Name: Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games
SKU: 64797027
Price: 2617.05 MXN
Availability: InStock
Author: Bahare Kiumarsi;Wenqian Xue;Hamidreza Modares;Frank L. Lewis;Bosen Lian
ISBN: 9783031452543

portada Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Formato

Libro Físico

Editorial

Springer International Publishing AG

Autor

Bahare Kiumarsi;Wenqian Xue;Hamidreza Modares;Frank L. Lewis;Bosen Lian

Colección

Advances in Industrial Control

Año

2025

N° páginas

267

Encuadernación

Tapa Blanda

Dimensiones

23.5x15.5 cm

ISBN13

9783031452543

Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games

Bahare Kiumarsi;Wenqian Xue;Hamidreza Modares;Frank L. Lewis;Bosen Lian (Autor) · Springer International Publishing AG · Tapa Blanda

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Reseña del libro "Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games"

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.