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100 1 _aLian, Bosen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aIntegral and Inverse Reinforcement Learning for Optimal Control Systems and Games
_h[electronic resource] /
_cby Bosen Lian, Wenqian Xue, Frank L. Lewis, Hamidreza Modares, Bahare Kiumarsi.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXX, 267 p. 43 illus., 41 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
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347 _atext file
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490 1 _aAdvances in Industrial Control,
_x2193-1577
505 0 _a1. Introduction -- 2. Background on Integral and Inverse Reinforcement Learning for Dynamic System Feedback -- 3. Integral Reinforcement Learning for Optimal Regulation -- 4. Integral Reinforcement Learning for Optimal Tracking -- 5. Integral Reinforcement Learning for Nonlinear Tracker -- Integral Reinforcement Learning for H-infinity Control -- 6. Inverse Reinforcement Learning for Linear and Nonlinear Systems -- 7. Inverse Reinforcement Learning for Two-Player Zero-Sum Games -- 8. Inverse Reinforcement Learning for Multi-player Nonzero-sum Games.
520 _aIntegral 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.
541 _fUABC ;
_cPerpetuidad
650 0 _aControl engineering.
650 0 _aEngineering mathematics.
650 0 _aEngineering
_xData processing.
650 0 _aComputational intelligence.
650 0 _aAutomotive engineering.
650 1 4 _aControl and Systems Theory.
650 2 4 _aMathematical and Computational Engineering Applications.
650 2 4 _aComputational Intelligence.
650 2 4 _aAutomotive Engineering.
700 1 _aXue, Wenqian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aLewis, Frank L.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aModares, Hamidreza.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aKiumarsi, Bahare.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031452512
776 0 8 _iPrinted edition:
_z9783031452536
776 0 8 _iPrinted edition:
_z9783031452543
830 0 _aAdvances in Industrial Control,
_x2193-1577
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-45252-9
912 _aZDB-2-INR
912 _aZDB-2-SXIT
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