Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 250,22
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Añadir al carritoCondición: New. In.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 267,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology.The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including:deep learning;artificial intelligence;applications of game theory;mixed modality learning; andmulti-agent reinforcement learning.Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 400,82
Cantidad disponible: 2 disponibles
Añadir al carritoHardcover. Condición: Brand New. 857 pages. 9.25x6.10x1.89 inches. In Stock.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 206,31
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Jun 2021, 2021
ISBN 10: 3030609898 ISBN 13: 9783030609894
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 246,09
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology.The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including:deep learning;artificial intelligence;applications of game theory;mixed modality learning; andmulti-agent reinforcement learning.Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative. 860 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2021
ISBN 10: 3030609898 ISBN 13: 9783030609894
Librería: moluna, Greven, Alemania
EUR 223,97
Cantidad disponible: Más de 20 disponibles
Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Enriches understanding of the applications of reinforcement learning for control of dynamic systemsCollates research from a wide-range of experts, creating a comprehensive guideDiscusses both theoretical and practical aspects of machine lea.
Idioma: Inglés
Publicado por Springer, Springer Jun 2021, 2021
ISBN 10: 3030609898 ISBN 13: 9783030609894
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 267,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology.The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including:deep learning;artificial intelligence;applications of game theory;mixed modality learning; andmulti-agent reinforcement learning.Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 860 pp. Englisch.