
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Continuous control with Deep Reinforcement Learning
- 2. 【5分鐘 Paper】Playing Atari with Deep Reinforcement Learning
- 3. 解讀continuous control with deep reinforcement learning（DDPG）
- 4. 【5分鐘 Paper】Asynchronous Methods for Deep Reinforcement Learning
- 5. 【5分鐘 Paper】Deep Reinforcement Learning with Double Q-learning
- 6. 【5分鐘 Paper】Dueling Network Architectures for Deep Reinforcement Learning
- 7. DDPG，CONTINUOUS CONTROL WITH DEEP REINFORCEMENT LEARNING 論文閱讀
- 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