书目名称 | Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games |
编辑 | Bosen Lian,Wenqian Xue,Bahare Kiumarsi |
视频video | http://file.papertrans.cn/469/468351/468351.mp4 |
概述 | Provides control engineers with a first look at state-of-the art inverse reinforcement learning methods.Comprehensive introduction combines with illustrative examples to bring readers up to speed.Algo |
丛书名称 | Advances in Industrial Control |
图书封面 |  |
描述 | .Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games. develops its specific learning techniques, motivated by application to autonomous driving and microgrid systems, with breadth and depth: integral reinforcement learning (RL) achieves model-free control without system estimation compared with system identification methods and their inevitable estimation errors; novel inverse RL methods fill a gap that will help them to attract readers interested in finding data-driven model-free solutions for inverse optimization and optimal control, imitation learning and autonomous driving among other areas... .Graduate students will find that this book offers a thorough introduction to integral and inverse RL for feedback control related to optimal regulation and tracking, disturbance rejection, and multiplayer and multiagent systems. For researchers, it provides a combination of theoretical analysis, rigorous algorithms, and a wide-ranging selection of examples. The book equips practitioners working in various domains – aircraft, robotics, power systems, and communication networks among them – with theoretical insights valuable in tackling the real-world challeng |
出版日期 | Book 2024 |
关键词 | Reinforcement Learning for Optimal Feedback Control; Integral Reinforcement Learning; Adaptive Dynamic |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-45252-9 |
isbn_softcover | 978-3-031-45254-3 |
isbn_ebook | 978-3-031-45252-9Series ISSN 1430-9491 Series E-ISSN 2193-1577 |
issn_series | 1430-9491 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |