Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games
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- Hardcover ausgewählt
- Taschenbuch
- eBook
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Sprache:Englisch
Fr. 181.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
06.03.2024
Abbildungen
XX, 267 p. 43 illus., 41 illus. in color.
Verlag
SpringerSeitenzahl
267
Maße (L/B/H)
24.1/16/2.2 cm
Gewicht
600 g
Auflage
2024
Sprache
Englisch
ISBN
978-3-031-45251-2
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.
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