9783030609924 - handbook of reinforcement learning and control: 325 (studies in systems, decision and control, 325) (8 resultados)
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Editorial: Springer, 2022
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Taschenbuch. Condición: Neu. Handbook of Reinforcement Learning and Control | Kyriakos G. Vamvoudakis (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | xxiv | Englisch | 2022 | Springer | EAN 9783030609924 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot…]hartmann[at]springer[dot]com | Anbieter: preigu.
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Editorial: Springer, 2022
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Taschenbuch. 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 g…athered 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.
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Editorial: Springer, Berlin|Springer International Publishing|Springer, 2022
Serie: Libro 326 de 378 - Studies in Systems, Decision and Control
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.
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Editorial: Springer, Springer Jun 2022, 2022
Serie: Libro 326 de 378 - Studies in Systems, Decision and Control
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Taschenbuch. 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 gathe…red 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 860 pp. Englisch.
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Editorial: Palgrave Macmillan, 2022
Serie: Libro 326 de 378 - Studies in Systems, Decision and Control
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt 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 gather…ed 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.
