Manifold Regularized Reinforcement Learning
文献类型：期刊论文
| 作者 | Li, Hongliang1; Liu, Derong2; Wang, Ding3
|
| 刊名 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
 |
| 出版日期 | 2018-04-01 |
| 卷号 | 29期号:4页码:932-943 |
| 关键词 | Adaptive Dynamic Programming Approximate Dynamic Programming Approximate Policy Iteration (Api) Manifold Regularization Reinforcement Learning (Rl) |
| DOI | 10.1109/TNNLS.2017.2650943 |
| 文献子类 | Article |
| 英文摘要 | This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance. |
| WOS关键词 | TIME NONLINEAR-SYSTEMS ; VALUE FUNCTION APPROXIMATION ; SQUARES POLICY ITERATION ; DIMENSIONALITY REDUCTION ; LAPLACIAN FRAMEWORK ; GEOMETRIC FRAMEWORK ; ALGORITHMS ; REPRESENTATION ; MACHINES ; DESIGN |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000427859600014 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21992]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_智能化团队 |
| 作者单位 | 1.Tencent Inc, AI Platform Dept, Shenzhen 518057, Peoples R China 2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Hongliang,Liu, Derong,Wang, Ding. Manifold Regularized Reinforcement Learning[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(4):932-943. |
| APA | Li, Hongliang,Liu, Derong,&Wang, Ding.(2018).Manifold Regularized Reinforcement Learning.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(4),932-943. |
| MLA | Li, Hongliang,et al."Manifold Regularized Reinforcement Learning".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.4(2018):932-943. |
入库方式： OAI收割
来源：自动化研究所
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