| PDP: parallel dynamic programming | |
Fei-Yue Wang ; Jie Zhang; Qinglai Wei; Xinhu Zheng; Li Li
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| 发表期刊 | IEEE/CAA Journal of Automatica Sinica
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| 2017 | |
| 卷号 | 4期号:1页码:1-5 |
| 摘要 | Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive dynamic programming (ADP) is first presented instead of direct dynamic programming (DP), and the inherent relationship between ADP and deep reinforcement learning is developed. Next, analytics intelligence, as the necessary requirement, for the real reinforcement learning, is discussed. Finally, the principle of the parallel dynamic programming, which integrates dynamic programming and analytics intelligence, is presented as the future computational intelligence. |
| 关键词 | Parallel Dynamic Programming Dynamic Programming Adaptive Dynamic Programming Reinforcementlearning Deep Learning Neural Networks Artificial Intelligence. |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/19739 |
| 专题 | 复杂系统管理与控制国家重点实验室_先进控制与自动化 |
| 推荐引用方式 GB/T 7714 | Fei-Yue Wang,Jie Zhang,Qinglai Wei,et al. PDP: parallel dynamic programming[J]. IEEE/CAA Journal of Automatica Sinica,2017,4(1):1-5. |
| APA | Fei-Yue Wang,Jie Zhang,Qinglai Wei,Xinhu Zheng,&Li Li.(2017).PDP: parallel dynamic programming.IEEE/CAA Journal of Automatica Sinica,4(1),1-5. |
| MLA | Fei-Yue Wang,et al."PDP: parallel dynamic programming".IEEE/CAA Journal of Automatica Sinica 4.1(2017):1-5. |
| 条目包含的文件 | 下载所有文件 | |||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| PDP Parallel Dynamic（3789KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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