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Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

von Bahare Kiumarsi, Bosen Lian, Frank L. Lewis, Hamidreza Modares und Wenqian Xue
Hardcover - 9783031452512
149,79 €
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Softcover - 9783031452543
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Weitere Formate

Softcover - 9783031452543
149,79 €

Beschreibung

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 challenges they face.

Details

Verlag Springer International Publishing
Ersterscheinung 06. März 2024
Maße 23.5 cm x 15.5 cm
Gewicht 600 Gramm
Format Hardcover
ISBN-13 9783031452512
Auflage 2024
Seiten 267

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