| 書目名稱 | Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games | | 編輯 | Bosen Lian,Wenqian Xue,Bahare Kiumarsi | | 視頻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 | | 叢書名稱 | Advances in Industrial Control | | 圖書封面 |  | | 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 | | 關(guān)鍵詞 | 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 |
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