Publicado por LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208434173 ISBN 13: 9786208434175
Idioma: Inglés
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208434173 ISBN 13: 9786208434175
Idioma: Inglés
Librería: California Books, Miami, FL, Estados Unidos de America
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Librería: Books Puddle, New York, NY, Estados Unidos de America
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Publicado por Scholars' Press Feb 2019, 2019
ISBN 10: 6138778707 ISBN 13: 9786138778707
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 45,90
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Artificial intelligence has made big steps forward with reinforcement learning (RL) in the last century, and with the advent of deep learning (DL) in the 90s, especially, the breakthrough of convolutional networks in computer vision field. The adoption of DL neural networks in RL, in the first decade of the 21 century, led to an end-to-end framework allowing a great advance in human-level agents and autonomous systems, called deep reinforcement learning (DRL). In this book, we will go through the development Timeline of RL and DL technologies, describing the main improvements made in both fields. Then, we will dive into DRL and have an overview of the state-of-the-art of this new and promising field, by browsing a set of algorithms (Value optimization, Policy optimization and Actor-Critic), then, giving an outline of current challenges and real-world applications, along with the hardware and frameworks used.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
EUR 80,09
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Añadir al carritoPaperback. Condición: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.
Librería: Zubal-Books, Since 1961, Cleveland, OH, Estados Unidos de America
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Añadir al carritoCondición: New. 672 pp., paperback, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Photos available upon request.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 250,46
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Librería: Broad Street Books, Branchville, NJ, Estados Unidos de America
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2014
ISBN 10: 364244685X ISBN 13: 9783642446856
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 406,59
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Añadir al carritoTaschenbuch. Condición: 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.
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2012
ISBN 10: 364227644X ISBN 13: 9783642276446
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 406,59
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Añadir al carritoBuch. Condición: 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.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 447,00
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 447,00
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Publicado por Springer-Verlag New York Inc, 2012
ISBN 10: 364227644X ISBN 13: 9783642276446
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 588,86
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Añadir al carritoHardcover. Condición: Brand New. 2012 edition. 672 pages. 9.25x6.25x1.75 inches. In Stock.
Publicado por Springer-Verlag New York Inc, 2014
ISBN 10: 364244685X ISBN 13: 9783642446856
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 587,79
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Añadir al carritoPaperback. Condición: Brand New. 2012 edition. 674 pages. 9.25x6.10x1.42 inches. In Stock.
Publicado por Scholars' Press Feb 2019, 2019
ISBN 10: 6138778707 ISBN 13: 9786138778707
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 45,90
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Artificial intelligence has made big steps forward with reinforcement learning (RL) in the last century, and with the advent of deep learning (DL) in the 90s, especially, the breakthrough of convolutional networks in computer vision field. The adoption of DL neural networks in RL, in the first decade of the 21 century, led to an end-to-end framework allowing a great advance in human-level agents and autonomous systems, called deep reinforcement learning (DRL). In this book, we will go through the development Timeline of RL and DL technologies, describing the main improvements made in both fields. Then, we will dive into DRL and have an overview of the state-of-the-art of this new and promising field, by browsing a set of algorithms (Value optimization, Policy optimization and Actor-Critic), then, giving an outline of current challenges and real-world applications, along with the hardware and frameworks used. 64 pp. Englisch.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 46,45
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence has made big steps forward with reinforcement learning (RL) in the last century, and with the advent of deep learning (DL) in the 90s, especially, the breakthrough of convolutional networks in computer vision field. The adoption of DL neural networks in RL, in the first decade of the 21 century, led to an end-to-end framework allowing a great advance in human-level agents and autonomous systems, called deep reinforcement learning (DRL). In this book, we will go through the development Timeline of RL and DL technologies, describing the main improvements made in both fields. Then, we will dive into DRL and have an overview of the state-of-the-art of this new and promising field, by browsing a set of algorithms (Value optimization, Policy optimization and Actor-Critic), then, giving an outline of current challenges and real-world applications, along with the hardware and frameworks used.
Librería: moluna, Greven, Alemania
EUR 39,32
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Fenjiro YoussefFenjiro Youssef, born in Morocco in 1978. He received the Master of degree in Computer Science from INPL, France, in 2001. In 2002, he joined Maroc Telecom where he currently holds the position of Project Manager Offic.
Publicado por LAP LAMBERT Academic Publishing, 2025
ISBN 10: 6208434173 ISBN 13: 9786208434175
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 61,63
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 70,82
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