| Title | : | Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games |
|---|---|---|
| Author | : | Bosen Lian, Wenqian Xue, Frank L. Lewis, Hamidreza Modares & Bahare Kiumarsi |
| Release | : | 2024-03-05 |
| Kind | : | ebook |
| Genre | : | Electrical Engineering, Books, Professional & Technical, Engineering, Science & Nature, Mathematics, Computers & Internet |
| Size | : | 18743568 |
| 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. |
