| 书目名称 | Reinforcement Learning for Optimal Feedback Control |
| 副标题 | A Lyapunov-Based App |
| 编辑 | Rushikesh Kamalapurkar,Patrick Walters,Warren Dixo |
| 视频video | |
| 概述 | Illustrates the effectiveness of the developed methods with comparative simulations to leading off-line numerical methods.Presents theoretical development through engineering examples and hardware imp |
| 丛书名称 | Communications and Control Engineering |
| 图书封面 |  |
| 描述 | .Reinforcement Learning for Optimal Feedback Control .develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. .To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements...This monograph provides academic researchers with backgrounds in diverse discipline |
| 出版日期 | Book 2018 |
| 关键词 | Nonlinear Control; Lyapunov-based Control; Reinforcement Learning; Optimal Control; Dynamic Programming; |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-78384-0 |
| isbn_softcover | 978-3-030-08689-3 |
| isbn_ebook | 978-3-319-78384-0Series ISSN 0178-5354 Series E-ISSN 2197-7119 |
| issn_series | 0178-5354 |
| copyright | Springer International Publishing AG 2018 |
发表于 2025-3-21 17:35:21
