Reinforcement Learning: State-of-the-Art - Couverture souple

9783642446856: Reinforcement Learning: State-of-the-Art

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ISBN 10 : 364244685X ISBN 13 : 9783642446856

Editeur : Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2014

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This book presents up-to-date information on the main contemporary sub-fields of reinforcement learning, including partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations.

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�diteur: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Date d'�dition: 2014
Langue: anglais
ISBN 10: 364244685X
ISBN 13: 9783642446856
Reliure: Broch�
Nombre de pages: 638
�diteur: Wiering Marco, Van Otterlo Martijn
Coordonn�es du fabricant: non disponible
Personne responsable: CMN Printpool Inh. Mathis Neumann
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Reinforcement Learning: State-of-the-Art (Adaptation, Learning, and Optimization (12)) [Paperback] Wiering, Marco and van Otterlo, Martijn

Wiering, Marco [Editor]; van Otterlo, Martijn [Editor];

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Reinforcement Learning: State-of-the-Art (Adaptation, Learning, and Optimization, 12)

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Reinforcement Learning

Wiering, Marco|Otterlo, Martijn van

Edit� par Springer Berlin Heidelberg, 2014

ISBN 10 : 364244685X ISBN 13 : 9783642446856

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers all important recent developments in reinforcement learningVery good introduction and explanation of the different emerging areas in Reinforcement LearningIncludes a survey of previous papers written on the topicCo. N� de r�f. du vendeur 5061380

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Reinforcement Learning

Martijn van Otterlo

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg Apr 2014, 2014

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade.The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research.Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledgerepresentation in reinforcement learning settings. 672 pp. Englisch. N� de r�f. du vendeur 9783642446856

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Reinforcement Learning

Martijn van Otterlo

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg Apr 2014, 2014

ISBN 10 : 364244685X ISBN 13 : 9783642446856

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Taschenbuch. Etat : Neu. Neuware -Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade.The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 672 pp. Englisch. N� de r�f. du vendeur 9783642446856

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Reinforcement Learning : State-of-the-Art

Martijn van Otterlo

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2014

ISBN 10 : 364244685X ISBN 13 : 9783642446856

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade.The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research.Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledgerepresentation in reinforcement learning settings. N� de r�f. du vendeur 9783642446856

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