Reinforcement learning and approximate dynamic programming for feedback control

By:

Lewis, Frank L

Contributor(s):

Material type: Text

TextSeries: IEEE Press series on computational intelligencePublication details: New Jersey: Wiley, c2013.Description: xxvi, 613 pages : illustrations ; 24 cmISBN:

9781118104200

Subject(s):

DDC classification:

003.5 23 LEW-R

LOC classification:

Q325.6 .R464 2013

Other classification:

TEC008000

Summary: "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"--Summary: "Reinforcement learning and adaptive control can be useful for controlling a wide variety of systems including robots, industrial processes, and economical decision making"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Books	IIITD Reference	Computer Science and Engineering	REF 003.5 LEW-R (Browse shelf(Opens below))	Not for loan		003899

Total holds: 0

"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 and adaptive control can be useful for controlling a wide variety of systems including robots, industrial processes, and economical decision making"--

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