Isbn: 9783031546525 - applications of game theory in deep learning (16 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer International Publishing AG, Cham, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Paperback. Condizione: new. Paperback. This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer-Nature New York Inc, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Paperback. Condizione: Brand New. 96 pages. 9.25x6.10x0.20 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications.

  • Lingua: Inglese

    Editore: Springer International Publishing AG, Cham, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Paperback. Condizione: new. Paperback. This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Lingua: Inglese

    Editore: Springer, Springer Mär 2024, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications. 96 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, 2024

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    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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  • Lingua: Inglese

    Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game .

  • Lingua: Inglese

    Editore: Springer, Springer Mär 2024, 2024

    3031546520 / 9783031546525

    Serie: Libro 52 di 60 - SpringerBriefs in Computer Science

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book aims to unravel the complex tapestry that interweaves strategic decision-making models with the forefront of deep learning techniques. Applications of Game Theory in Deep Learning provides an extensive and insightful exploration of game theory in deep learning, diving deep into both the theoretical foundations and the real-world applications that showcase this intriguing intersection of fields. Starting with the essential foundations for comprehending both game theory and deep learning, delving into the individual significance of each field, the book culminates in a nuanced examination of Game Theory's pivotal role in augmenting and shaping the development of Deep Learning algorithms. By elucidating the theoretical underpinnings and practical applications of this synergistic relationship, we equip the reader with a comprehensive understanding of their combined potential. In our digital age, where algorithms and autonomous agents are becoming more common, the combination of game theory and deep learning has opened a new frontier of exploration. The combination of these two disciplines opens new and exciting avenues. We observe how artificial agents can think strategically, adapt to ever-shifting environments, and make decisions that are consistent with their goals and the dynamics of their surroundings. This book presents case studies, methodologies, and real-world applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 96 pp. Englisch.