Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (eBook)

Artikelnummer: 978-1-118-45397-1
Einband: Adobe Digital Editions
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Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.
Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.
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VerlagJohn Wiley & Sons
EinbandAdobe Digital Editions
Erscheinungsjahr2013
Seitenangabe929 S.
AusgabekennzeichenEnglisch
Masse7'501 KB
Auflage13001 A. 1. Auflage
PlattformEPUB
ReiheIEEE Press Series on Computational Intelligence
AutorLewis, Frank L. (Hrsg.) / Liu, Derong (Hrsg.)

Alle Bände der Reihe "IEEE Press Series on Computational Intelligence"

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